Internet Utilization Behaviour of Agricultural Students of Swami Keshwanand Rajasthan Agricultural University, Bikaner
Thesis
Submitted to the Swami Keshwanand Rajasthan Agricultural University, Bikaner in partial fulfillment of the requirement for the degree of
Master of Science
in the
Faculty of Agriculture (Extension Education)
By
Suresh Garhwal
2010
Swami Keshwanand Rajasthan Agricultural University, Bikaner S.K.N. College of Agriculture, Jobner
CERTIFICATE-I
Dated :------.2010
This is to certify that Mr. Suresh Garhwal has successfully completed the comprehensive examination held on ------as required under the regulation for Master’s degree.
(N.K. Sharma ) Head Department of Extension Education S.K.N. College of Agriculture, Jobner
Swami Keshwanand Rajasthan Agricultural University, Bikaner S.K.N. College of Agriculture, Jobner
CERTIFICATE-II
Dated :------2010
This is to certify that the thesis entitled “Internet Utilization Behaviour of Agricultural Students of Swami Keshwanand Rajasthan Agricultural University, Bikaner”, submitted for the degree of Master of Science in the subject of Extension Education embodies bonafide research work carried out by Mr. Suresh Garhwal under my guidance and supervision and that no part of this thesis has been submitted for any other degree. The assistance and help received during the course of investigation have been fully acknowledged. The draft of the thesis was also approved by the advisory committee on ......
(I. M. Khan) (N.K. Sharma) Major Advisor Head
Department of Extension Education S.K.N. College of Agriculture,
Jobner
(G. L. Keshwa) Dean S.K.N.College of Agriculture, Jobner Swami Keshwanand Rajasthan Agricultural University, Bikaner S.K.N. College of Agriculture, Jobner
CERTIFICATE-III
Dated :------2010
This is to certify that the thesis entitled “Internet Utilization Behaviour of Agricultural Students of Swami Keshwanand Rajasthan Agricultural University, Bikaner”, submitted by Mr. Suresh Garhwal to Rajasthan Agricultural University, Bikaner, in partial fulfilment of the requirements for the degree of Master of Science in the subject of Extension Education after recommendation by the external examiner, was defended by the candidate before the following members of the examination committee. The performance of the candidate in the oral examination on his thesis has been found satisfactory. We therefore, recommend that the thesis be approved.
(I. M. Khan) Major Advisor
(J. P. Yadav) (K.N. Gupta) Advisor Advisor
(N.K. Sharma) (R. C. Kumawat) Head Dean, PGS Nominee Department of Extension Education
(G.L. Keshwa) Approved Dean S.K.N. College of Agriculture, DEAN Jobner POST GRADUATE STUDIES RAJASTHAN AGRICULTURAL UNIVERSITY, BIKANER
Swami Keshwanand Rajasthan Agricultural University, Bikaner S.K.N. College of Agriculture, Jobner
CERTIFICATE-IV
Dated :------2010
This is to certify that Mr. Suresh Garhwal of the Department of Extension Education, S.K.N. College of Agriculture, Jobner has made all corrections/modifications in the thesis entitled “Internet Utilization Behaviour of Agricultural Students of Swami Keshwanand Rajasthan Agricultural University, Bikaner”, which were suggested by the external examiner and the advisory committee in the oral examination held on ------2010. The final copies of the thesis duly bound and corrected were submitted on ------2010 and forwarded herewith for approval.
(I. M. Khan) Major Advisor (N.K. Sharma) Head Department of Extension Education
(G.L. Keshwa) Dean S.K.N. College of Agriculture, Jobner
APPROVED
DEAN, PGS RAU, Bikaner
CONTENTS
CHAPTER PARTICULARS PAGE NO. NO.
1. INTRODUCTION ………..
2. REVIEW OF LITERATURE ………..
3. THEORETICAL ORIENTATION ………..
4. RESEARCH METHODOLOGY ………..
5. RESULTS AND DISCUSSION ………..
6. SUMMARY AND CONCLUSION ………..
BIBLIOGRAPHY ………..
ABSTRACT (English) ………..
ABSTRACT (Hindi) ………..
APPENDICES ………..
ACKNOWLEDGEMENT
With great reverence, I express my warmest feeling with deep sense of gratitude to my advisor and chairman of my advisory committee Dr. I.M. Khan Assistant Professor, Department of Extension Education, S.K.N. College of Agriculture, Jobner (Swami Keshwanand Rajasthan Agricultural University, Bikaner). I have no words to express my heartfelt thanks to him for his illuminating guidance, unfailing encouragement, scholarly suggestions, unique supervision, constructive criticism, sympathetic attitude and keen interest during the course of this investigation and preparation of this manuscript.
I am heartly thankful to member of my advisory committee Dr. J.P. Yadav, Assistant Professor, Department of Extension Education, Dr. K.N. Gupta, Associate Professor, Department of Statistics, Dr. R.C. Kumawat, Associate Professor and Head (Dean PGS nominee), Department of Agricultural Economics, for their sincere advice, critical suggestions and kind help during the period of investigation.
I am thankful to Dr. N.K. Sharma, Associate Professor and Head, Department of Extension, for their encouragement and full cooperation during the research programme. I record my sincere thanks to Dr. G.L. Keshwa, Dean, S.K.N. College of Agriculture, Jobner for his continuous support to academic pursuits and facilities provided for the execution of the present research work. I also want to pay my cordial thanks to Dr. G. S. Bangarva, Dr. H. L. Jat, Dr. Sangram Singh, and Sh. Manish Agarwal and all the staff members of the Department of Extension Education, S.K.N. College of Agriculture, Jobner for providing all sorts of help and co-operation as when needed. I especially indebted to my colleagues Miss Ankita and Mr. Rohitash, Subhash, Badhalaji, Shripalji, Ganga Ram and Shankar for not only being excellent fellow batch mates but understanding friends without those help and support things this work have not been smooth.
Direction is not enough to express my gratitude to my Mother Smt. Vimla Devi and Father Sh. Ram Kumar, My younger brother Rakesh and younger sister Suman, and sangeeta and other family members, whose selfless love, filial affection, constant encouragement, obstinate sacrifices, expectation and blessing have always been the most vital source of inspiration and motivation in my life. Their memories gave me a sense of relief after hours of tedious work during my research.
I am also greatful to Sh. Suresh Yadav, Vimal Computers, Jobner for typing the manuscript neatly and efficiently within a very short period.
Last but not least, a million thanks to God, the almighty who made me to do this task and made every Job a success for me. My heart is budding with ecstasy and bliss at this moment when I am extending my thanks to all who co-operated me directly or indirectly.
Jobner Date: (Suresh Garhwal)
L I S T O F T A B L E S
Table Particulars Page No. No. 4.1 Locale of study and selection of sample ……… 5.1.1 Distribution of internet utilizing agricultural students according ……… to their gender 5.1.2 Distribution of internet utilizing male and female agricultural ……… students according to their age 5.1.3 Distribution of internet utilizing male and female agricultural ……… students according to their marital status 5.1.4 Distribution of internet utilizing male and female agricultural ……… students according to their educational qualification 5.1.5 Distribution of internet utilizing male and female agricultural ……… students according to their academic achievement (OGPA obtained during last semester) 5.1.6 Distribution of internet utilizing male and female agricultural ……… students according to their fathers education 5.1.7 Distribution of internet utilizing male and female agricultural ……… students according to their mothers education 5.1.8 Distribution of internet utilizing male and female agricultural ……… students according to their fathers occupation 5.1.9 Distribution of internet utilizing male and female agricultural ……… students according to their native place 5.1.10 Distribution of internet utilizing male and female agricultural ……… students according to their type of family 5.1.11 Distribution of internet utilizing male and female agricultural ……… students according to their size of family 5.1.12 Distribution of internet utilizing male and female agricultural ……… students according to their family income (Rs. per month)
Table Particulars Page No. No. 5.1.13 Distribution of internet utilizing male and female agricultural ……… students according to their medium of instruction during school days 5.1.14 Distribution of internet utilizing male and female agricultural ……… students according to their exposure to extra – curricular activities 5.1.15 Distribution of internet utilizing male and female agricultural ……… students according to their training being extended by the college library as to how to use Internet 5.1.16 Distribution of internet utilizing male and female agricultural ……… students according to their study of any course, to know the use of Internet 5.1.17 Distribution of internet utilizing male and female agricultural ……… students according to their type of course studied 5.1.18 Distribution of internet utilizing male and female agricultural ……… students according to their expertise in navigating the web 5.1.19 Distribution of internet utilizing male and female agricultural ……… students according to their place of living at the time of education 5.1.20 Distribution of internet utilizing male and female agricultural ……… students according to their wish to migrate abroad 5.1.21 Distribution of internet utilizing male and female agricultural ……… students according to their wish to get higher academic degree 5.1.22 Distribution of internet utilizing male and female agricultural ……… students according to their frequency of library use 5.1.23 Distribution of internet utilizing male and female agricultural ……… students according to their wish to serve in different areas 5.2.1 Experience of internet use of internet utilizing male and female ……… agricultural students
Table Particulars Page No. No. 5.2.2 Preference of access to internet of internet utilizing male and ……… female agricultural students 5.2.3 Expenditure incurred in using internet (Rs. Per month) by ……… internet utilizing male and female agricultural students 5.2.4 Frequency of Internet use of internet utilizing male and female ……… agricultural students 5.2.5 Purpose of internet use of internet utilizing male and female ……… agricultural students 5.2.6 Possession of E-mail ID of internet utilizing male and female ……… agricultural students 5.2.7 Frequency of e-mail use of internet utilizing male and female ……… agricultural students 5.2.8 Purpose of E-mail use of internet utilizing male and female ……… agricultural students 5.2.9 Chatting to make communication by internet utilizing male and ……… female agricultural students 5.2.10 Frequency of Chatting of internet utilizing male and female ……… agricultural students 5.2.11 Use of different search-engines by internet utilizing male and ……… female agricultural students 5.2.12 Rating Internet as sources of information by internet utilizing ……… male and female agricultural students 5.2.13 Satisfaction with Internet facility of internet utilizing male and ……… female agricultural students 5.2.14 Preference of Internet on other media for getting information by ……… internet utilizing male and female agricultural students 5.2.15 Browsing techniques for getting required information from the ……… Internet by internet utilizing male and female agricultural students
Table Particulars Page No. No. 5.2.16 Frequency of locating the desired information on the Internet ……… by internet utilizing male and female agricultural students 5.2.17 Activities during Internet use by internet utilizing male and ……… female agricultural students 5.2.18 Preference of timing of access to internet by internet utilizing ……… male and female agricultural students 5.2.19 Orientation to Internet source of internet utilizing male and ……… female agricultural students 5.2.20 Internet utilization level of internet utilizing male and female ……… agricultural students 5.3.1 Effect of internet utilization on the academic performance of ……… the male and female agricultural students 5.3.2 Effect of internet utilization on the non academic performance ……… of the male and female agricultural students 5.4.1 Association of age of internet utilizing male and female ……… agricultural students with their internet utilization 5.4.2 Association of marital status of internet utilizing male and ……… female agricultural students with their internet utilization 5.4.3 Association of educational qualification of internet utilizing ……… male and female agricultural students with their internet utilization 5.4.4 Association of Academic achievement (OGPA) of internet ……… utilizing male and female agricultural students with their internet utilization 5.4.5 Association of Education of father of internet utilizing male and ……… female agricultural students with their internet utilization 5.4.6 Association of Education of mother of internet utilizing male ……… and female agricultural students with their internet utilization
Table Particulars Page No. No. 5.4.7 Association of occupation of father of internet utilizing male ……… and female agricultural students with their internet utilization 5.4.8 Association of native place of internet utilizing male and female ……… agricultural students with their internet utilization 5.4.9 Association of type of family of internet utilizing male and ……… female agricultural students with their internet utilization 5.4.10 Association of size of family of internet utilizing male and ……… female agricultural students with their internet utilization 5.4.11 Association of family income of internet utilizing male and ……… female agricultural students with their internet utilization 5.4.12 Association of medium of instruction during school days of ……… internet utilizing male and female agricultural students with their internet utilization 5.4.13 Association of training being extended by the college library of ……… internet utilizing male and female agricultural students with their internet utilization 5.4.14 Association of computer course studied to know use of internet ……… by internet utilizing male and female agricultural students with their internet utilization 5.4.15 Association of type of computer course studied to know use of ……… internet by internet utilizing male and female agricultural students with their internet utilization 5.4.16 Association of Expertise in navigating web of internet utilizing ……… male and female agricultural students with their internet utilization 5.4.17 Association of Place of living at the time of education of ……… internet utilizing male and female agricultural students with their internet utilization
Table Particulars Page No. No. 5.4.18 Association of wish to migrate abroad of education of internet ……… utilizing male and female agricultural students with their internet utilization 5.4.19 Association of wish to get higher academic degree of internet ……… utilizing male and female agricultural students with their internet utilization 5.5.1 Physical constraints faced by the internet utilizing male and ……… female agricultural students 5.5.2 Technical constraints faced by the internet utilizing male and ……… female agricultural students 5.5.3 Economic constraints faced by the internet utilizing male and ……… female agricultural students 5.5.4 Operational constraints faced by the internet utilizing male and ……… female agricultural students 5.5.5 Psychological constraints faced by the internet utilizing male ……… and female agricultural students
L I S T O F F I G U R E S
Figure Particulars Page No. No. 3.1 Tentative paradigm of the study ……… 4.1 Locale of study and selection of sample ……… 5.1.1 Distribution of internet utilizing agricultural students according ……… to their gender 5.1.2 Distribution of internet utilizing male and female agricultural ……… students according to their age 5.1.3 Distribution of internet utilizing male and female agricultural ……… students according to their marital status 5.1.4 Distribution of internet utilizing male and female agricultural ……… students according to their educational qualification 5.1.5 Distribution of internet utilizing male and female agricultural ……… students according to their academic achievement (OGPA obtained during last semester) 5.1.6 Distribution of internet utilizing male and female agricultural ……… students according to their fathers education 5.1.7 Distribution of internet utilizing male and female agricultural ……… students according to their mothers education 5.1.8 Distribution of internet utilizing male and female agricultural ……… students according to their fathers occupation 5.1.9 Distribution of internet utilizing male and female agricultural ……… students according to their native place 5.1.10 Distribution of internet utilizing male and female agricultural ……… students according to their type of family 5.1.11 Distribution of internet utilizing male and female agricultural ……… students according to their size of family 5.1.12 Distribution of internet utilizing male and female agricultural ……… students according to their family income (Rs. per month)
Figure Particulars Page No. No. 5.1.13 Distribution of internet utilizing male and female agricultural ……… students according to their medium of instruction during school days 5.1.14 Distribution of internet utilizing male and female agricultural ……… students according to their exposure to extra – curricular activities 5.1.15 Distribution of internet utilizing male and female agricultural ……… students according to their training being extended by the college library as to how to use Internet 5.1.16 Distribution of internet utilizing male and female agricultural ……… students according to their study of any course, to know the use of Internet 5.1.17 Distribution of internet utilizing male and female agricultural ……… students according to their type of course studied 5.1.18 Distribution of internet utilizing male and female agricultural ……… students according to their expertise in navigating the web 5.1.19 Distribution of internet utilizing male and female agricultural ……… students according to their place of living at the time of education 5.1.20 Distribution of internet utilizing male and female agricultural ……… students according to their wish to migrate abroad 5.1.21 Distribution of internet utilizing male and female agricultural ……… students according to their wish to get higher academic degree 5.1.22 Distribution of internet utilizing male and female agricultural ……… students according to their frequency of library use 5.1.23 Distribution of internet utilizing male and female agricultural ……… students according to their wish to serve in different areas 5.2.1 Experience of internet use of internet utilizing male and female ……… agricultural students
Figure Particulars Page No. No. 5.2.2 Preference of access to internet of internet utilizing male and ……… female agricultural students 5.2.3 Expenditure incurred in using internet (Rs. Per month) by ……… internet utilizing male and female agricultural students 5.2.4 Frequency of Internet use of internet utilizing male and female ……… agricultural students 5.2.5 Purpose of internet use of internet utilizing male and female ……… agricultural students 5.2.6 Possession of E-mail ID of internet utilizing male and female ……… agricultural students 5.2.7 Frequency of e-mail use of internet utilizing male and female ……… agricultural students 5.2.8 Purpose of E-mail use of internet utilizing male and female ……… agricultural students 5.2.9 Chatting to make communication by internet utilizing male and ……… female agricultural students 5.2.10 Frequency of Chatting of internet utilizing male and female ……… agricultural students 5.2.11 Use of different search-engines by internet utilizing male and ……… female agricultural students 5.2.12 Rating Internet as sources of information by internet utilizing ……… male and female agricultural students 5.2.13 Satisfaction with Internet facility of internet utilizing male and ……… female agricultural students 5.2.14 Preference of Internet on other media for getting information by ……… internet utilizing male and female agricultural students 5.2.15 Browsing techniques for getting required information from the ……… Internet by internet utilizing male and female agricultural students
Figure Particulars Page No. No. 5.2.16 Frequency of locating the desired information on the Internet ……… by internet utilizing male and female agricultural students 5.2.17 Activities during Internet use by internet utilizing male and ……… female agricultural students 5.2.18 Preference of timing of access to internet by internet utilizing ……… male and female agricultural students 5.2.19 Orientation to Internet source of internet utilizing male and ……… female agricultural students 5.2.20 Internet utilization level of internet utilizing male and female ……… agricultural students 5.3.1 Effect of internet utilization on the academic performance of ……… the male and female agricultural students 5.3.2 Effect of internet utilization on the non academic performance ……… of the male and female agricultural students 5.4.1 Factors associated with the internet utilization of agricultural ……… students 5.5.1 Physical constraints faced by the internet utilizing male and ……… female agricultural students 5.5.2 Technical constraints faced by the internet utilizing male and ……… female agricultural students 5.5.3 Economic constraints faced by the internet utilizing male and ……… female agricultural students 5.5.4 Operational constraints faced by the internet utilizing male and ……… female agricultural students 5.5.5 Psychological constraints faced by the internet utilizing male ……… and female agricultural students
L I S T O F A P P E N D I C E S
Appendix Particulars Page No. No. I Covering letter sent to the experts ……… II Interview schedule A. Personal and family characteristics of the agricultural ……… students B. Internet utilization pattern of agricultural students ……… C. Effect of internet utilization on overall performance of ……… agricultural students D. Constraints faced in internet utilization by agricultural ……… students
1 INTRODUCTION
Communication is crucial for social change by which alteration occurs in the same structure and function of a social system. The 21st century is witnessing a communication revolution with information processing and retrieval which are being reliably done at incredible speeds.
Encyclopedia Britannica defines communication as "The exchange of meanings between individuals through a common system of symbols". The word communication has been originated from the Latin word "Communis" which means common, sharing of ideas, information and feelings between individuals, so that a common understanding is established between the person sending the information and the person receiving the same. Therefore, a conscious attempt to establish commonality is communication. Communication is essential to all human associations. All type of developments be it the personal development of individual or nation's development in any field such as agriculture, industry, health, culture etc. depends mainly on the success of communication. Communication can play a powerful role in nation building and contributes significantly to bring about social change in the desired direction.
The role of communication in development is not only to provide information and create awareness among the public or society but to implement the new ideas which cause change. Communication plays a vital role in the diffusion of knowledge and new technologies but this can be possible only when communication followed by appropriate media. "Internet technology of communication, its universal acceptance by communities and subsequent globalization within a short span of a few years is a classic example of what sustained investment and commitment to research and development have been achieved." (Agarwala, Kamlesh, N. et al. 2000).
"The internet is a world wide network of networks. It is a conglomeration of smaller networks and other connected machines spanning the entire globe.
"The internet is a global system of public and private computer networks that allow desktop computer to exchange data. Messages and files with any of the millions of other computer with connections to the internet".
"The internet is an existing area where you can find information about almost every topic you have books, encyclopedias, magazines, articles and every other type of reference material at your fingertips. In addition you have access to expert opinion on various topics and can communicate with people offering commentaries / views on all ranges of the subjects.
Internet is an inter-connection between several computers of different types belonging to various networks all over the globe. It is a network of networks. The kind of colossal powers that the internet gives yours machine is mind- bogging. To send or receive data within a matter of seconds to someone placed beyond the pacific was unthinkable before the advent of the internet. The internet represents the transformation and evolution of the entire information age. It is due to these factors that people all over the globe have recognized the internet as their latest developmental tool. "Internet" is one of the tool of communication. Internet has changed life as a few things have done. It has added a new dimension to our existence by placing within easy reach, mind boggling range of information. It gives each of us the option to be as publisher of our information and views, and as the number of people on internet multiply and commerce transforms the internet, the opportunities are getting larger.
In the era of networked information, Internet, the largest worldwide network of networks, has emerged as the most powerful tool for an instant access to information. Information is now just a „finger touch‟ distance away from the user and it would not be inappropriate to say that the Internet has become the biggest global digital information library which provides the fastest access to the right kind of information in nano-seconds of time to end-user at any time and at any place in the world. The Internet has become the most extensively used information source that empowers the average person to get in roaming with the latest information. Today's users can no longer depend on conventional information sources to cope with the latest developments in their respective fields.
The internet offers many options for computer users to communicate with others like chat, mail, telephone, browse special field for references and so on. The imperative necessity is to mount intense national as well as international efforts in the interest of achieving a bright common future by using the internet technology for all humanity on our planet. So, for this purpose there is a need to develop human resources.
In India, the internet services were officially made available to public from 15th August 1995 onwards through Videsh Sancher Nigam limited (VSNL). Today there are many service providers offering internet services. There are many ways by which you can communicate with people on the internet.
The most common use of internet is electronic mail (e-mail). By using e-mail a user can send text, pictures, sounds, programmes or even movies to any other person anywhere in the world. With introduction of www internet has become so popular in any research and academic institution that it has billions of users today and the number is increasing every day. There are a number of news group on the internet. The messages sent to a news group are simply posted on the electronic notice board. Anyone can see these messages.
Internet provides a tremendous wealth of information. There are millions of computer programs and data that have been made available to the users. These files may be text files, graphics files, sound files, full motion video files or even program files. There are number of ways in which you can obtain the desired information. World wide web (www) is set of interconnected pages that represent specific web sites. These web pages are rich in illustration, graphics and multimedia contents. File Transfer Protocol (FTP) enables files to be downloaded from various computer file servers and archives. Many hardware and software manufactures, educational organizations and institutions have set up FTP sites from which you can download software, instruction materials, updates, etc. Hyper Text Transfer Protocol (HTTP) is the preferred means of transferring hypertext documents over the internet.
Today in corporation and classroom in the US, Europe and even Asia, the internet is becoming not just a prerequisite, reinforcement and remedial learning tool; it is enabling many non-credit and credit course and even full degree programmes to be offered entirely online. In India today, institution like IGNOU, BITS Pilani, IIT Delhi and Kanpur have all initiated new programmes using the internet for education and the leading private sector computer training institutions like Aptech and NIIT have demonstrated success in online education not just in India but worldwide.
According to India broadband forum upto 31st March (2008), the number of Internet users in Asia is 5,29,701,704. Though Asia has only 16% of populations of the world, 37.6% of total internet users are Asian which is great. Of them around 60 million are from India. India is 3rd in Asia (1st is China (220 million) and 2nd is Japan (87.5 million)) and 4th in world ((1st is China (220 million), 2nd is USA (216 million) and 3rd is Japan (87.5 million)) as per as internet users are concerned. India has 13% of internet users in Asia and 7.36% that of the world. But the sorrowful fact is only 5.3% of people in India use internet. The reason of this is most of the people in India don‟t know computer. 70% of people who know computer have used internet which is a healthy sign.
In India 19-40 years age group is major section (85%) using internet in India. 85% of internet users in India are male which not a very good sign is. Among working women, only 11% use internet. The ratio is almost half (6%) in case of non-working women and even worst in case of house-wives (2%). The scenario is much better in case of young men (33%). Also 15% older men, 14% school going kids and 21% college students use internet in India. 46% of net users are graduate, 26% are post- graduate. Among these, 2/3 rd of user use internet 2-3 times a week. 62% uses internet from office as in most of the offices, it‟s free.
Mumbai has the maximum number of internet users (3.24 million) in India followed by Delhi (2.66 million). The top ten cities where people use internets are Mumbai, Delhi, Bangalore, Kolkata, Chennai, Pune, Hydrabad, Ahmedabad, Surat and Nagpur. The total numbers of internet users of those 10 cities are 37% of the total numbers of internet users in India.
Now take a look which types of sites majority of users browse. Most of the users use net for emailing (95%) which is obvious. Next is job searching (73%) showing crisis of getting job in India followed by chatting sites (62%), social networking sites (51%) and quite interestingly mathematical sites (48%).
According to India broadband form (2008) The top ten sites internet users browse in India are Yahoo, Google India, Google, Orkut, Rediff, Youtube, Blogger.com, Windows Live, Rapid Share, Wikipedia . Though internet ownership had seen growth of 32% as compared to 2007 which is a delighting fact, whereas, only 5.3% people used internet in India which is very low. Most of the users were male (85%). The female percentage should increase. Maximum number of users were from top 10 cities (37%). So, the internet usage in rural areas is very less. Most of the users were male (85%).
According to the “India Online” study from Juxt Consult (2007). Internet usage in India continues to grow at a slow but steady pace, both in breadth and depth, with the overall internet-using population in urban India reaching 30.32 million - a growth of 28% from April 2006 to April 2007. Of the 30.32 million urban internet users, 25.17 million (83%) log on at least once a month; the balance of 5.15 million (17%) are occasional users, according to the study. The penetration of the internet among urban Indians stands at 9% now, assuming the total urban population at 336 million, Juxt Consult said.
India as on September 2008, had 45.3 million active internet users. This is according to the I-Cube [Internet in India] Study released today and conducted annually by IMRB International and Internet and Mobile Association of India [IAMAI]. Active internet users are those who have used the internet at least once in the last one month – this is an internationally accepted benchmark for enumerating internet users.
Urban users continue to dominate internet use contributing to 42 million of the 45 million odd users. In September last 2007, the number of active internet users in urban India was 36 million showing a year on year growth of less than 13 per cent. Commenting on the study Dr. Subho Ray, president, IAMAI, said, “the growth rate was alarming compared with the rest in past years as well as with some other countries notably where the number of internet users are more than 250 million”
The Internet revolution seems to be in full swing, but is India really plugged into the global community it represents? Maybe yes, maybe no. As the Internet spins a web of interconnectivity around the globe, as it grows literally by the hour, India is struggling, not to catch up but to keep from falling further and further behind.
Inside India, things do seem to be improving. Five years ago there was limited Internet access but only in a few major cities, all in the hands of the government. VSNL, the agency responsible for Internet activities, and the DOT (Department of Telecommunications) provided an agonizingly erratic connectivity, with miserly bandwidth and far too few phone lines. Connection rates ran as low as 5% (for every 20 dialups you might get connected once) and users were frequently cut off. And the rates for this pathetic level of service were among the highest in the world. Domestic users paid about $2 per hour, and lease lines, for the few companies that could afford them, ranged over $2000 per month for a 64 Kpbs line. By the end of 1998, after three years of government monopoly, there were barely 150,000 Internet connections in India.
Today (midyear 2000) the government monopoly is largely over. Dozens of small to large Internet Service Providers have set up shop, triggering a price war and an improvement of service. Users are now estimated at over 2 million, with a growth predicted to reach 50 million in the next five years. Small Internet kiosks have set up even in small towns, and the governments, both State and Central are pushing for growth in the Internet sector. Internet is the new buzzword. The many small tutorial colleges that pushed computer software courses of variable quality are now in a hardsell scramble to push Net related content. The Internet represents the new wealth frontier for the middle classes - a good salary and a clean job, and for a few, the chance to go abroad.
The internet is clearly an ideal medium for delivering true learning because it is based on an interconnected architecture that allows communication and collaboration, can be enriched with multimedia capability that enhances the learning experience. It enables true student -centered learning by ensuring that:
Students learn the way that suits them best in environment of anonymity.
Students control the content and pace and share perspectives with peers and faculty. Opportunities are provided for exploration.
Students get rehearsal time.
Student-to-student and faculty-to-student interaction is enhanced.
To explore an enormous scope of using internet facilities in all research and academic institutions students, research scholars can link themselves to remote computer via the internet and gain access to the data, information and programs stored on it and they can do almost anything like sending and receiving messages, receiving news update about specific events or topics, reading or copying information stored on other computers, reading newspapers, magazines and newsletters, downloading computer software, sharing of expensive hardware, centralized administration of all computers, posting and reading public messages to exchange news and information about certain topics or area of interest.
The adoption of internet facilities into the research, education and extension is to use the potential of the new information and communication tools to revolutionize an outmoded NARS, to better prepare students and scientists for the information age and accelerate national development efforts.
Statement and problem of study
The Internet has emerged as a powerful educational tool. With the increasing impact of information and communication technologies on higher education, all those concerned with higher education are attempting to grasp how ICT could help in modernizing the process of teaching, learning and research. With the advent of the Internet, following dilemma arise in higher educational system:
Learner is not dependent on teacher for interaction; and
Teachers can give lectures virtually to unknown learners.
So, in this era, teachers and students can carry forward their work on the Internet in ways that are similar to and tightly intertwined with the traditional ways that they learn, teach and study in libraries, classrooms, laboratories, seminars, conferences, etc. The Internet can provide access to essentially unlimited resources of information not conventionally obtainable through other means.
Today, Agricultural colleges are playing an important role in imparting technical education. The Agriculturist, who are the outcomes of these colleges, require the latest and pinpointed information in their respective fields. Due to the high cost of Agricultural information resources, developing countries cannot provide these resources to their users. But the Internet with its advantages, make the way for the developing countries to access information at a very low cost.
The ever increasing number of people accessing Internet coupled with recent explosion of information resources on the Internet, may have considerable implications for teaching, learning and research. Teachers and students are depending more and more on the Internet for their various educational purposes. The present survey is, therefore, an attempt to assess the effectiveness of Internet as an educational tool, and what role it actually plays in the educational system with special reference to the Agricultural colleges in the state of Rajasthan.
The Internet is an inseparable part of today‟s Agricultural educational system. Agricultural colleges invest a good deal of amount on providing this facility to both the teachers and students. It is, therefore, important to find out up-to what extent they are utilizing this facility. Internet use is a staple of college students‟ educational experience. They use the internet to communicate with professors and classmates, to do research, and to access library materials. For most college students the internet is a functional tool, one that has greatly changed the way they interact with others and with information as they go about their studies. The college experience is not only about learning in the classroom, it is also about encountering as they do for their education. But just as they use the internet to supplement the formal parts of their education, they go online to enhance their social lives.
As Agricultural colleges provide Internet facility to both the teachers and the students and expect them to utilize it for education purposes, it is necessary to conduct a study to determine whether Internet is used for academic activities and how the Internet has influenced the academic efficiency of the target users. The study also explores the satisfaction level of the users with the Internet facility provided by the Agricultural colleges under study. The study has particularly been taken up to assess the benefits of Internet over conventional documents.
The study includes only those Agricultural colleges which are engaged in imparting degree level courses in the field of Agricultural & technology. The study is primarily concerned with the Agricultural
Looking to the spectacular scope of internet, the students and faculty of the Swami Keshwanand Rajasthan Agricultural University, (SKRAU) have been providing internet facility from 2001 onwards to perform triple function of teaching, research and extension education in effective manner.
This facility for connecting students and faculties with each corner of world reduce the time lag to a considerable extent. It helps academicians, research workers and students to get quick solution of their questions and queries. This facility makes possible to keep a live contact among the scientists, academicians, research scholars and students of the university globally. The value and effectiveness of any communication system can be judged through the assessment of involvement of its real users in it. What are the opportunities and limitations of the internet as a tool for education and how can it make a real difference to the development of our great nation and how students are living in the future with today's technology were provided the motivation.
The study of the personal characteristics of the respondents will be helpful to enumerate the internet utilization pattern of the students. The analysis of the internet utilization pattern of the agriculture students will be helpful in providing the base-line for developing internet technology programmes, whereas the findings related to the effect of internet utilization on over all performance of the respondents and the constraints encountered will be helpful for the implementers in selecting the target group for implementing the programmes related to internet.
The results of this study may act as guidelines to the students, educationists, policymakers and planners administrators, extension workers, social scientists, teachers, academic institutions, parents and other people who are engaged in the communication technology in one way or the other.
Looking to all these aspects, a research project entitled as “Internet Utilization Behaviour of Agricultural Students of Swami Keshwanand Rajasthan Agricultural University, Bikaner”. was undertaken with following specific objectives:
Objectives of the study
(i) To study the personal and family characteristics of the respondents.
(ii) To analyze the internet utilization pattern of the agricultural students. (iii) To find out the effect of internet utilization on over all performance of the agricultural students.
(iv) To study the factors associated with the internet utilization of agricultural students.
(v) To identify the constraints faced in internet utilization by the agricultural students.
Scope of the study
Despite the young age of the Internet, it has grown at an extremely rapid pace due largely to how easily accessible it has become to users. Each day, something new emerges via the Internet, whether it be a game, a user-created video, or a piece of music that is shared with the world. Looking forward, it will continue to grow and it is likely that today's innovations will be obsolete tomorrow. It is important for users and providers, both of service and content, to be aware of what is happening. While certain trends are apparent and intelligent speculation can lead to good ideas about where the Internet is headed, the truth is that the future of the Internet remains unknown. Some may consider this distressing, but most are probably excited at the thought, and ultimately, at the possibilities.
Limitations of the study
Any human effort, however earnest it may be, is not devoid of limitations. This research study is also no exception to this truth.
1. The present study has the usual limitations of the social science research.
2. The present study has obvious limit as regards to time, study area, sample size, and other limited research facilities usually faced by a single student investigator.
3. It also suffered from the usual limitation due to lack of precision and accuracy, which is commonly found in the exploratory type of studies. 4. The present study restricted in selection of respondents from only SKRAU Bikaner of Rajasthan state. Therefore the findings revealed from the present study could not be generalized on a larger basis.
Layout of the thesis
Six chapters have been complied from presenting the details of the study. The first chapter introduction includes the problem statement, objectives, scope and limitations of the study. The second chapter review of literature helps in understanding the past studies and experiences. The third chapter deals with theoretical orientation. The fourth chapter gives the details of methodology. The fifth chapter highlights the findings of the investigation and discussion on them. A brief summary and conclusion of the dissertation have been presented in the sixth chapter followed by “bibliography”. The „appendices‟ appear at the end of the thesis.
2 REVIEW OF LITERATURE
The chapter is devoted to review of literature relevant to the topic of the study. An endeavor has been mode to present here a review of studies or pertinent literature, which is likely to have direct learning on this study. Keeping is view the objectives of the study the review has been presented under following heads :-
2.1 Personal characteristics of the respondent
Loyd and Grossard (1984) found that females have lower scores on computer related technology competencies than their counterparts. Zidon and Miller (1990) reported that weak relationship between gender and with perception of computer use.
Singh and Singh (1991) reported that 18.40 per cent of the women scientists were from villages, 23.32 per cent from towns, 20.86 per cent from small cities, 18.40 per cent from big cities and 19.02 per cent from metropolitan cities.
Patel (1993) reported that majority (55.00 per cent) of the research scientists had PhD degree.
Goh (1997) found that friends and family members were the key influencing factors that encouraged the use of internet. However, the high cost of computers and computer peripherals was the main deterrent for non-users.
Goh et al. (1997), Lee (1997) and Pang (1997) identified several factors that influenced the use of Internet in the Klang Valley, namely, education, affordability, and the need for infotainment. Education and a positive attitude toward IT were necessary prerequisites for IT acculturation. In the three studies, it was found that largely academicians and professionals used Internet
Kosambi (1997) found that 48.65, 43.24, 6.10 and 59.45 per cent of girls had participated or membership in NSS and NCC, extension club, student council respectively.
Lee (1997) found that 26.00 per cent of his respondents did not have basic computer skills. Mahipal and Prasad (1997) reflected that majority (66.10 per cent) of the subject matter specialists had rural and 30.90 per cent from urban background.
Pang (1997) noted that knowledge or communication motivated the use of Internet among respondents.
Shashaani (1997) found that gender differences in internet access and usage was high and in turn had influenced the knowledge possession.
Richard C. Sherman et al. (1998) reported that when men and women were statistically equated in terms of voluntary activities (MUD, USENET, WWW, Chat Email) their attitudinal differences were eliminated but their self-perceptions of familiarity were not. The latter finding may reflect a cultural stereotype of computer expertise as a male-specific quality. That is, in judging their level of familiarity with computers, not men and women may implicitly use a male comparison target.
Sherman et al. (1998) observed that men had significantly higher levels of participation that women in familiarity and interne activities.
James et al. (1999) reported that for teachers, Internet technology can be considered a new form of expertise that is being imposed upon or at least being integrated into, the practice of teaching. Teachers, at all levels in their careers, are encountering the demands of Internet technological expertise in unique ways. King and Martin (1999) indicated that internet has been a male domain since its beginning. The gender gap in internet use has narrowed in recent years but has not closed entirely.
Christian End (2000) examined gender differences in internet use and investigated attitudinal correlates of Internet experience over a year‟s time. The results suggested that the internet gender gap may be narrowing but is still significant. Implications are discussed for higher education, where the curriculum necessitates the use of computers.
David (2000) reported that Edmonton public schools strives to ensure that students were provided with a safe and secure learning environment when engaged in educational assignment importing Internet activities students use computers for activities that 90 hand in hand with our understanding of what constitutes a traditional childhood communicate and form relationship as children always have.
Moreover, Laite (2000) surveyed 406 graduate and undergraduate students from Shippensburg University. The survey showed that 57.6% of the undergraduate students used the Internet 1-2 times per week and another 37.1% used it 1-2 times daily. More than 50% of the graduate students used Internet 1-2 times per week and 37.7% used it 1-2 times daily. The survey showed that the most used Internet service was e-mail. A hundred percent of the graduates and undergraduate students used e- mail service.
Ruth (2000) reported that younger generation has sown much internet towards internet communication and possessed more knowledge pertaining to internet technology. Sherif and Khan (2000) found that 53 per cent of the respondents were males and the rest females. No gross variation in time spent before the internet among boys and girls was observed. This was found to be universally true as opposed to the popular perception that girls spend less time on the internet.
Sood (2000) reported that local language has a predominant role in accessing information through internet and many people use English to access the internet as most of the websites are in English.
Anonymous (2001*) concluded that family income remains an indicator of whether a person uses a computer or the Internet. Individuals who live in high-income households are more likely to be computer and Internet users than those who live in low-income households. This relationship has held true in each successive survey of computer and Internet use.
Anonymous (2001**) reported that in September 2001, people living in each urban/rural category, non-central city urban, central city urban, and rural had higher rates of Internet use.
Anonymous (2001**) reported that rates of Internet use show a similar pattern. Internet use rates climb steadily as age increases for children through young adults, level off at relatively high rates for people between ages 26 and 55, and then fall among people at higher ages. Jessic Donn et al. (2001) indicated several possible explanations for graduate student‟s greater acceptance of forming relationships on the internet. Graduate students, being older and therefore closer to the age at which many people marry, may have greater empathy for the desire to meet people, and may also have difficulty in doing so through traditional means, and so are more open to using other methods. A second possible explanation of their findings in study was that graduate students may already be somewhat accustomed to using the internet for other purposes, such as making professional contacts and doing research.
Anonymous (2002**) reported that college students find out about the library‟s website from multiple sources, including from their professors and teaching assistants (49%), by looking it up themselves (45%), from classes about using the library (34%) and from librarians (27%).
Bonk (2002) concluded that about 45.00 per cent of the respondents had concerned with job related skill and computer programming skill.
Bonk (2002) reported that nearly one fourth of the participants were under age of 36, half were 36 to 50 years old and slightly more than one quarter were over age 50 years
Bonk (2002) opined that 3.00 per cent of the Internet users had high school diplomas, 8.00 per cent obtained some type of professional certification beyond high school, 35.00 per cent possessed bachelor‟s degrees, 41.00 per cent had master‟s degrees, 8.00 per cent had advanced degrees and remaining 5.00 per cent had earned doctoral degree.
Catherine and Banji (2002) reported that 50.00 per cent of the academician respondents working in university were at „Lecturer‟ grade while only 17.80 per cent were below this grade. 96.40 per cent of the respondents had at least a Masters degree, while in addition 32.10 per cent had Doctorates (Ph.D.'s). Those without Masters degrees are mostly „Tutorial Fellows‟ and a few „Assistant Lecturers‟ 40.70 per cent obtained their highest qualifications from Kenya and 33.30 per cent from Europe. Further he reported that higher degree holder academician respondents working in university tend to use the Internet more intensely because a large number obtained their postgraduate qualifications in developed countries, where the use of computers was entrenched within the institutions.
Curtis (2002) reported that the age of Internet user respondents was quite varied ranges from 35 to 50 years the most prevalent online skills learned were computer application and software skills (64.00 per cent) as well as technical skills (50.00 per cent)
Douglas and Thomas (2002) reported that at first glance, the activity associated with the Internet project had a little time giving direction and students were very active. Students were very eager to help each other and teachers spent most of their time facilitating student work students had many opportunities to tell teachers what they had found and it was common to hear teachers respond with comments such as “I didn‟t know that” But most of the assignments offered students some degree of choice, increasing their level of interest and providing the opportunity to relate to their experiences. John et al. (2002) revealed that 20 per cent of teachers consider themselves well prepared to use technology in their classes.
Krishnatray and Kulshrestha (2002) concluded that among the Internet Uses College going boys and girls most of them were graduates and three per cent were post graduates.
Murali (2002) studied that majority of Internet users were under 35 years old male with a university education and high income, urban based and English speaking.
Patel (2002) reported that only 17.00 per cent of the respondents had low gain in knowledge, 65.00 per cent had medium, while almost 18.00 per cent could gain knowledge by viewing multimedia.
Sadiq et al. (2002) reported that as far as teachers themselves are concerned, majority of them think that the Internet has helped them in collecting updated material for teaching in their courses, and that the Internet has enhanced their knowledge as far as teaching and research interests are concerned. They also believe that the Internet has facilitated in improving curricula and teaching methods. But nevertheless they do emphasize on the need for new methods to be supplemental to traditional classroom teaching and not as a replacement. Moreover, teachers who are strong with their Internet usage skills are more likely to use Internet technologies in course content preparation. Anonymous (2003a) reported that to succeed in a web- based course, students should be motivated and self discipline, self reliance and self direction are the minimum required items to complete the course work at a distance successfully through Internet.
Anonymous (2003) suggested that to succeed in Web- based courses, students should be motivated and self-directed. The minimum required items to complete the course work at a distance successfully are (1) Seriousness: Online classes aren't for goof-offs who seek easy credits. Virtual students should expect to spend at least as much time on homework as those in traditional courses. (2) Self-Disciplined: It is up to students to budget there time and keep up with assignments. They must create and stick to their own schedules. (3) Self-reliance: The ability to independently solve problems or research information is needed. Questions can be answered by e-mail, but that takes time. (4) Careful Reading Skills: Because classroom lectures are replaced primarily by written words, students need to be careful and slow-thoughtful readers and (5) Computer Skills: Students must be comfortable using computers and the Internet that includes e-mail, Web browsing, downloading and word processing.
Patel and Patel (2003) concluded that Internet is a tool having potential to contribute to agricultural development as one can access to vast global information. Ali (2004) reported that majority (89.30 per cent) of respondents had graduate degree, 2.10 per cent had master degree and 4.30 per cent had from other qualification.
Chauhan (2004) furnished that slightly more than half of the Internet user students had small size of family.
Chauhan (2004) indicated that independents factors like age, education; exposure in extra curricular activities and library exposure were observed significant with Internet exposure of college students. He further concluded that majority of the Internet students had above 23 years of age (51.67 per cent), first class academic performance (51.67 per cent), above SSC level of education of their father (83.33 per cent), up to SSC or more than that level education of their mother (70.00 per cent), native place in rural area (51.66 per cent), nuclear and small size of family (51.66 per cent), aspiration to go abroad either for further study or for permanent settling (66.67 per cent), wish to get higher academic degree (51.67 per cent), low level of exposure of extra curricular activity and everyday exposure of library ( 75.00 per cent).
Kalra (2004) reported that 75% of the internet users were between the age groups of 15-25 years; among those 79.13% users were males. And further among those, 68.25% were students, 21.25% belonged to service class, 10.50% belongs to business class. Singh et al. (2004) reported that majority (80.00 per cent) of them possessed B Sc Agri degree while, 20.00 per cent was M sc Agri.
Chauhan (2005) concluded that academically less active students were more active in computer and had less computer nervousness.
Mishra et al. (2005) reported that the majority of students (85.71%) use internet. Out of the internet users 67.71% were the male students and 52.29% were the female students.
Patel and Chauhan (2005) reported that majority of the internet user postgraduate students of Agriculture College were studying in M.Sc, (Ag.) (65.00%). Majority of them had above 23 years of age (51.67%), first class (51.67%), above S.S.C. level of education of their father (83.33%), up to S.S.C. or more than that level education of their mother (70.00%), native place in rural area (51.66%), nuclear and small size of family (51.66%), aspiration to go abroad either for further study or for permanent settling (66.67%), wish to get higher academic degree (51.67%), low level of exposure of extra curricular activity and everyday exposure of library (75.00%).
Patel and Chauhan (2005) reported that all most similar level of Internet exposure was seen among the students who wanted to have higher academic degree and those who did not want higher academic degree. Patel and Chauhan (2005) reported that the level of Internet exposure among those postgraduate students was observed better who had higher level of library exposure.
Parmar (2005) reported that majority (61.67 per cent) of the agricultural scientists belonged to middle age group.
Shingare (2005) opined that less than half of the teachers (43.20 per cent) had low participation in extra curricular activities.
Brown and Baer (2006) examined the use of e-marketing by small farms (n=300) in twelve states in Northeastern USA, during April 2005. A majority of the farms surveyed had no website for their business. Farms with websites generally had higher levels of gross farm sales than did farms without websites. A higher percentage of farms with websites earned more than 75% of their household income from the farm than did farms without websites. Respondents from farms with websites generally had higher education levels than those not using a website for their farm business. Farmers used a variety of methods and personnel to develop their websites. Most websites provide a way to email the farmer in addition to information on products and the farm. A majority provided times of operation, directions, and prices. More than 40% of the farms with websites took orders over the internet for their products in 2004.
Luque-Martinez et. al. (2007) Observed modeling of usage behaviour of new information technologies is of great utility to managers who need to evaluate the probability of success in the introduction of these technologies. The present study empirically contrasts the capacity of Davis' Technology Acceptance Model (MIS Quarterly (1989) 13(3), 319-340) to help understand the determinants of the intention to use the Internet to search for holiday information. Data for this study were obtained from a questionnaire survey carried out in June 2004-June 2005 among tourists (n=296) in Andalusia, Spain. The findings show that the above theory does explain the intention to use the Internet on the part of the tourist, but it should be expanded to take account of the tourist's satisfaction with previous experiences of searching for holiday information.
Taragola and Lierde (2007) presented at a conference in Glasgow, the UK, from 2-5 July 2007 organized by the European Federation for Information Technology in Agriculture, Food and Environment. A survey was carried out in 2005 amongst 208 Flemish enterprises (64 growing greenhouse vegetables, 29 growing field vegetables, 62 growing ornamental crops, and 53 growing perennial crops such as fruit trees). Computers are used by 189 enterprises (91% of total), and internet and email by 174 (92%). Data are presented on relationships with personal use of computers and internet, age, educational level, enterprise size. Constraints limiting computer use and consequences of low computer use are also discussed.
Boschetti et al. (2008) observed three-dimensional virtual globes are radically changing the way geographic information is perceived by the public. This article describes how NASA World Wind, an open source virtual globe, is currently being used for visualization of the MODIS burned area product. The procedures adopted for converting the product into a format compatible with World Wind, as well as the spatial generalization of these data at different scales, are described. Directions to instructions on how to obtain the MODIS burned area product visualization imagery and use it in World Wind are included. This article highlights the potential benefits of integrating the visualization capability of virtual globes into the next generation of remotely sensed product internet analysis and distribution systems.
Hunter et al. (2008) observed most weight-loss research targets obese individuals who desire large weight reductions. However, evaluation of weight-gain prevention in overweight individuals is also critical as most Americans become obese as a result of a gradual gain of 1-2 pounds per year over many years. Method: This study evaluated the efficacy of an Internet- based program for weight-loss and weight-gain prevention with a two-group, prospective, randomized controlled trial. A military medical research center with a population of 17 000 active-duty military personnel supplied 446 overweight individuals (222 men; 224 women) with a mean age of 34 years and a mean BMI of 29. Recruitment and study participation occurred 2003-2005 and data were analyzed in 2006. Participants were randomly assigned to receive the 6-month behavioral Internet treatment (BIT, n=227) or usual care (n=224). Change in body weight, BMI, percent body fat, and waist circumference; presented as group by time interactions, were measured. Results: After 6 months, completers who received BIT lost 1.3 kg while those assigned to usual care gained 0.6 kg (F< sub>(df=366)=24.17; I<0.001). Results were similar for the intention-to- treat model. BIT participants also had significant changes in BMI (-0.5 vs +0.2 kg/m2; F< sub>(df=366)=24.58); percent body fat (-0.4 vs +0.6%; F< sub>(df=366)=10.45); and waist circumference (-2.1 vs -0.4 cm; F< sub>(df=366)=17.09); p<0.001 for all. Conclusions: Internet-based weight-management interventions result in small amounts of weight loss, prevent weight gain, and have potential for widespread dissemination as a population health approach.
Masionyte and Zaltauskiene (2008) discussed the computerization of the rural areas in Lithuania, particularly in the households and in public services. Statistical information shows that internet access is available in every fourth household in the rural area. It is also most often used in the schools, libraries or at public internet access points. Public services which have already been automated are social insurance payments, customs declaration, employment services, public libraries and the like.
Sanjiv-Sharma (2008) observed the challenges and prospects relevant to the use of ICT [Information Communication Technology] in the agricultural business sector in India are discussed. The largest Internet-based initiative (e-choupal) in rural India, which aims to empower small farmers with readily accessible on-line knowledge and real-time linkage to world markets, is highlighted.
2. Internet utilization pattern
Becker (1998) conducted a study on the Internet use by 2250 teachers from public and private schools in the U.S. The study revealed that 90% of the teachers had Internet access. More than half of the teachers (59%) had Internet access at home. A majority of the teachers (68%) used Internet to find information resources for preparing their lessons.
Dorothy et al. (1998) concluded that primary teachers use ICT primarily to support classroom practice; secondary teachers use it as much or more for professional development and personal use as in the classroom. The teachers recognized a range of benefits for pupils and for them; the overall perception of the value of ICT among the teachers was positive. Further he reported that that Internet was available in the majority of secondary schools, the level of use of WWW and e-mail was observed still relatively low. This is likely to be a combination of lack of knowledge. The talent to use ICT effectively and appropriately is essential to allow learners to acquire and exploit information within every sphere of human activity.
Henry (1998) reported that a majority of teachers (68 per cent) use the Internet in their effort to find information resources for use in their lessons, and more than one-quarter of all teachers report doing this on a weekly basis or more often (28 per cent ). Teachers who used the Internet in this way typically have either home or classroom access. Both home and classroom access were about equally related to use, and teachers who have the combination of both home and classroom access reported the most frequent use, with 46 per cent of such teachers reporting weekly or more frequent use. It was also seen that even among teachers with home and classroom Internet access, more teachers reported only occasional use of the Internet for lesson preparation than reported use of Internet on at least a weekly basis. The areas of professional use of the Internet by teachers were seen in case of e-mail with teachers from other schools and publishing on the World Wide Web. Far fewer teachers engaged in these types of communications than use Internet as an information-gathering tool to obtain resources for lesson preparation, only 16 per cent of teachers communicated by e-mail with teachers from other schools as often as five times during the school year. It was also seen that, relatively few teachers have begun posting information, suggestions, opinions or student work on the World Wide Web, whereas relatively small per cent age of teachers, published information on the Web.
Henry (1998) concluded that the teachers with less than four years of teaching experience are slightly less likely than other teachers to use the Internet with students. However, their younger age makes them more comfortable with the Internet in terms of their own use. Teachers under age 30 in their first few years of teaching were the ones most likely to use the Internet professionally and overall, teachers under 30 were also more likely than older teachers to consider the Internet to be essential teaching tool. Further same author concluded that teachers who reported that their school provided them with their own computer were more likely to believe that classroom Internet is essential to teaching and was more likely to use the Internet as well.
Singh (1998) conducted a research study on the use of Internet by the librarians in Malaysia. The main findings of the study indicated that 90% of the respondents used the Internet for work related purposes. Most of the respondents were recent users.
Becker (1999) reported that 24.00 per cent of teachers used Internet both at home and classroom followed by 35.00 per cent at home, and 26.00 per cent had not using Internet at any place. Only 15.00 per cent of them use Internet in the classroom.
Becky et al. (1999) reported that most teachers indicated that professional development activities were available to them on a number of topics on Internet. Teachers who spent more time in professional development on Internet reported feeling better prepared than their colleagues. The one-third of teachers reported feeling well prepared or very well prepared to use computers and the Internet for classroom instruction, with less experienced teachers indicating they felt better prepared to use technology than their more experienced colleagues.
Bavakutty and Salih (1999) conducted a study at Calicut University, which showed that students, research scholars, and teachers used the Internet for the purpose of study, research and teaching respectively. The purposes of Internet use were: sending and receiving e-mails in connection with academic requirements, making a search on library catalogues, downloading images and communication with the peer.
Cassandra (1999) reported that when teachers were asked the degree to which they used computers or the Internet to prepare for and manage their classes. Thirty-nine per cent of public school teachers with access to computers or the Internet in their classroom or elsewhere indicated they used computers or the Internet a lot to create instructional materials, and 34 per cent reported using computers a lot for administrative record keeping. George et al. (1999) reported that Teachers were already using Internet technology in a variety of ways for Internet research and to access current events or archived information, such as from CNN or other media sites.
Kooganurmath and Jange (1999) conducted a study, which revealed that a majority of the users used the Internet for communication, followed by the access to information. More than 70% of the users used it for higher studies and only 39% used it for discussions with peer groups. The most used services of Internet were e-mail, the Web, discussion forums, FTP and Telnet.
A study conducted by Mahajan and Patil (1999) revealed that the purpose of using Internet by research workers at Pune University was to conduct literature search; for students was to know curriculum based information; for teachers to find supporting information to write articles.
Neil Marriott et al. (1999) reported that e-mail and internet use was frequent. International students were found to use the University's ICT provision more than home students, but this was mainly due to e- mail and internet uses. One reason was that international students could keep in touch with friends and family via the e-mail and use the internet to access 'home' news and current affairs.
Sharma and Chauhan (1999) and Jagdeeshwara (1994) observed significant relationship between mass media exposure and modernization.
Voorbij (1999) examined the use of the Internet amongst students and academicians in the Netherlands. A questionnaire was distributed among 1000 members of the academic community and three focus-group interviews were also held with faculty members. The study revealed that the Web was being used primarily to search general, factual, ephemeral or very specific information. The study also revealed that students and academicians faced many problems while searching the Web.
Williams (1999) reported the use of information technology and the Internet in his project entitled "Information Technology in Michigan: Adult and Teen Survey Report." The results indicated that the majority of the respondents (72%) used the Internet at least once a week and 45% at least once a day. Amritpal Kaur (2000) conducted a survey regarding the use of Internet facility at the Guru Nanak Dev University, Amritsar. The study indicated that all respondents used Internet for sending e-mail and 82% for Web. More than 60% of the respondents used Internet for primary information. 38% for secondary and only 15% used it for consulting OPACs. A majority of the respondents i.e. 75.6% faced the problem of slow Internet connectivity. All respondents used search engines to browse the required information. More than one third of the respondents typed the web address directly and only 1.5% used subscription databases. The results of the study further showed that more than 80% of the respondents felt that in comparison to traditional documents, Internet was time saving, easy to use, more informative, more useful and more preferred.
Chandran (2000) conducted a study at S V University, Tirupathi, which showed that more than 25% of the respondents used the Internet for 2-3 times a week and more than 56% used it for accessing information. A majority of the respondents used the Web and e-mail services of Internet. The purposes of using Internet included communication and information gathering. The sources used for identifying information about Internet included website itself, journals and magazines, staff and newspapers. A majority of the respondents used general websites as compared to recreational and discipline oriented websites.
Naushad Ali (2000) conducted a study at Aligarh Muslim University, Aligarh. The study showed that more than 50% of the study population was satisfied regarding the timings of the Internet service, but were not satisfied with staff‟s cooperation, and reservation facility. Majority of the respondents were not happy with the number of nodes available.
Kanaujia and Satyanarayana (2003) conducted a study of the Science & Technology community of Lucknow city to assess the level of awareness and demand of web based learning environment among Science & Technology information seekers. The major findings of the study revealed that 49.2% users browsed the Web for more than 2 to 4 hours and 14% for more than 5 hours a day. The study further showed that 36.6% users consulted e-journals regularly on the Internet, 40.4% used Internet for consulting technical reports, 24.8% to find online databases and 10.4% for telnet service.
Chi-Cheng Chang (2001) reported that 57% of the internet users tend to browse internet for more hours. Anonymous (2002) reported on the results of a survey of UMass Amberst freshmen and sophomores about their exposure to course- based instructional technologies, including e-mail, course websites, the internet, video, computer- generated displays, and computerized quiz and response systems. Students were also asked about their interest in online courses. The survey found e-mail is commonly used for communication between professors and students, course websites and required internet research are also fairly common, students tend to be exposed to course-based interactive technologies less frequently and student interest in taking online courses is mixed; few have actually taken such a course.
Anonymous (2002) found that e-mail is by enlarge the most common internet activity, with 90 per cent of all internet users claiming to be e-mailers. The most widespread use of the internet today is as an information search utility for products travel, hobbies, and general information.
Anonymous (2002**) reported that three further of the internet user students agree completely that they are successful at finding the information they need for courses and assignments. The first choice web resources for most of their assignments are search engines gooogle and Alta vista (42 per cent), Web portals like Yahoo, Msn (20 per cent), course specific websites (12 per cent) and campus library website (11 per cent).
Anonymous (2002) reported that information technology has been one of the most aspired fields in today‟s world integrating IT with agriculture will help any country to regulate its overall economy and trade. The different IT technologies like expert system in decision support system. Remote sensing, Gyandoot etc. have brought revolution in Indian agriculture, even corporate like ITC MSSL and HLL are now looking forward to extract huge benefits out of this collaboration of IT with agriculture.
Anonymous (2002) reported that seven in ten students used the campus library website for at least some of their assignment and one-in five used it for most assignments college student find out about the library‟s website from multiple sources, including from their professors and teaching assistants (49 percent), by looking it up themselves (45 percent) from classes about using the library (34 percent) and from libraries (27 percent). Among the students who did not use the campus library‟s website some (20 percent) did not know the library had a site, and some (29 percent) said it didn‟t have what they need, but less than half (43 percent) left other sites have better information, During their most recent electronic visit, most used full taxes of journal articles (67 percent) databases ad journal indexes (51 percent) and electrum books (21 percent) Few college students used any “Ask-a-librarian” services. Nearly 9 out of 10 students (89 percent) also use the campus library‟s print resources including books journals articles and encyclopedias. In addition to using the library‟s print resources they made photocopies from print resources and even print copies of electronic resources.
Bonk (2002) opined that most of the respondents (60.00 per cent) were using web-based learning as an alternative to instructor led-course.
Catherine and Banji (2002) reported that academician respondents offered several reasons for using or wanting to use the computer or Internet. The first reason was the email followed by for academic research, teaching materials, current Affairs, networking with peers, publishing work in progress, entertainment (sport) and e- commerce. Many respondents, especially those who had studied abroad offered that exposure to the convenience of the Internet for academic discourse or simply social interactions encouraged them to seek access though sometimes costly and also though communal means. The need to keep in touch with colleagues and friends overseas on return also encourages the use of ICTs. Some have initiated collaborative research through connections overseas and this has enhanced their use of the Internet and the new ICTs in general. In Nigeria, 12.90 per cent of academician computer users had their first experience with computers abroad, 8.8 per cent in their homes and 19.10 per cent in their institutions. They observed that 66.90 per cent of the respondents used computers for e-mail/Internet. In Kenya, 90.70 per cent of the academician respondents used the Internet for the last 1-5 years spending on average 1-2 hours per day. He furthers disclosed that academician respondents using Internet working in university were in the 31-40 age group followed by the 41-50 age group.
Kim Deok (2002) explored that 53.90% of internet users used it connected in cybercafes, followed by 27.85% at home and 18.25% in the offices.
Kapoor (2002) stated that e-learning provides-a) a education to everybody, b) quality education, c) online books/ literature facility, d) online consultation session, e) online examination and f) admission for all and at any place and g) practice based learning.
Krishnatray and Kuilshrestha (2002) concluded that the respondents main reasons for accessing the internet were to search for educational information (both related to the syllabus and not related to syllabus), look for product information and for business information. The respondents accessed the internet in a large way to keep a track of advances in their fields of interest. Among the more personal reasons for accessing are the e-mail, downloading software and for news. E-mail ws widely preferred medium for sending messages with nearly 54 per cent of the respondents listing it as their first choice. Around 40 per cent of the respondents send and receive between 6-10 emails a week. Nearly 58 per cent of the respondents use the internet for 1 hour in a day. 40 per cent use the Net for anywhere between 1-3 hours in a day. Krishnatray and Kulshrestha (2002) concluded that among Internet User College going boys and girls 70.00 per cent of them had experience of three years. 90.00 per cent of the respondents accessed the net at cyber cafes.
Maniar (2002) reported that majority of the internet users had preferred afternoon hours to access internet, spent about 1-2hours and also said that they were using internet technology for the last two years and majority of them had changed their information acquisition habits.
Myriam (2002) reported that among the Internet user academicians, 39.00 per cent of the Brazilian respondents surfaced the Internet for the first time before 1995, approximately one-fifth of the respondents began in 1995 and almost the same number in 1996. Only one reported having started in 2000. A similar result was obtained when they were asked since when they have started accessing the Internet: 37.00 per cent stated before 1995, 18.00 per cent in 1995, 16.00 per cent in 1996, 12.00 per cent in 1997 and 13.00 per cent in 1998. In the qualitative section, 11 out of the 25 interviewees have had accessed Internet since 1995 or earlier, a large number which matches approximately that of the questionnaire. Four started in 1996, only two in 1997, four in 1998 and the rest did not specify.
Sharma (2002) reported that most (37.14%) of the respondents were observed in the medium level of internet utilization followed by low (35.00%), and high (27.86%) level of internet utilization from overall college/ universities. Majority (37.14%) of the respondents from overall college/ university and individual college/ university were observed under low level of internet utilization pattern index followed by, medium (33.53%) and high level (29.29%).
World Bank (2002) reported that ICT holds out the opportunity to revolutionize pedagogical methods, expand access to quality education, and improve the management of education systems.
Iroha (2003) concluded that slightly more than two fifth (22.50 per cent} of the teachers attended a workshop/seminar on ICT.
Nicholas et al. (2003) conducted a study in the UK to examine the use of the web for health information and advice. More than 1300 people were surveyed. The study showed that 66% of the respondents accessed the Internet from home, 28% from work place and the remainder (6%) used a combination of both work place and home. Teresa et al. (2003) indicated that students were responded most comfortable seeking information from a search engine, with 91.45 per cent selecting “very comfortable” or comfortable. The search engine receiving the most frequent mention was www.google.com.
Anonymous (2004*) revealed that two additional areas of professional usages of the Internet were observed by teachers viz., sending or receiving e-mail to or from the teachers of other schools and publishing literature on the World Wide Web. Far fewer teachers engaged used Internet as an information-gathering tool to obtain resources for lesson preparation, only 16.00 per cent of teachers communicated by e- mail with teachers from other schools as often as five times during the school year. However, classroom access to the Internet may make a difference in whether they use e-mail for professional purposes. Teachers with Internet access at home and in their classroom were more than three times as likely to e-mail teachers at other schools as teachers who had only home Internet access (33.00 per cent vs. 9.00 per cent).
Anonymous (2004***) opined that majority (70.00 per cent) of the respondents had 1-3 years of experiences of using Internet and almost 90.00 per cent were familiar to excellent level of competences.
Anonymous (2004**) reported that 46.00 per cent of teachers reported weekly or more frequent use of Internet. Of course, it was observed that teachers who wanted to use the Internet accessed it either at home or classroom. Despite these findings, it is also true that even among teachers with home and classroom Internet access, more teachers reported only "occasional" use of the Internet for lesson preparation than used it on at least a weekly basis. E-mail was widely preferred medium for sending messages with nearly 54.00 per cent of the respondents listing it as their first choice. Around 40.00 per cent of them sent and received 6 to 10 e-mails in a week; nearly 58.00 per cent of the respondents used the Internet for one hour in a day.
Hanauer et al. (2004) surveyed a diverse community college to assess the use of the Internet by the students for health-related information. The survey showed that although all the students surveyed had free Internet access through their community college, yet only 97% of the students reported having access to the Internet. The survey showed that 83% Internet users had access to the Internet at their home and 51% of the respondents accessed Internet at college or library. Eighty-one percent of the students reported to access the Internet most for college work Kalra (2004) reported that 90 per cent users were internet for e-mail purposes. And 47 per cent of them receive and send e-mail every day. About 3 out of 4 users were chatting on the net following by surfing, playing games and listening music. And further, 51.50 per cent of the users were visiting the cybercafé daily and 45.25 per cent were visiting it weekly and 6.25 per cent only were monthly visitors.
Patel (2004) concluded that little less than half (43.55 per cent) of the information expecting respondents were having high level of mass media exposure. However, 33.06 per cent of them had low and medium exposure to mass media, respectively.
Patel (2004) observed that majority of the students had everyday exposure of Internet (53.33 per cent) and they were possessed at least one or more e-mail ID (81.66 per cent). Exactly half of them (50.00 per cent) had more than three years of exposure of Internet with everyday to at least once in a month contact of chatting facility of Internet. More than one third (35.00 per cent) were using e-mail facility at list twice in a week to receive or send mails. Major sources of Internet utilized by them were library or private cyber café, www.google.com and www.yahoo.com were the main search engines utilized by users to connect themselves with useful sites.
Chauhan (2005) opined that majority (63.00 per cent) of the interest expecting respondents expected to use Internet daily, 78.00 per cent of them expected to use Internet by their own, while 22.00 per cent of them projected to use Internet with the help of others, if Internet is provided to them at community Internet centre. The major purposes of Internet use expressed by highest respondents were to exchange information, to collect information, chatting with relatives and for entertainment.
Mishra, Yadav and Bisht (2005) conducted a study to know Internet utilization pattern of the undergraduate students of G B Pant University of Agriculture and Technology, Pantnagar. The findings of the study indicated that a majority of the students (85.7%) used the Internet. Out of the Internet users 67.7% were male students and 32.3% female students. The findings of the study also showed that 61.5% of the males and 51.6% of the females used Internet for preparing assignments. A majority of the respondents i.e. 83.1% male and 61.3% female respondents indicated that they faced the problem of slow functioning of Internet connection.
Mishra et al. (2005) reported that majority (36.46%) of the students used internet once in a week, followed by once in a fortnight (16.67%), once is a month (16.67%), occasionally (16.67%), daily (13.45%). Most preferred places for internet access were, 87.69 per cent of the male students used internet in cybercafé, followed by 6.15 per cent in college and 6.15 per cent at home, on the other hand 83.87 per cent female students go to cybercafé to use internet, followed by 9.68 per cent at home and 6.45 per cent in college.
Patel (2005) reported that nearly two- third (64.00 per cent) of the respondents were having medium level of media exposure, followed by 20.00 per cent with low and 6.00 per cent with high level of mass media exposure.
Patel and Chauhan (2005) observed that majority of the postgraduate students had everyday exposure of internet (53.33%) and they were possessed at least one or more e-mails ID (81.66%). Exactly half of them (50.00%) had more than three years of exposure of Internet with everyday to at list once in a month contact of chatting facility of internet. More than one third (35%) were using e-mail facility at list twice in a week to receive or send mails.
Patel and Chauhan (2005) reported that best three uses on Internet made by research scholars were to collect information for research reference, to send e-mail and to collect information for class note. In addition to this, they also used Internet to collect information for carrier development, to collect information to attend seminar, to develop own web site, to collect information for abroad study, for entertainment, to send application for job, to send information for publication in journals, to satisfy curiosity, chatting and just to pass time. Steve and Comille (2005) concluded that college faculties were active users of the Internet. Majority (60 per cent) of the respondents used the Internet from 4 to19 hours per week, another 40 per cent reported being online for 20 or more hours, approximately three hours or more per week or three or more hours per day. College faculty has logged many years online. Over four–fifths (82 per cent) of college faculty respondents reported having used e–mail from six to fifteen years. Fewer than five per cent of the respondents over 55 years of age used e–mail for five years or less. Some 92 per cent reported accessing e–mail at home and 89 per cent access it at work. Yet, a significant number, one in five, reported using public locations like labs or Internet cafes for e–mailing. He also reported that age seemed to play a role in faculty members‟ use and experience of the Internet. Interestingly, age correlated with the sense of the Internet‟s positive impact: the older the faculty member, the more highly he or she regarded the Internet‟s impact.
Nogueira Terrones et. al. (2006) showed that training duration seemed to be the most important feature in determining the level of performance of assessors remotely trained over the Internet.
Patel (2006) reported that majority (61.67 per cent) of the opinion contributor teachers towards the use of multimedia in agricultural education had above two years of experience of Internet exposure, followed by 28.33 per cent with up to two years and only 10.00 per cent without experience of Internet exposure. She also concluded that more than half (55.00 per cent) of the opinion contributor teachers towards the use of multimedia in agricultural education had above four years of experience of computer exposure, followed by 28.33 per cent with up to 2 years and 16.64 per cent with above 2 to 4 years of experience about exposure of computer.
Kumar et al. (2007) determined the various aspects of internet utilization patterns of veterinary students from the Acharya N.G Ranga Agricultural University in Andhra Pradesh, India. Results showed that only a small number of students owned computers at home and cyber cafes were the most common place to access the internet. The frequency of use was only once a week, usually in evening, and the cost is around Rs. 51-100 per month. Results also revealed that majority of the students preferred Google and Yahoo search engines for class assignments and research work. Most of the students expressed that e-mailing and the abundance of information available as major positive aspects, and viruses and hackers as major negative aspects of internet use. Slow functioning was the major problem faced by the students during the use of internet and eye pain was the major complaint of majority of the students.
Wu-Jia Gang et al. (2007) determined internet use and internet addiction disorder (IAD) in Guangzhou city, China and to analyze the relationship between IAD and other risky health behaviours. Questionnaires were used to investigate 3800 students in 16 schools. These students were chosen by layered multistage random sampling from 6 schools. IAD was determined according to a standard established by specialists. The percentage of IAD was 12.7% in youngsters of Guangzhou city, with the highest percentage in technical secondary schools (15.6%) and the lowest in key junior high schools (9.5%). IAD in male (14.4%) was higher than in female (11.1%). In all kinds of reasons for using the internet, recreational motive was chosen by most students. The motive of 72.8% students who used the internet was to chat. 71.6% students used it for multimedia amusement. Practical motives were also considered, such as to collect information and news. In IAD students, recreational reasons were predominant. IAD could promote some risky health behaviours, such as smoking, drinking, unhealthy mentality, suicide, drug abuse, gambling, looking on erotic publication, sexual behaviour, and so on. All OR< sub>MH values were >2 at P<0.001. Results show that the percentage of youngsters with IAD in Guangzhou city is similar to other areas of the country. Recreational motive is an important cause of IAD. IAD can increase health risks among students and something must be done to supervise the behaviours of using the internet among youngsters.
Ahmed et al. (2008) observed the patterns of use of the Internet by a questionnaire survey of 102 hospital doctors and 123 medical students in Khartoum, Sudan, in January 2005. More doctors (84.3%) had used the Internet than had students (78.9%). Half of consultants (55.0%) used the Internet daily, compared with only 18.2% of junior doctors. Many consultants and junior doctors rated their abilities as poor (60.0% and 53.1%). One-third of students (33.3%) used the Internet only for personal and not for academic purposes. Barriers to greater use of the Internet by doctors included: time constraints (80.2%), poor skills (54.6%), no access to full texts of journal articles (53.4%), difficulty in verifying the quality of information (47.6%) and high costs (41.8%). Students faced similar barriers but also listed poor knowledge of the English language.
3. Effect of internet use on over all performance Goldberg (1996) supported that student who were taught using both traditional method and internet performed better than those who were only exposed to the traditional methods.
Moore and Kearsley (1996) have acknowledged that most distance education learners want some kind of interaction with their instructor and fellow learners during an educational event. This may be for purely social reasons or for getting feedback on their ideas and questions. In traditional distance classroom learning environments, e- mail, fax, telephone and mail all offer methods to connect with the instructor and other learners.
James (1997) reported that the information age and its supporting technologies such as the internet and other digital tools, has enabled work and learning to occur during time periods and in locations based upon individual needs. With millions of internet subscribers using e-mail and the world wide web (WWW), the internet is now considered a mass media. Individuals may soon consider such electronic connectivity as essential in daily living.
Richard C. Sherman (1997) reported that the world wide web (WWW) is an exciting new tool for teaching college courses in psychology. The potential benefits of the WWW stem from the wealth of information it makes available to instructors and students, the ease of access to that information, and the “hypermedia” richness of WWW documents.
Scherer (1997) mentioned that very small (8.25 per cent) of the internet users perceived their online use to have a negative impact on their lives.
Hussein and Jefferys (1998) explained that the benefits of internet included its multi-faceted and collaborative approach to education. Internet effectively overcomes the barriers of time, location, the linearity of learning process and communication with the tutors. It can provide a holistic approach to learning by enabling the students and faculty to make available their projects, writings and curriculum materials in a mutually beneficial manner, which is either achieved with difficulty or unpractical in the traditional style of teaching.
Patnaik and Saravanan (1999) reported that the rapid spread of computer network flourishing computer software industries, the liberal approach towards the internet subscribers and government‟s the liberal approach towards the internet subscribers and government‟s enhanced support for the development of IT and communication infrastructure in the factors responsible for growth of internet in India.
Anderson (2000) reported that small group of students primarily men in the hard sciences use the internet to the degree that it has a negative impact on their academic or social lives
Gagnon and Krovi (2000) investigated that internet related training does have a dramatically positive influence on the use of the internet along with the larger departments with greater resources and the presence of faculty within the department are the factors that can encourage internet usage.
James and Drik (2000) highlighted that triggered by the internet, continuing adult education may well become the greatest growth industry in the near future.
Raymond (2000) indicated that the present Hong Kong education stakeholders were quite familiar with using Internet technology. The skill competency level, technology infrastructure and social acceptance were quite mature. These have already laid a good foundation for the growth of Internet learning. Using Internet for learning creates an impression of state-of-art technology and innovative learning style. This will have some positive effect in raising the university‟s status. Singh (2000) explored that education in India is entering a new phase with many important institutions exercising the option of offering information about themselves on net which gives prospective students the advantage of acquiring the relevant information about universities and training institutions without spending too much time, energy and money.
Agnihotri (2001) emphasized that the educational sector and private schools, big coaching centres have come up as major purchaser of internet accessibility.
Andrew Trotter (2002) reported that internet access has a measurable impact on student achievement. The researchers specifically looked at the impact of the federal Education (E) rate program, a program designed to help schools acquire telecommunications services. Though the results do not indicate that internet investment has made an impact, critics of the study suggest that not only is it too early to make this kind of assessment, but that internet connections alone are not likely to improve student test-scores. Nevertheless, the study serves as a “first crack” at trying to determine if this link between internet connections and student achievement can be made and it provide some interesting conclusions.
Jones (2002) reported that nearly four-fifths of college students (79 per cent) agree that internet use has had a positive impact on their college academic experience. Almost half (46 per cent) of college students agree that e-mail enables them to express ideas to a professor that they would not have expressed in class. Two – thirds (68%) of college students reported subscribing to one or more academic – oriented mailing lists that relate to their studies. Nearly three – quarters (73 per cent) of college students say they use the internet more than the library, while only 9 per cent said they use the library more than the internet for information searching.
Jones (2002) explained that 42 per cent of the college students used internet primarily to communicate socially. And 72 per cent of the students say most of their online communications is with friends and considers the internet to be an eary and convenient choice for communication with friends.
Aryal (2003) reported that ICT has made tremendous impact in all aspects of socio-economic life of the people because of its multipurpose advantageous services and provisions.
Chauhan (2004) reported that degree of Internet exposure of the postgraduate students was not affected by their academic performance.
Hermann et al. (2005) evaluated the Oklahoma Cooperative Extension Service Nutrition Web Site in terms of Web site characteristics, information sections, information formats, and uses of the information immediately after and 6 months after an in-service training on the Web site. Immediately after training, educators appeared to be most interested in quickly using Web site information in educational programmes. Six months after training, educators appeared to begin to use the Web site as a source of current information that could be used to address immediate consumer questions and be used for news releases.
Ahn-Yun and Kim-KyungWon (2007) investigated utilization status of internet, health/nutrition websites among children, and to assess the needs for developing nutrition websites and education programs for children. The survey questionnaire was administered to 5-6th grade students (n=434) at two elementary schools. About 32% used the internet every day while 19.5% used it whenever they needed, showing significant differences in internet usage by gender (p<0.01). Although the subjects used the internet frequently, those who used health/nutrition websites were 23.3%. The purpose of using these sites were mainly 'to obtain health/nutrition information' (55%), 'to get information regarding weight control' (17%). Fifty-six percent of the users were satisfied with the nutrition websites, but only 30% said that they were helpful. The preferred topics in developing nutrition websites were assessment of obesity, exercise methods, weight control methods, nutrition information (e.g., diet for stature growth), dietary assessment and food hygiene. Girls showed more interest in these topics than boys (p<0.05). For school nutrition education, girls showed more interest than boys in topics for cooking snacks (p<0.001) and selecting snacks (p<0.05). In nutrition websites, subjects wanted to have information and game/quiz, as well as getting information using Flash animation. The favorite colors for screen and text were slightly different by gender (p<0.01). In school nutrition education, 89.5% of subjects liked to have activities (e.g., cooking, exercise, game). They also liked materials using computers, video and internet than printed materials. If nutrition education was done at schools, subjects wanted to receive 5.7 times of education per semester on average (mean length: 42.6 min./session). This study suggests that nutrition websites and education programs for children should include the topics such as assessment of obesity or diet, weight control and special information (e.g., diet for growth) as well as general information. In designing nutrition websites and programs, methods including game, quiz, Flash animation and activities (cooking, exercise) could be appropriately used to induce the interest and involvement of children.
Blasio (2008) found that by reducing the cost of performing isolated economic activities in remote areas, information technology might serve as a substitute for urban agglomeration. The results do not support the argument that the Internet reduces the role of distance. Internet usage is much more frequent among urban consumers than among their non-urban counterparts.
4. Factor associated internet utilization
Bennett (1998) examined that web-based chat rooms, stock portfolio management tools, up-to-the minute sports statistics and virtual shopping are the communication facilities associated with the internet usage.
Philip (1998) reported that a key aspect of technology policy in South Africa was universal access. This sounds like a technological problem, but closer examination shows there are significant cultural problems. One of the problems in a multi-ethnic country is language. South Africa has 11 official languages in addition to several others spoken by sizable minorities. He raised two major questions; does universal access mean all languages must be accommodated or does globalization imply English must be forced on everyone? Gognon and Krovi (2000) highlighted that e-business is encouraging business processes, enterprise decision-making, application and organizational structures.
Agnihorti (2001) examines that ISP traffics have fallen sharply with better economies of scale and lower cost for national and international leased lines and affecting the usage of internet.
Anonymous (2001) stated that various factors like age, race occupation, monthly income, accessibility of localite, cosmopolite and mass media sources for providing information about different sites, ownership of electronic devices for using internet, access of internet at home, online shopping feature of interent, consumer interest in various forms of internet, difference in exposure of internet for men and women and difference of various type of websites in reach by location all are the factors associated with internet use.
Jessic et al. (2001) reported several possible explanations for graduate students‟ greater acceptance of forming relationship on the Internet. A possible explanation of their findings was that graduate students may already be some what accustomed to using the Internet for other purposes such as a making professional contacts and doing research.
Gupta (2002) stated that the approach of discovering the root of problem like problem of bug while working on net by determining where, why, when and how defects are introduced and devise strategies that would prevent the introduction of each defect can affect the usage of internet
Jadhao (2002) observed significant relationship between mass media exposure and transformation.
Marc (2002) concluded that engineering graduates require an ever-increasing range of skills to maintain relevance with the global environment of the new millennium. Communication skills are vital component of this, recognized by academia and industry alike. English language skills are also important given its widespread status across the globe as a lingua franca. Indeed, multilingual skills are considered a salient element in the make-up of the new global engineer. English for specific purposes focuses the learner‟s attention on the particular terminology and communication skills required in the international professional field. He further indicated that there is a clear necessity for effective English communication skills for engineers in the current globalization. Statistics indicate that the prime language of Internet sites is becoming increasingly regionalized, with the local dominant language being the first choice in language options. English is still strong, but it is becoming the second choice in an increasingly multilingual international community. The Internet, as an instrument of globalization, contributes to this process of recognizing diversity. This has clear implications for engineers.
Verma (2002) reported that due to the technological advancement like modem doubling (way for a user to get fast internet connection with an analog telephone line, to use two 56 KBPs modems to double the band width), modem bonding (use of Multilink protocol plus (CM+) to combine the band width of two modems) and modem teaming (working of modems as separate connections) using the “Smart download” capability- are the factors associated for growing internet usage.
Chauhan (2004) reported that level of Internet exposure was higher among the Ph.D. scholars than M.Sc. scholars.
Chauhan (2004) revealed that slightly more than half of Internet user research students were more than 23 years of age. He observed that level of Internet exposure was increased with increased in the age of the research students.
Chauhan (2004) signified that degree of Internet exposure of postgraduate students was not affected by their degree of father’s and mother’s education
Patel (2004) revealed that more than half of the information needing respondents (55.65 per cent) were in the middle age group followed by old age and young age group.
Patel (2004) revealed that majority (51.67 per cent) of Internet user research scholar had above 23 years of age. Further she observed that age was significantly related with Internet exposure of the Internet user research scholar. Patel (2004) reported that 51.67 per cent of the postgraduate Internet user scholars had first class in graduation. She further observed that education level of the Internet user postgraduate students was positively significant with their Internet exposure.
Patel (2004) reported that that majority of the Internet user postgraduate students were with first class academic performance (51.67 per cent). Further she reported that degree of Internet exposure of the postgraduate students was non- significantly related with their academic performance.
Patel (2004) reported that majority (83.33 per cent) of the Internet user students‟ fathers‟ level of education was SSC or above that level. She further concluded that students‟ fathers‟ level of education was non- significantly related with the level of Internet exposure of the students.
Chauhan (2005) concluded that students having more age had low level of computer nervousness.
Chauhan (2005) concluded that students with lower level education of their father were found more active in computer and had less computer nervousness, but this trend was not up to the level of significance.
Patel and Chauhan (2005) reported that the college students with higher academic performance were slightly more active in using Internet than those of lower academic performance.
Patel and Chauhan (2005) concluded that that slightly more than two fifth of the Internet user postgraduate students‟ fathers‟ level of education was above secondary level. They also concluded that Internet exposure observed insignificantly higher among those students, whose fathers‟ level of education was higher.
Patel (2006) reported that majority of the multimedia opinion provider teachers had middle age (61.66 per cent). She also stated that age and opinion of the teachers regarding multimedia application in agricultural education were negatively and significantly related with each other.
Patel (2006) reported that majority (61.67 per cent) of the opinion contributor teachers towards the use of multimedia in agricultural education had earned their Ph.D. degree with distinction, out of such teachers, 48.34 percent and 10.00 percent had distinction in their M.Sc. and B.Sc. degree, respectively. She stated that there was negative non- significant relationship between opinion of the teacher regarding multimedia application in agricultural education and their academic performance.
Shah (2006) reported that there was negatively significant relationship between age of the AAU teachers and their Internet exposure, reflecting that degree of Internet exposure of the AAU teacher was observed better among young teachers than the old aged teachers.
Shah (2006) declared that there was positive relationship between the academic qualification and degree of Internet exposure of the AAU teachers.
Shah (2006) observed that academic performance of the teachers had negatively non-significant relationship with their opinion regarding multimedia application.
Atiso (2007) found that in recent years, higher education in Ghana has been characterized by an increasing number of students without a corresponding increase in facilities such as residential and classroom accommodations and the acquisition of modern books and journals for both students and lecturers. The lack of up-to-date information for higher education could be offset in part by the Internet, which could be tapped to enhance academic work. Until recently, many universities in Ghana have depended primarily on print media (books, journals, newspapers) and grey literature as the main sources of information for both students and lecturers. This paper discusses the Internet as a supplementary source of information for tertiary institutions in Ghana, with particular reference to students of the faculty of agriculture of the University of Ghana, Legon, where the technology is relatively new and expensive and not easily accessible to the majority of students. The Internet could serve as a perfect supplement for lecturers and students and should therefore be viewed as a necessity, rather than a luxury afforded to the privileged few, as is currently the case because of the cost involved in accessing the technology. Yldz-Samur et al. (2008) determined the status of computer and Internet using and the factors affecting use of internet in nutrition and dietetics students. Methods: This study was carried out in Hacettepe University School of Health Technology, Department of Nutrition and Dietetics, Turkey. Applying questionnaires under observation collected the data. Results: Out of 256 students, 232 contributed to the study (90.6%). Only 7.3% of the students were computer illiterate. Two thirds of the students (65.1%) personally owned a computer. Those students using computer spend an average of 6.71+or-0.49 hours per week in front of the screen, spends an average of 5.39+or-0.41 hours per week in the Internet and they remain online for an average of 1.41+or-0.79 hours. Time spent for the Internet usage for professional development/learning is significantly higher among senior students. Students familiar with computer usage spend relatively longer times in front of the screen and on the Internet in comparison to others (p<0.01). The students who have a computer and Internet connection, spend relatively more time using the computer, connecting to the Internet and visiting nutrition related sites in comparison to both students who have a computer but no readily available Internet connection and who do not own a computer at all (p<0.01). CONCLUSIONS: University administration should aim at increasing the use of computers and the Internet by students for learning and professional development purposes by promoting such activities and providing training opportunities for better computer use.
5. Constraints encountered in internet utilization
A pilot study done by Harris (University of Texas at Austin) and Grangennett (University of Nebraska at Omaha) made reference to several well known researchers. "Computer anxiety levels have been found to be better predictors of success in using computers that is extent of prior computer experience (Marcoulides, 1988), but computer anxiety scores are not related to amounts of computer experience (Rosen, Sears & Weil, 1987; Marcoulides). Computer experience appears to effect attitudes about computers, rather than computer anxiety (Gressard and Loyd, 1986, Igbaria & Chakrabarti, 1990).
Birkenholz and Stewart (1991) reported that lack of training in using computers was a major barrier to using the microcomputer and computer related technologies.
DeLoughry (1993) reported that encourage students to explore, "People need the opportunity to play before they gain confidence." He quoted the words of Weil that schools, colleges and businesses allow students and employees to experiment with new computers and new software before they are incorporated into daily activities. This would allow the user the time to explore, "play", and feel comfortable.
Bill Gates (1995) analysed that the pricing of network access may be set politically rather than in the marketplace. It is going to be expensive to enfranchise people in remote locations because the cost of bringing wiring to far-flung homes and even small communities is very high.
Tarjanne (1996) stated that the most of problems on internet is that the information contained on the internet is unstructured, unsorted and difficult to find to in particular.
Brown and Vician (1997) reported that computer anxiety has been associated with decreased use and worse, avoidance of information technology. Avoidance of computer use can seriously affect some students‟ academic progress, which may cause lower performance in business settings and ultimately affect career opportunities. Goh (1997) found that the high cost of computers and computer peripherals was the main deterrent for non-users of Internet.
Hamizatul (1997) Yeap (1998) and Pang (1997) identified several factors that learn Internet skills were even stronger because of “a shortage of teaching staff” as well as equipment in institutions of higher learning. They further observed that students faced several major barriers to their successful use of library resources through Internet were genuine, students perceived that access was denied because of the inability to access databases remotely due to password requirements and/or license restrictions, difficulty in searching and justifying within the library and its websites costs of copying and printing at the library shortage of knowledge able librarians, lack of the customer orientation they have come to expect as consumers.
Tseng et al. (1997) reported that feelings of anxiety toward computers and computer use, is common, affecting 30 to 40% of the population.
Bennett (1998) stated that there are sites such as E* trade which allow one to constantly reassess their investments with the ability to usage.
Dorothy et al. (1998) observed that lack of availability of some ICT resources (1eg Internet, e-mail, computer conferencing, video conferencing, fax, digital camera, digital scanner and on-line information sources) was the main problem given by teachers in accessing ICT. This should not necessarily be taken to mean that there might not be other inhibitive factors such as lack of knowledge or skills, or lack of support, but rather that access to the technology tends to over ride all other factors in determining use.
Yeap‟s (1998) comparative study of the Arts and Science students at one of the local universities, he found that the lack of exposure and shortage of equipment influenced to a great extent the involvement of students in the use of Internet. Yeap‟s found that the Science students were more likely to use Internet because of their knowledge in Internet applications compared with the Arts Students.
Patnaik and Saravanan (1999) highlighted that India‟s telephone density is hardly 1.3 per cent (Telephones per 100 population) against world average 11 and computer density is around 1.5 (per thousand population) against world average 2. It indicates that the slow diffusion of internet in India is due to the improper telecommunications and computer networks.
Roa (1999) stated that due to insufficient online usage and online spending (buying power) internet utilization may not be a viable proposition for many developing nations.
Anonymous (2000) reported that simulataneous access to the internet via a single modem or using one – connection and one account multiple users can browse the web, check e-mail or use any internet application are the facilities promiting the use of intenet.
Anonymous (2000) reported major problem like poor quality of Internet connectivity, low bandwidths and waiting for years to own a telephone connection were more very common problems.
Gagnon and Krovi (2000) compiled that the availability and sophistication of computer resources along with the lack of interent training for the faculty involved inproviding internet training to students can influence the usage of the internet.
Gagnon and Krovi (2000) found from a study of undergraduate operations research and management science courses that the availability and sophistication of computer resources influenced the use of internet/ worldwide web.
Raymond (2000) reported that only 23 per cent respondents believed that they had no technical hurdles in using Internet for learning. However, this observation does not preclude general acceptance, as 50 per cent of respondents clearly expressed a liking for Internet learning regardless of the technical hurdles they had once felt difficult. He further reported that more than half of the respondents believe that it is worthwhile going towards using Internet as a teaching media.
Shah, Beena (2000) highlighted that the enquiry- discovery model used in internet instruction succeeded in creating interest and enthusiasm among learners to gain the knowledge through self- paced learning to the extent they want, affect the usage of internet.
Agnihotri (2001) indicated that inadequate penetration of PCs and the internet in homes as well as limitations in access are main problems faced in internet utilization.
Agnihotri (2001) reported that while using internet, the logon screen is sometimes a nuisance for single user computers as every time the Windows loads, the user has to furnish the password or hit Escape key to proceed further.
Agnihotri (2001) evaluated that high dial-up charges and low PC penetration are the major problems in internet usage.
Ardeshana et al. (2001) revealed that major constraints were less use of A.V. aids, appropriate to the subject in teaching, lack of appreciation of the teachers for good teaching, poor training facilities to the teachers and course contents are not revised according to the need of the time.
Anonymous (2002**) reported that the perceived barriers for their successful use of internet sources are, difficulty in searching, navigating the websites, cost of copying and printing the materials etc.
Anonymous (2002**) highlighted that advertising within websites bother college students. Four-out-of-five students are bothered at least a little, and one- quarter are more bothered. Most (58%) believe that there is no difference in the reliability of information on websites with advertising and only one-in-five believes ad-free websites have more reliable information.
Catherine and Banji (2002) revealed that academician respondents using Internet working in university In Nigeria had faced constraints, from the ranked severity of constraints, costs ranked the highest in Kenya it was ranked third. The biggest constraint in Kenya was the availability of Internet connection and this was second in Nigeria. Reliability of electricity and computer skills in general were not considered huge constraints and the least was the language of content since respondents in both.
Gagnon and Krovi (2000) found that the most frequent factor for not using internet is lack of student access to computer laboratory resources. Lack of relevant websites, lack of proper computer equipment for students, lack of incentives to use the internet are the obstacles in internet utilization.
Panda (2001) reported that the cyber terrorism through computer virus, hackers, cyber- punks and disrupts the normal functioning of computer network.
Anonymous (2002) reported that while working on internet several risks exposed are virus attack, hacking and data threats etc.
Hasnain (2002) stated that the excessive spamming (spam mail) may disrupt the computer and may even deny access. Kumar (2002) reported that hard disks crash, communication lines stop working, browsers take ages to download information, hackers and virus threats are the constraints faced while using internet.
Noronha (2002) highlighted that some of the problems in internet utilization are poor infrastructure, lack of sufficiently motivated teachers to impart training on internet use to students and reluctance of school/ college authorities to open access of internet to students.
Raman Mohan (2002) stated that the biggest nuisance for Net surfers these days are the pop up windows that open up themselves as any person take rounds of different websites.
Singh (2002) reported that no-availability of equipments, media and other basic amentities like electricity are the major problems in the utilization of internet.
Singh (2002) reported that if anybody download a file (runabled and containing a virus) – attached to an e-mail or USENET posting (i.e. binary) and ru nit, there are chances of having viruses in that filed while using e-mailing.
Verma (2002) stated that while surfing the internet, sudden stucking of internet explorer, stopping opening the website or hanging the system (due to specification limits the number of simultaneous connections any browser can make to a given server) are the constraints commonly faced.
Singh (2002) reported that while using internet, two common problems are of Junk mail and spam. Spam is flooding the internet with many copies of the same message in an attempt to send massage to people who would not otherwise choose to recipient but spam causes inconvenience and costs the recipient money to receive it.
Pat et al. (2003) reported that the more aggressive the technology policy and the stronger the entrepreneurial orientation, the more the firm uses the Internet to conduct business activities. More important, the competitive intensity of the business environment moderated these relationships: Technology policy and entrepreneurial orientation were associated with the use of Internet-based electronic commerce under high levels of competitive intensity, but significantly less so under low levels of competitive intensity.
Anonymous (2004) observed that major constraints areas were lack of supporting facility and lack of incentives.
Anonymous (2004) reported that more and more, professional success depends upon reasonable application of computer technology. However, not all people find easy access. Certainly, two major hindrances are computer anxiety and lack of computer self-efficacy.
Mishra et al., (2005) observed that the obstacles encountered by the students in internet use were 83.03 per cent male and 61.29 per cent females said slow functioning, 35.38 per cent male and 41.94 per cent females aid lack of skills for using the new medium, 32.31 per cent male and 29.03 per cent female said costly and 32.31 per cent male nd 16.13 per cent female said poor facilities of internet in college as barriers in internet use. Some other problems were difficult in finding scientific materials related to their field (18.46%) male and 29.03% female), electricity failure (24.62% male and 19.35% female), language (15.38%) male and 6.45 % female only) and internet oriented education is not being imparted (1.54% male only).
Misovic (2007) examined two enterprise information system (IS) architectures: an older application architecture and a more recent service-oriented architecture. The application architecture is a classical web-based application that can accept a partial or complex solution of enterprise IS. The first solution has problems with data process communication integrity, which disturbs IS applications. The second solution is suitable for large enterprises but not for small and medium enterprises. Classical web-based applications are too inflexible to adapt to changes in the enterprise's market production environment. On the other hand, the service-oriented architecture can operate on enterprise web services. Computerization of such small and flexible units can be addressed by classical web services. A new web-based application plays a structural unit role for service-oriented architecture. This application consists of a sequence formed by enterprise web-service calling. Enterprise web services can easily adapt to changes in the enterprise's market production environment thus contemporary service- oriented architecture are preferred by enterprises over the older application architecture.
Goodwin (2008) found that every user can contribute to Wikipedia, the online- encyclopedia. Many people use it already and it therefore provides a broad range of knowledge. The present article is about positive prospects and risks for the forest sector. On the one hand Wikipedia is an additional channel to reach other scientists, students and the general public. On the other hand the quality of its content is controversial. For this reason forest scientists should keep an eye on subject-related articles and enhance them if necessary.
3 THEORETICAL ORIENTATION
This chapter includes the theoretical orientation for the study. The obtainable literature reviewed in relation to the problem in the preceding chapter facilitated in devising theoretical orientation and direction for choice of variables for the study and operationalization of the concepts. The chapter has been divided and presented in the following sections.
3.1 Conceptual framework of the study
3.1.1 What is the Internet?
3.1.2 The origin of the Internet
3.1.3 Organlzational structure of the internet
3.1.4 History of the internet
3.1.5 SKRAU- A profile
3.1.6 Structure of Internet/Broadband/Mobile Technologies
3.1.7 Future application of internet
3.1.8 Issues Related to Internet/Broadband/Mobile Technologies
3.1.9 Concept of personal characteristics
3.1.10 Concept of utilization pattern 3.1.11 Concept of performance
3.1.12 Concept of constraints
3.2 Operationalization of the terms use in the study
3.3 Abbreviations used in the study
3.4 Theoretical model of the study
3.5 Empirical hypotheses
3.1.1 What is the Internet?
The Internet is “at once a world-wide broadcasting capability, a mechanism for information dissemination, and a medium for collaboration and interaction between individuals and their computer without regard for geographic location” (Internet Society, 2008a). While what is known today as the Internet is only approximately twenty-five years old, decades of small and large technological advances had paved the way for its development and success.
A working definition
It is understandable that when the question „What is the Internet?‟ is asked, the answers often vary widely. For example, representative answers may include: a network of networks based on the TCP/IP protocols a community of people who use and develop those networks a collection of resources that can be reached from those networks.
The Internet is a global resource connecting millions of users; it began as an experiment over 20 years ago by the United States; specifically, its Department of Defense.
The Internet is an American invention. But its impact is global. Internet is a glimpse of the future of networked computing, a total network in which a user can glide seamlessly from network to network as need dictates.
3.1.2 The origin of the Internet The originating network was named ARPANET and designed to support military research into computer communications. From its inception, ARPANET was built on a key assumption: the network is unreliable. Translating this into more practical English, the network was designed to operate during a nuclear attack as a means of allowing data to find their ways to their destinations and to relay upon many computers in many places. A nuclear blast or routine network outage would not impair the webs of communication paths.
The core of the design was a computer that would act as a switch to route the packets of data back and forth among their sources and destinations. The model for the design was somewhat like the American Telephone & Telegraph company‟s telephone system in the United States. Each computer was, and is still today, connected to a local switch from which all other computers can be contacted. The designers engineered additional features into the packet scheme to make certain that data arrived as they were sent.
Almost as a by-product of reliability was a foreshadowing of what is now called client server architecture: in effect, a larger machine linked to smaller machines which could in turn be linked to other computers. Communication took place between the source and destination computer. The network required a computer to accept messages or data packets and keep the pipeline filled. If one of these trafficcop computers failed, the rest of the network was not affected.
3.1.3 Organlzational structure of the internet
Internet is run by a loose federation of US government agencies, trade associations, contractors, volunteers and committees. In its early stages, the Internet consisted of government-sponsored networks. With the advent of Xerox PARC‟s Ethernet, however, linking computers accelerated. Over time, privately owned and operated networks became an important part of the Internet architecture.
Internet Society
Internet Architecture Board
Internet Engineering Internet Research Task Force Task Force
Research Groups Areas and Working Groups
With the introduction of the National Science Foundation NSFNET, however, the architecture evolved to include intermediate level networks consisting of collections of commercially produced routers and trunk or access lines which connected local area network facilities to the government-sponsored backbones.
The government sponsored supercomputer centres (such as the National Aerospace Simulator at NASA/AMES, the Magnetic Fusion Energy Computing Center at Lawrence Livermore Laboratory and the half-dozen or so NSF-sponsored supercomputer centres) fostered the growth of communications networks specifically to support supercomputer access although, over time, these have tended to look more and more like general-purpose intermediate-level networks.
A number of intermediate level networks applied for and received funding from the National Science Foundation. These direct subsidies are temporary in the sense that those receiving funding should become self supporting. To achieve this goal, intermediate level networks have been developing ways to generate revenue.
But the mix of government backbones, consortium intermediate level nets and private local area networks, must evolve to respond to the global, economic and technical demands of the user communities. With the move to higher speed backbone operation, the importance of the participation in the Internet of a broader range of non- governmental organisations has increased. However, the US government funding for Internet is going to decrease. The Internet must become selfsupporting. In other words, it is in the process of changing from a government sponsored service with a user community composed of academics, researchers and a handful of commercial activities, into a different, marketplace driven environment. 3.1.4 History of the internet
However, some claim that the undersea transatlantic cables laid in 1866 were the first step to developing the Internet. The cables were designed to allow telegraph signals from continent to continent, and their success allowed for immediate communication across the ocean (Sherman, 2003, p. 8). Another significant event in history happened in 1957 when the U.S.S.R. launched Sputnik-I into Earth‟s orbit. In response, the United States created the Advanced Research Projects Agency (ARPA) under the Department of Defense. ARPA‟s “mission was to apply state of the art technology to US defense and to avoid being surprised (again!) by technological advances of the enemy” (Universiteit Leiden, 2008).
The 1960s and the beginning of the ARPANET.
In 1962, ARPA appointed J. C. R. Licklider of MIT to head its computer research program. His objective was to design the first electronic network to aid the United States military (Universiteit Leiden, 2008). In August of that same year, Licklider published a series of memos describing what he called a “Galactic Network.” He envisioned the concept of a “Galactic Network” as a globally interconnected set of computers which people could use to quickly access data and programs from any site (Internet Society, 2008a). This idea was the precursor to what has evolved into the Internet and World Wide Web. One year prior to Licklider‟s concept, Leonard Kleinrock published the first paper on packet switching theory. Packet switching is the transferring of packages of information over an electronic network (Sherman, 2003, p. 12). Since this electronic network did not exist, the next step was to find a way in which computers could communicate with one another. In 1965, Kleinrock, Lawrence G. Roberts, and Thomas Merrill connected a TX-2 computer at Stanford Research Institute with a Q-32 computer at UCLA over a low speed dial-up telephone line to create the first ever built wide area computer network. The circuit switched telephone system was inadequate and thus proved the need for Kleinrock‟s packet switching (Internet Society, 2008a).
In 1966, Roberts joined the ARPA team and one year later published his plan for the ARPANET. When his plans were published, it became clear that three teams, MIT, National Physics Laboratory, and RAND Corporation, had all been independently working on packet switching theories without knowledge of the other teams. Collectively, they incorporated their best ideas into the ARPANET (Universiteit Leiden, 2008). By 1969, ARPA realized that the military could be aided by the scientific minds at universities, so two other schools were added into the network, University of California at Santa Barbara and the University of Utah (Sherman, 2003, p. 16). Also in 1969, the first Interface Message Processors (IMP‟s) were installed in computers at both UCLA and Stanford. An IMP is a “processor-controlled switch that is used to route packets to their proper destination” (Birds-Eye, 2008). With this function, UCLA students were able to 'login' to Stanford‟s computers, access its databases and try to send data. The fledging network had come into being when the experiment was successful (Universiteit Leiden, 2008). The first commercial online service, Compuserve, appeared in 1969, and later would became the first service to offer mail, technical support, and online chatting (Compuserve.com, 2008). The 1980s and the birth of the Internet. No one really knows who invented the word “Internet,” but by the 1980s it was clearly here, and here to stay. By 1983 people no longer were using ARPANET, instead they were logging onto the Internet. In 1984, the Domain Name Servers (DNS) was introduced. This system introduced tiering into US Internet addresses and included .edu (educational), .com (commercial), .gov (government), as well as .org (international organization) and a series of country codes. The 1980's brought the first subscription based commercial Internet company, UUNET in 1987 (Universiteit Leiden, 2008). The decade was also the beginning of concern for security on the Internet. The first computer virus was released on November 1, 1988. It was called the Internet Worm and it briefly disabled about six thousand Internet hosts (Sherman, 2003, p. 27). One year later, as Sherman (2003) points out, more concern was raised when a group of international spies were caught using the Internet to spy on the US, and so the term “cyberspies” was coined. Towards the end of the 90s there were more than 1.2 million websites (Universities Leiden, 2008). Google, a new search engine, was launched in 1998. Over the years Google has grown into one of the top search engines on the Internet, accounting for more then 65 percent of the market by the end of 2007 (hitwise.com, 2008). In 1999 two other major websites were released, Myspace and Napster (Infoplease, 2008). These two websites were the first of many social networks and peer to peer file sharing databases, respectively, to come. Myspace lead the way for future social networking sites, such as Facebook, which launched in 2004. It redefined the way in which people could communicate with each other. Instead of talking on the phone or meeting in person, users log on to the website and send messages to their friends, blog about their thoughts and ideas, and provide information about themselves, such as their educational background, favorite music and television shows, and anything else they can think of. Napster was a music file-sharing website in which users could easily access and download MP3 files from other users‟ computers. However, as explained in the next section, Napster quickly saw its own demise because of legal problems. By the end of this decade, anyone with a computer could access the Internet and they were using it for all types of information and content. The Internet has revolutionized the computer and communications world like nothing before it. In 2006, there were more than 92 million websites, and that number will continue to rise by the millions every year (Infoplease, 2008). The Internet and the World Wide Web would not be what they are today without the help of the developers, businesses, and consumers who have all taken a part in the creation of this worldwide phenomena.
3.1.5 The Swami Keshwanand Rajasthan Agricultural University (SKRAU)- A Profile
The Swami Keshwanand Rajasthan Agricultural University, also known as SKRAU is one of the leading universities in Rajasthan as well as India. Swami Keshwanand Rajasthan Agriculture University is situated in the city of Bikaner, Rajasthan.
The Swami Keshwanand Rajasthan Agricultural University has been separated from the existing Sukhadia University in the year 1987, with aims to provide education in agriculture and allied branches, facilitate research work in relevant field and undertake mass educational programmes especially designed for rural people of Rajasthan.
Faculties/Departments: Agriculture Veterinary & Animal Sciences Home Science Agri-Business Management
Swami Keshwanand Rajasthan Agriculture University is an Agricultural University located in Bikaner in the Indian state of Rajasthan. The University consists of six colleges and teaching is split between two campuses, one 45 km from Jaipur in Jobner and the other in Bikaner
The constitute colleges include:
The College of Veterinary and Animal Sciences, Bikaner established in 1954
The College of Agriculture, Bikaner The College of Home Science, Bikaner
Institute of Agribusiness Management, Bikaner
Academic Staff College cum Distance Education Centre, Bikaner
S.K.N. College of Agriculture, Jobner
The university conducts education and training in Agriculture and Allied Sciences which includes Agriculture, Veterinary and Animal Sciences, Home Science and Agri-Business Management. The university carries out production oriented research programs, rural mass education and adoption and propagation of new technologies throughout the state.
In order to achieve all these predetermined objectives the university system has been classified into three functional areas such as research, teaching & extension. To fulfill all the educational needs the university has following constituent colleges under its jurisdiction
Educational Streams
The study programs at Swami Keshwanand Rajasthan Agriculture University are aimed to broaden the intellectual potential of the students, faculty and other staff so as to contribute towards the diverse economy. It provides educational opportunities to the students through its various curricula and enables them to expand knowledge base, acquire decision making skills linked to their preferred fields of expertise, and to express themselves professionally. Instructions are given to the students so that they can develop ability in their profession.
SKRAU Bikaner carries out research programmes through university faculty and enrolled students, and confer academic distinctions on persons who bring about technological interventions of economic importance. It awards medals, prizes, scholarships, fellowships, distinctions and honorary degrees.
Extension education programme promotes agricultural education in the masses. Three main functional areas of the Directorate of Extension Education, SKRAU, are training, advisory and communication. The directorate has a team of multi disciplinary scientists who work in close co-ordination with the Department of Agriculture, Animal Husbandry, Horticulture, Forestry, Co-operatives, Panchayat Samities and other agencies engaged for betterment of rural people. The Swami Keshwanand Rajasthan Agricultural University is authorized to provide instruction in Agriculture and Allied Sciences which include Horticulture, Veterinary & Animal Sciences, Home Science and Agri-Business Management. It has also been authorized in other fields of agricultural learning, which the university may deem fit. It is empowered to maintain academic institutions, dealing with agriculture, veterinary and animal sciences, home science, agri-business management, etc., to carry out instruction in these faculties, hold examinations, and confer degree, diplomas, pertaining to professional qualifications.
3.1.6 Structure of Internet/Broadband/Mobile Technologies
After considering the history of the Internet, it is important to understand the structure of the Internet, including how it works. The Internet developed out of the telephone networks. Telephone networks use circuit switching, which involves operators manually connecting telephones to each other through “patch panels” that accept patch cords from each telephone line and electrically connect them to one another through the panel, which operates like a switch. Circuit switching is not a viable option for connecting computers because it makes limited use of the telecommunication facilities and takes too long to set up a connection. Instead, packet switching is used in digital communications. Computers send out brief bursts of data that are relayed from computer to computer until they reach their destination. The computers that perform this function are sometimes called “packet switches” or “routers”. Together, these routers and communication links between them form the foundation of the Internet. (Kahn, 1999).
The Internet gets to users via Internet Service Providers (ISP's). There are three groups of ISP's: backbone providers, national providers, and local providers. Backbone providers are nationwide or multinational organization that control Internet routing and often own pieces of the backbone itself. National providers buy capacity and routing services from backbone providers. They then run points of presence (POP's), which are locations of access points to the Internet, across the country, or in some cases, the world. They are typically described as resellers who are reselling bandwidth that is purchased from the backbone provider. Local providers operate within a smaller geographic area, but operate much in the same way as the national providers. Users pay an ISP for set-up and service and are then able to access the Internet. (McPhillips, 1999).
In the late 1990s, the United States was buzzing with Internet Service providers (ISPs), many of whom provided service through dial-up connections. By the end of 2004, however, most ISPs consolidated or were driven out of business. (Burgelman, 2005). The major cable and telecom companies are now the direct connection for consumers to the Internet. Often, service is provided via broadband technologies.
(i) What Is Broadband
According to the Federal Communications Commission, broadband or high- speed Internet access allows users to access the Internet and Internet related services at significantly higher speeds than those available through “dial-up” Internet access services. Broadband speeds vary significantly depending on the particular type and level of service ordered and may range from as low as 200 kilobits per second (kbps), or 200,000 bits per second, to six megabits per second (Mbps), or 6,000,000 bits per second. Some recent offerings even include 50 to 100 Mbps. Broadband services for residential consumers typically provide faster downstream speeds (from the Internet to your computer) than upstream speeds (from your computer to the Internet) (2008).
(ii) How Does Broadband Work
Broadband works by allowing users to access information via the Internet by using one of the high speed transmission technologies available. The transmission is digital, so all content is transmitted as “bits” of data. These bits move faster in broadband transmission technologies than in traditional dial-up Internet connections. Computers can be attached to a broadband connection by existing electrical or telephone wiring, coaxial cable, or wireless devices. (FCC, 2008.)
(iii) What types of broadband options are available
Broadband can be provided over the following platforms:
• Digital Subscriber Line (DSL);
• Cable Modem;
• Fiber-Optic Cable (Fiber);
• Wireless;
• Satellite; and
• Broadband over Powerline (BPL). (a) Digital Subscriber Line (DSL)
DSL is a wireline transmission technology that uses existing copper telephone lines to transmit data to homes and businesses. Transmission speeds range from several hundred Kbps to millions of bits per second. The availability and speed of DSL service depends on the distance of homes or businesses to the closest telephone company facility.
The following are types of DSL transmission technologies:
Asymmetrical Digital Subscriber Line (ADSL) used primarily by residential customers who receive a lot of data but do not send much. It typically provides faster speed in the downstream direction than upstream. It allows faster downstream data transmission over the same line used to provide voice service, but does not disrupt phone calls.
Symmetrical Digital Subscriber Line (SDSL) –
Used typically by businesses for services such as video conferencing. Downstream and upstream traffic speeds are equal. Faster forms of SDSL, usually available to businesses, include High data rate Digital Subscriber Line (HDSL) and Very High data rate Digital Subscriber Line (VDSL). (FCC, 2008).
(b) Cable Modem
Cable operators use the same coaxial cables that deliver picture and sound to television sets to provide broadband via cable modem service. Cable modems are external devices that have two connections, one to the cable wall outlet and the other to a computer. Transmission speeds are 1.5 Mbps or more. Speed varies depending on the type of cable model, cable network, and traffic load, but is comparable to residential DSL. (FCC, 2008).
(c) Fiber-Optic Cable (Fiber)
Fiber optic technology involves transmission through transparent glass fibers that are equivalent to the size of the diameter of a human hair. Electrical signals carrying data are converted to light and sent through the fibers. Transmission speeds are far faster than DSL or cable modem, but depend on how close your computer is to the fiber and how much bandwidth is used. Fiber can also be used to provide voice and video services. Phone companies offer fiber-based broadband in limited areas. (FCC, 2008).
(d) Wireless
Wireless broadband can be mobile or fixed. Wireless fidelity (WiFi) is an example of a fixed, short range technology that is used in conjunction with DSL or cable modem service to connect devices within a home or business to the Internet. Using a radio link between a customer location and a service provider facility, WiFi connects a home or business to the Internet. WiFi can often be found in “hotspots” such as airports, parks and bookstores. Speeds are comparable to DSL and cable modem. (FCC, 2008).
(e) Satellite
In addition to providing television service, satellites also provide links for broadband service. It is another form of wireless broadband and is used primarily to service remote or sparsely populated areas. Issues with satellite service include the line of sight to the satellite and severe weather, which can disrupt transmission. Speeds are slower than DSL and cable modem, but are still faster than dial-up download speeds. (FCC, 2008).
(f) Broadband over Powerline (BPL)
Broadband over powerlines uses the existing power distribution network to provide broadband to customers via electrical connections and outlets. Speeds are comparable to DSL and cable modem. BPL is still an emerging technology and is available only in limited areas. (FCC, 2008).
3.1.7 Future application of internet
As the world moves forward in an era where the Internet, broadband and wireless technologies are essentially ubiquitous, a number of opportunities for future applications in these fields are created. Among these applications are technological innovations. Legal and ethical concerns are paramount in the growth of these industries. Finally, business applications and opportunities are essentially limitless. (A) Technological Applications.
As technology evolves, it presents a number of unique opportunities to develop future applications that many companies are taking advantage of. These applications include: broadband over powerlines (BPL), WiMax, Internet Protocol advancements, and the development of new web browsers.
(i) Broadband Over Powerlines (BPL).
Broadband over powerlines is sometimes referred to as “high speed Internet through your electrical outlets” (Ransford, 2008). It is a technology developed with the intention of sending data over the same lines that transmit electricity to individual households. The potential reach of BPL was one of the factors that led to its development because as Burgelman noted, “Powerlines were already in place and reached more homes than either cable systems or even telephone lines” (2005, p. 5).
(ii) WiMAX.
Another technological innovation in wireless Internet access is WiMAX. It works by transmitting a wireless signal from a base station to different devices. Unlike Wifi, which transmits broadband access signals in the range of 300 feet, WiMAX transmits signals 30 miles (Burgelman, 2005). The potential for WiMAX is virtually unlimited as base stations could conceivably offer cable or satellite signals, as well as landline and telephone signals in addition to wireless Internet access. The leading proponent of WiMAX in the United States is Sprint (Sanders, 2008). They plan to launch the XOHM WiMAX network in September 2008.
(iii) IPv4 vs. IPv6.
Another future application related to the Internet is the deployment of Internet Protocol version 6 (IPv6), which is the next generation IP standard. Internet protocol specifies how communications take place between devices through an addressing system. The current system, IPv4, is anticipated to run out of address space in 2010 or 2011. In early 2008, only 16% of the space remains unallocated (OECD, 2007). While IPv4 has a theoretical maximum of about 4 million addresses, IPv6's will be in the trillions (Internet Society, 2008b). (iv) Web Browsers.
Other technological advancements in Internet technology include the development of new web browsers. In early September, Google released a free browser named Chrome, in part to offer competition to Microsoft's Internet Explorer and Mozilla's Firefox browser (Lohr, 2008).
(v) Legal and Ethical Issues in Internet/Broadband/Wireless Technology.
The digital media era has brought with it a number of legal and ethical concerns including copyright infringement, security, and privacy. A number of these same issues can be found in Internet, Broadband, and Wireless technology. Security and privacy will more than likely always be a concern for these technologies. Hopes for growth in these industries and greater access to these technologies have also led to government intervention in the form of legislation and inquiries into activities by telecommunications companies.
(a) Security & Privacy.
Recent advancements in Internet development have brought about security and privacy concerns. At the center of privacy concerns are activities by both Internet service providers and e-businesses. Recently, ISP's have been criticized for engaging in deep packet inspection. Deep packet inspection is a filtering technique that involves the inspection of packets of information as they are transmitted across the Internet. In August of 2008, Yahoo! announced, partly in response to Congress' concerns about consumer privacy, that it would allow users to shut off targeted advertising on its web sites (Whoriskey, 2008).
(b) Legislation.
A number of pieces of legislation have been introduced to address some of the concerns of the Internet and Broadband. The first was in the Senate and is the Broadband Data Improvement Act in May 2007. Among its many provisions, it calls on the Federal Communications Commission to reevaluate the current definition of broadband to develop a new “second generation” metric (Horrigan, 2007). The most recent piece of legislation is currently in draft status and has not been introduced. The author is Representative Ed Markey of Massachusetts. Markey also authored the 2007 Broadband Census Act. The new act, the Wireless Consumer Protection and Community Broadband Empowerment Act of 2008, is hoping “To require the Federal Communications Commission to promulgate new consumer protection regulations for wireless service subscribers, to restrict state and local regulation of public providers of advanced communications capability and service, to increase spectrum efficiency by Federal agencies, and for other purposes” (Public Knowledge, 2008).
(B) Business Applications and Opportunities for Internet/ Broadband/ Wireless Technology.
Along with the technological advancements and legislative efforts made in the wake of the growth of the Internet, broadband, and wireless technologies, a number of business opportunities will become available for companies looking to capitalize on the popularity of these technologies. Among them are the potential uses of the wireless spectrum that will soon be available, as well as expanded Wi-Fi applications and the rise of user generated content on the Internet and on mobile phones.
(i) Wireless Spectrum.
On February 17, 2009, television stations must cease broadcasting on analog channels and switch the broadcasting digital programming. The switch was made in part to free up parts of the broadcast spectrum for public safety communications such as police and fire departments. The switch, however, will also free up space that may be auctioned to telecommunications companies who could provide consumers with advanced wireless services.
(ii) Wi-Fi Applications.
While widespread Wi-Fi has been around for many years, the future holds opportunities for new applications and additional usage of the technology. Many of the city, wide Wi-Fi ventures developed by municipalities around the country have not panned out as planned. However, some cities are scaling back these ambitious plans of having “wireless cities” and instead offering targeted Wi-Fi in specific parts of cities.
(iii) User-generated content.
The Internet is no stranger to user-generated content as the popularity of sites like YouTube and Wikipedia can attest to. In fact, one could argue that most content on the Internet is generated by its primary users and not necessarily by web companies. Users build their own websites and blogs, and they contribute their own content including photographs, videos, games, music, written work, and computer coding to the Internet for all to see.
3.1.8 Issues Related to Internet/Broadband/Mobile Technologies
The rise of the Internet has brought with it a number of important issues. These issues include convergence, net neutrality, and digital inclusion, among many others.
(i) Convergence.
Convergence essentially exists because of the Internet. It has enabled users to download a wide variety of digital content including music, video, and games. With broadband and other high speed Internet capabilities, they can do so at an extremely rapid pace. Aside from the obvious content that users have access to, the Internet has enabled convergence through mobile phones, through the services offered by telecommunications companies, and via the new Voice Over Internet Protocol phone technology.
From a mobile phone, a user can take digital photographs, download and listen to music, access the Internet, and even watch television. Certainly, the release and subsequent popularity of the iPhone, a device which is alluded to in Simon's statement, speaks to the truth of his words. Along with the Internet, a mobile phone could be considered the ultimate convergence tool.
(ii) Net Neutrality.
Network Neutrality (Net Neutrality) is the principle that keeps the Internet open and free. Content is carried over the Internet by carriers and ISP's that run the major backbones. Net Neutrality refers to the absence of restrictions or priorities placed on said content (Pcmag.com, 2008). This principle prevents providers from blocking or altering the speed of content based on its source, ownership, or destination. Many consumers assume that they can do what they want, when they want on the Internet and Net Neutrality makes that possible. This idea of non restrictive service has been a part of the “nation‟s communication networks since the 1930s,” with the implementation of the Communications Act of 1934 (Save the Internet, 2008).
(iii) The Controversy.
The Internet has had net neutrality since its inception, and this has leveled the playing field for all participants including users, as well as content and service providers (Pcmag.com, 2008). However, major carriers, such as AT&T, Comcast, and Time Warner now want to charge larger sites for the traffic they create. Ultimately, these companies want to control which sites run at a faster pace or which site will not load at all (Save the Internet, 2008). They have lobbied the FCC to eliminate network neutrality.
(iv) Internet Freedom Preservation Act of 2008
On February 12, 2008, Ed Markey and Chip Pickering introduced the Internet Freedom Preservation Act. This legislation establishes a broadband policy to protect the Internet from blocking, censorship, and discrimination from service providers, and requires the FCC to research competition, protection, and other broadband issues (Save the Internet, 2008). If Congress passes this bill, the Internet will remain open and free.
(v) Digital Inclusion.
Digital inclusion refers to the ability of providers to penetrate the broadband market and offer Internet access to as many people as possible. In international terms, the Organization for Economic Cooperation and Development (OECD) reports that broadband statistics vary greatly across the globe in terms of pricing and performance. As far as best speeds for the lowest price, the switch to super high speed fiber based networks has enabled Finland, Japan, Korea, and Sweden to land at the top of the list. Japan has 100Mbps connections, which is 10 times greater than the average OECD offering. They also have the lowest pricing with a broadband per megabit per second rate of $0.22 USD equivalent. Turkey comes in highest at $81.13 Mbps. The United States reported a $3.18 Mbps (Smith, 2007).
3.1.9 Concept of personal characteristics
For the present study the personal characteristics operationilized as the all behaviour characteristics of the internet utilizing male and female agriculture students which play an important role in utilizing the internet.
The characteristics or features are used in a particular way to unravel a tangled evolutionary history, document the rate of evolutionary change, or as evidence of biodiversity. "Characters" are the "data" of evolutionary biology and they can be employed differently in research providing both opportunities and limitations. The Character Concept in Evolutionary Biology is about characters, their use, how different sorts of characters are limited, and what are appropriate methods for character analysis. Leading evolutionary biologists from around the world are contributors to this authoritative review of the "character concept." Because characters and the conception of characters are central to all studies of evolution, and because evolution is the central organizing principle of biology, this book will appeal to a wide cross section of biologists. Key features focuses upon "characters" fundamental data for evolutionary biology, Covers the myriad ways in which characters are defined, described, and distinguished, Includes historical, morphological, molecular, behavioral, and philosophical perspectives
3.1.10 Concept of utilization pattern
The concept of proper utilization means maximum utilization, balanced utilization and progressive utilization of each and everything. Progressive utilization motivated by consumption and based on human values will ensure social security.
There are multiple dimensions to the concept of utilization. The role of evaluation in relation to the D&U process is to help NIDRR researchers understand how much and how effectively consumers (or other targeted groups) are using the research outputs that have been disseminated. Utilization of research outcomes, then, can be considered in terms of these two basic dimensions.
It refers to the extent utilization of various sources and channels of information by an individual farmer available for seeking the information. The utilization pattern includes use of information sources and channels at different times, i.e. morning, day time, evening, and as also any time during the day/night. different sites of use of information sources and channels included in the utilization pattern, i.e., at home, neighbour‟s house, friend‟s house and any other place like market, community place and tea stall etc. Utilization measurement is made complex by the nature of "use." Following utilization continuum, identifies some examples of outcomes that may represent utilization.
Utilization continuum
Received Received Received Received Received information on information information information information internalization internalized and internalized and internalized and internalized and rejected partially applied/ fully replicated adapted/ tailored rejected for application
3.1.11 Concept of performance
Performance is a net result of the combined efforts of all individuals and group in the organization. Khanna (2004) described the benefits of the telecommunication, cellular phones, computers the internet electronic commerce and artificial intelligence have provided to the progress and development the IT sector in India organizational performance is as ambiguous a term as organizational goal. Since it is difficult to define exactly what the goals of an organization are, so it is also difficult to determine how well the organization has performed . In assessing organizational performance we are forced to ask the question. Performance from whose view point? Take, for example, a firm from society may be said to be the goal of the firm and so the firm should be evaluated in term of weather it does this or not. From the point of view of the owners of the firm. Profitability and growth rate may be the criteria for assessing performance from the point of view of the employees of the firm the firms performance may be assessed in terms of how well it treats its employees. From the point of view of the firms customers, courteous service, prompt delivery a good product and a competitive price may be the criteria in terms of which the firms performance is assessed (Khandwalla, 1977).
3.1.12 Concept of constraints
The simplest dictionary meanings of constaints are to compel, to force, to confine, to restrain to violate, to straighten, to contract, to distresss, to limit, to press, restriction of liberty, affection, restricted to avoid or perform some action. In behavioural research, there were difficulties in conceptualizing the constraints as variable because they did not tend themselves easily to abstractions. Such notions as adoption behaviour and acceptance of practices innovations suffered from vagul and contradictory formulation to such an extent that there was little concerning the adoption and acceptance of such segments of technologies, their degress, directionality and the problem of their measurement (Bhatnagar, 1974). Constraints exist primarly in terms of they are defined and conceived in organization (Bhople and Agrawal, 1987 how and Tawade et al., 1987). Constraints are projections of collective sentiments rather than simple mirror of objective conditions (Bora, 1990).
According to some auther, there exists interaction among the different constraints (Hashim, 1989). It is argued that many constraints exist simultaneously in several stages of development and patterns of progression from one stage to another depending upon the time, place and other sets of conditions (Bhatnagar, 1974).
Bhople and Agarwal (1987) defined constraints as “The state or quality of sense being restricted to a given course of action or constraints are nothing but the problems that come in the way of adoption of technology”.
Singh (2009) identified that constraints implied forcible restrictions and confinement of action.
3.2 Operationalization of the terms used in the study
3.2.1 Communication :
“Communication” is an act which answers the following questions who says what, in what channel, to whom, with what effect. So, communication is a term which means that sender and receiver are tuned together for a meassage (Lasweell, 1960).
3.2.2 Utilization pattern : It refers to extent of utilization, different sites of use and different time of use of different sources and channels in seeking information.
3.2.3 Internet utilization pattern :
It refers to the uses of internet in communication incorporating ways, frequency, during, basis impertinence, purposes and benefits derived from the internet usage in combination.
3.2.4 Constraints perceived in intent utilization
The constraints perceived in internet utilization pattern refer to the problems faced / perceived by the respondents in the course of internet utilization pattern.
3.2.5 Age: number of chronological years completed by the respondents on the date of interview.
3.2.6 Education: It is formal education level of respondent.
3.2.7 Academic performance: It is performance of the respondents in terms of the intellectual category or class in which they passed their last academic degree.
3.2.8 Knowledge of different languages: It is number of languages known by the research scholars.
3.2.9 Father’s education: It is level of formal education of respondent‟s father.
3.2.10 Mother’s education: It is level of formal education of respondent‟s mother.
3.2.11 Native place: It is birth place with background of the respondents where they have passes their childhood in terms or rural or urban.
3.2.12 Type of family: It refers to type of family of respondents in terms of nuclear or joint type of family.
3.2.13 Family size: It refers to number of family members in the family of respondents.
3.2.14 Wish to migrate abroad: It is aspiration of the respondents to go abroad for study or for settling or as inhabitant.
3.2.15 Exposure in extracurricular activity: It is involvement, participation, or association of the respondents in other than academic activities of college.
3.2.16 Library exposure: It is frequency of use and time spent by respondents in library. 3.2.17 Computer training: It refers to number of training received by the respondents about computer and its features.
3.2.18 Wish to get higher academic degree: It is aspiration of the respondents to earn higher academic degree.
3.2.19 Orientation: It is degree to which respondents are oriented to place themselves in competitive situation in relation to other for projecting their excellence in any professions.
3.3 Abbreviations used in the study
ARIS = Agricultural Research Information System
ARPA = Advance research project Ajency
BPL = Broadband Over powerline
.com = Commercial d.f. = Degree of freedom
DNS = Domein name servers et al. = (et alibi) and else where
Ext. Edu. = Extension Education
FTP = File transfer protocol
.gov = Government
H0 = Null Hypothesis
H1 = Alternate Hypothesis
HTTP = Hyper Text transfer protocol i.e. = That is
IMP = Interface massage prosser
ISP’s = Internet service providers
IT = Information Technology
J. = Journal Kbps = Kilobits per second
M.P.S. = Mean per cent score
M.S. = Mean Score
Mbps = Megabits
NARS = National Agricultural Research System
NGOs = Non governmental organizations
No. = Number of Respondent
NS = Non-Significant
.org = International organization
DSL = Digital subscriber line rs = Rank order correlation
S.D. = Standard Deviation
S.No. = Serial Number
SKRAU = Swami Keshwanad Rajasthan Agricultural University
% = Per cent
Viz. = (Videlicet) namely
VSNL = Videsh Sanchar Nigam Limited
Wifi = Wireless fidelity
WWW = World wide web
3.4 Theoretical model of the study For the successful completion of the present research work a theoretical model of the study has been developed in the form of a tentative paradigm (Fig. 3.1) to show the influence of selected independent variables over the internet utilization level of the agricultural students of Swami Keshwanand Agricultural University, Bikaner the entire study is based on the model. On the basis of the findings of the study the final form of the paradigm has been presented at the and of this dissertation in the chapter “Findings and Discussion”. As shown in the paradigm there are 19 independent variables that might be associated with the internet utilization level of the agricultural students. The variables tentatively included in the model are : 1. Age 2. Marital status 3. Educational qualification 4. academic achievement 5. Education of father 6. Education of mother 7. Occupation of father 8. Native place 9. Type of family 10. Size of family 11. Family income 12. Medium of instruction 13. Training being extended by the college library 14. Computer course studied 15. Type of computer course studied 16. Expertise in navigating web 17. Place of living 18. Wish to migrate abroad 19. Wish to get higher academic degree
3.5 Derived hypotheses
A hypothesis is a tentative generalization, the validity of which remains to be tested. In its most elementary stage the hypothesis may be any hunch, guess, imaginative idea, which becomes the basis for action and investigation.
Keeping in view the specific objectives of the study, the following hypotheses have been formulated. These general hypotheses are to be tested in the study.
H1.1 There is a significant agreement between the internet utilizing male and female agricultural students with respect to their Gender, Age, Marital status, Educational qualification, Academic achievement, Education of father, Education of mother, Occupation of father, Native place, Type of family, Size of family, Family income, Medium of instruction, Exposure to extra – curricular activities, Training being extended by the college library as to how to use Internet, Studied of any course to know use of Internet, Type of course studied, Expertise in navigating the web, Place of living at the time of education, Wish to migrate abroad, Wish to get higher academic degree, Frequency of library use and Wish to serve in different areas.
H1.2 There is a significant agreement between in the internet utilizing male and female agricultural students with reference to their Experience of internet use, Preference of place of access to Internet, Expenditure incurred to use Internet, use of Internet use, Purpose of Internet use, Possession of E-mail ID, Frequency of E-mail use, Purpose of E-mail use, Frequency of chatting to make communication, Frequency of chatting, Use of different search-engines, Ratting the internet as sources of information, Satisfaction with internet facility, Preference of internet on other media for getting information, Browsing techniques required for getting information from the internet, Locating the desired information on the Internet, Activities during Internet use, Preference of timing of access to Internet and Orientation to Internet source.
H1.3 There is significant effect of internet utilization on the over all performance of the male and female agricultural students with reference to their academic performance and non academic performance.
H1.4 There is a significant association between the internet utilization of male and female agricultural students and their Age, Marital status, Educational qualification, Academic achievement, Education of father, Education of mother, Occupation of father, Native place, Type of family, Size of family, Family income, Medium of instruction, Training being extended by the college library as to how to use Internet, Studied of any course to know use of Internet, Type of course studied, Expertise in navigating the web, Place of living at the time of education, Wish to migrate abroad and, Wish to get higher academic degree.
H1.5 There is a significant agreement in perceiving the physical constraints, technical constraints, economical constraints, operational constraint and psychological constraints faced by the internet utilizing male and female agricultural students.
4 RESEARCH METHODOLOGY
In social sciences, the term research methodology is concerned with the description of methods and procedures used during research programme. It is considered as the „blue print‟ of the research architect.
This chapter deals with research design, tools and technique of a scientific investigation used for data collection in light of objectives of the study. The selection of universe and sampling technique for investigation as well as devices used for data analysis are also explained in this chapter under following sub heads.
4.1 Locale of the study
4.2 Selection of sample
4.2.1 Selection of Agricultural colleges:
4.2.2 Selection of the respondents
4.3 Variables and their empirical measures
4.3.1 Measurement of dependent variables
4.3.2 Measurement of independent variables
4.4 Tools and techniques of data collection
4.5 Statistical measures used for analysis of data
4.6 Derivation of hypothesis in null form
4.1 Locale of the study
The present study was conducted in Swami Keshwanand Rajasthan Agricultural University, Bikaner, which was purposively selected due to the following reasons:- 1. SKRAU, Bikaner is the sole agricultural university in Rajasthan which has maximum number of agricultural colleges (3) as compared to another agricultural university in Rajasthan i.e. Maharana Pratap University of Agricultural and Technology (MPUAT), Udaipur.
2. SKRAU, Bikaner is the only University which provides admission to more number of agricultural students in an academic session as compared to other agricultural universities in Rajasthan.
4.2 Selection of sample
The sampling plan for the study was as follows:
4.2.1 Selection of Agricultural colleges:
Swami Keshwanand Rajasthan Agricultural University, Bikaner has three constituent Colleges, i.e SKNCOA, Jobner, COA, Bikaner and COA, Lalsot; out of which two agricultural colleges namely SKNCOA, Jobner and COA, Bikaner were selected purposively due to the reason that all the students of these colleges have been provided internet facility at free of cost for UG students in college library and for PG and Ph.D. students in their concerned departments.
4.2.3 Selection of respondents :
From the two selected agricultural colleges separate lists of male and female students from B.Sc. (Ag.) Hons, M.Sc. (Ag.) Hons. and Ph.D. degree, registered in 2008-09 and using the internet were prepared with the help of records of student sections, from this list a separate lists of internet utilizing male and female agricultural students from different degree courses i.e. B.Sc. (Ag.) Hons., M.Sc. (Ag.) Hons and Ph.D. Degree were prepared from internet cell registers of the respective colleges and 25 per cent male and female internet utilizing students from each degree course i.e. B.Sc. (Ag.) Hons, M.Sc. (Ag.) Hons. and Ph.D. degree, were selected by using simple random sampling with proportionate allocation method. Hence a total sample of 113 agricultural students (85 male agricultural students and 28 female agricultural students) were selected from the study purpose.
In this way a total sample comprised of 113 students (85 male and 28 female students) from B.Sc (Ag.) Hons., M.Sc. (Ag.) Hons. and Ph.D. degrees were selected for study purpose. (Table 4.1)
4.3 Variables and their empirical measures
The variables under study were selected on the basis of extensive review of literature related to the subject and consultation with experts and finally the variables that are found to be most relevant to the present study are selected. The measurement procedure of the variables used in the study are presented in the following sections :
4.3.1 Measurement of dependent variables
There were three dependent variables in the study. The measurement procedure of these variables has been presented as under:
4.3.1.1 Measurement of internet utilization pattern of the agriculture students
4.3.1.2 Measurement of effect of internet utilization on over all performance of the agricultural students. 4.3.1.3 Measurement of the constraints faced in internet utilization by the agricultural students.
4.3.1.1 Measurement of internet utilization pattern of the agriculture students
The Internet utilization pattern was operationally defined as the pattern of use of internet in communication, incorporating ways, frequency, duration, places, purpose, use of internet components and benefits derived from the internet usage in combination.
To measure the level of Internet exposure of respondents different indicators of Internet utilization pattern were identified on the basis of review of literature and discussion with subject experts of the internet and department of extension education of SKNCOA, Jobner. In this way total 19 indicators viz.; (1) Experience of internet use, (2) Preference of place of access to Internet, (3) Expenditure incurred to use Internet, (4) Frequency of Internet use, (5) Purpose of Internet use, (6) Possession of E-mail ID, (7) Frequency of E-mail use, (8) Purpose of E-mail use, (9) Frequency of chatting to make communication, (10) Extent of chatting, (11) Use of different search-engines, (12) Rating the internet as sources of information, (13) Satisfaction with internet facility, (14) Preference of internet on other media for getting information, (15) Browsing techniques required for getting information from the internet, (16) Locating the desired information on the Internet, (17) Activities during Internet use, (18) Preference of timing of access to Internet and (19) Orientation to Internet source.
The scoring procedure of each of these indicators is explained as under was identified.
4.3.1.1.1 Experience of internet use
The experience of Internet use of the respondents were measured in total number of years of their association with Internet and its use. The respondents were categorized in to three groups viz., from 1 year, from 1-2 years and from more than 3 years of use and scoring was done by assigning 1, 2 and 3 score, respectively (Appendix-III).
4.3.1.1.2 Preference of place of access to internet
The preference of places of internet access by the respondents were measured by a structured schedule developed by the investigator in light of the suggestions of the experts and the responses of the respondents were collected on a three point continuum namely Mostly, Some time and Never with a score of 2, 1 and 0, respectively (Appendix-III).
4.3.1.1.3 Expenditure spent for internet use
The expenditure in rupees spent per month by the respondents for internet use was measured by a structured schedule developed by the investigator by getting experts opinion and the responses of the respondents were collected in five classes namely Nil, Rupees 50-100, Rupees 101-200, Rupees 201-300 and Rupees 301-400 per month with a score of 0, 1, 2, 3 and 4 respectively (Appendix-III).
4.3.1.1.4 Frequency of internet use
Frequency of internet use of the respondents were measured by a structured schedule developed by the investigator in light of the suggestions of the experts and the responses of the respondents were collected on three point continuum namely Upto 1 hours, 2 to 3 hours and above 3 hours with a score of 1, 2 and 3, respectively (Appendix-III).
4.3.1.1.5 Purpose of internet use
The purpose of Internet use of the respondents were measured by a structured schedule developed by the investigator in light of the suggestions of the experts and the responses of the respondents were collected on three point continuum namely Mostly, Some times and Never with a score of 2, 1 and 0, respectively (Appendix-III).
4.3.1.1.6 Possession of E-mail ID
The respondents were asked to give information regarding possession of e- mail ID and were measured by a structured schedule developed by the investigator in light of the suggestions of the experts and the responses of the respondents were collected in to four groups viz. No Mail ID, One mail ID, Two Mail ID and More than two Mail ID and the scores of „0‟, „1‟, „2‟ and „3‟ were assigned respectively (Appendix-III).
4.3.1.1.7 Frequency of E-mail use
In this part of internet utilization pattern the frequency of e-mail use of the internet utilization male and female students was measured i.e. for how much time and with how much duration the respondents are using E-mail. These were measured by a structured schedule developed by the investigator in light of the suggestions of the experts and the responses of the respondents were collected on three point continuum namely Upto 1 hour, 2 to 3 hours and above 3 hours with a score of 1, 2 and 3, respectively (Appendix-III).
4.3.1.1.8 Purpose of E-mail use
The purpose of E-mail use of the respondents were measured by a structured schedule developed by the investigator by getting experts opinion and the responses of the respondents were collected in five classes namely Pleasure purpose, Personal purpose, Academic purpose, Advertisement purpose and Others purpose and a score of 1 was given to “Yes” response and zero score to “No” responses (Appendix-III).
4.3.1.1.9 Frequency of chatting to make communication
Chatting to make communication of the respondents were measured by a structured schedule developed by the investigator by getting experts opinion and the responses of the respondents were collected in yes and No categories and a of 1 was given 1 to “Yes” response and zero score to “No” response respectively (Appendix-III).
4.3.1.1.10 Extent of Chatting
Frequency of chatting of the respondents were measured by a structured schedule developed by the investigator in light of the suggestions of the experts and the responses of the respondents were collected on three point continuum namely Upto 1 hours, 2 to 3 hours and above 3 hours with a score of 1, 2 and 3, respectively (Appendix-III).
4.3.1.1.11 Use of different search engines
Use of different search engines by the respondents were measured by a structured schedule developed by the investigator in light of the suggestions of the experts and the responses of the respondents were collected on three point continuum namely Mostly, Some times and Never with a score of 2, 1 and 0, respectively (Appendix-III).
4.3.1.1.12 Rating of internet as a source of information
The rating of internet as a source of information by the respondents were measured by a structured schedule developed by the investigator by getting experts opinion and the responses of the respondents were collected on four point continuum viz., Unsatisfactory, Satisfactory, Good and Excellent and a scores of 1, 2, 3 and 4 were given, respectively (Appendix-III).
4.3.1.1.13 Satisfaction with internet facility
Satisfaction with internet facility by the respondents were measured by a structured schedule developed by the investigator in light of the suggestions of the experts and the responses of the respondents were collected on four point continuum viz., Not satisfied, Least satisfied, Partially satisfied and Fully satisfied and a scores of 1, 2, 3 and 4 were given, respectively (Appendix-III).
4.3.1.1.14 Preference of internet on other media for getting information
Preference of internet on other media for getting information by the respondents were measured by a structured schedule developed by the investigator in light of the suggestion of the experts and the responses of the respondents were collected on four point continuum viz., Most preferred, Preferred, Less preferred, and Not preferred with a scores of 3, 2, 1 and 0 respectively (Appendix-III).
4.3.1.1.15 Browsing techniques required for getting information from the internet
Browsing techniques required for getting information from the internet by the respondents were measured by a structured schedule developed by the investigator in light of the suggestions of the experts and the responses of the respondents were collected on three point continuum namely Mostly, Some times and Never with a score of 2, 1 and 0, respectively (Appendix-III).
4.3.1.1.16 Locating the desired information on the internet
The locating the desired information on the internet of the respondents were measured by a structured schedule developed by the investigator by getting experts opinion and the responses of the respondents were classified in to four groups viz., Never, Rarely, Sometime and Frequently and a scores of 0, 1, 2 and 3 were given, respectively (Appendix-III).
4.3.1.1.17 Activities during Internet use
Activities during Internet use by the respondents were measured by a structured schedule developed by the investigator by getting experts opinion and the responses of the respondents were collected in to two categories viz., Just watching internet and Write useful information on separate pages with a score of 1 and 2 respectively (Appendix-III).
4.3.1.1.18 Preference of timing of access to internet
Preference of timing of access to internet by the respondents were measured by a structured schedule developed by the investigator in light of the suggestions of the experts and the responses of the respondents were collected in four categories namely Morning, Noon, Evening and Night (Appendix-III).
4.3.1.1.19 Orientation of internet sources
Orientation of internet sources of the respondents were measured by a structured schedule developed by the investigator by getting experts opinion and the responses of the respondents were collected in to four categories namely From my classmates, On my own by surfing around the internet, Library staff guidance and Others (Appendix-III).
4.3.1.1.20 Internet utilization level
To know internet utilization level of all the respondents, the score of all the above mentioned nineteen indicators were worked out and summed up for each respondent to find out the internet utilization pattern of each of the respondent. On the basis of mean and standard deviation the respondents were categorised in to three levels namely Low, Medium and High.
Low = (Mean – standard deviation)
Medium = (Mean – standard deviation) to (Mean + standard deviation)
High = (Above mean + standard deviation)
4.3.1.2 Measurement of effect of internet utilization on over all performance of the agricultural students
Effect of internet utilization on over all performance of the agricultural students a list of two indicators was developed namely Academic performance and Non academic performance of the respondents were measured as the extent to which the internet usage has influenced their academic and non academic activities in both the positive and negative aspects. To study the effect of internet utilization on overall performance of the respondents the following guides were developed and used on a five point likert type scale. The scoring was done as follows: Strongly agree (5), Agree (4), Neutral (3), Disagree (2) And strongly disagree (1).
4.3.1.2.1 Measurement of effect of internet utilization on academic performance of the agricultural students
The academic performance of the respondents was measured by a structured schedule developed by the investigator by getting experts opinion. The schedule consists of a list of 10 indicators related to academic performance. The academic performance score of a particular statement was worked out by totaling the scores obtained by that particular statement by all the respondents. Then, the mean percentage score of each statement was worked out and these were arranged in rank order according to their severity (Appendix-IV).
4.3.1.2.2 Measurement of effect of internet utilization on non academic performance of the agricultural students
The non academic performance of the respondents was measured by a structured schedule developed by the investigator by getting experts opinion. The schedule consist of a list of 6 indicators related to non academic performance. The non academic performance score of a particular statement was worked out by totaling the scores obtained by that particular statement by all the respondents. Then, the mean percentage score of each statement was worked out and these were arranged in rank order according to their severity ((Appendix-IV)).
4.3.1.3 Measurement of the constraints faced in internet utilization by the agricultural students
The constraints faced by the respondents in Internet use offered by them to effectively utilize the internet services are elicited through a structured interview – schedule developed by investigators by gating experts opinion and the responses of the respondents were divided in to five major categories i.e. Physical constraints, Technical constraints, Economical constraints, Operational constraints and Psychological constraints. The responses were tabulated based on frequency, percentage, MPS, rank and rank correlation order were given (Appendix-V).
4.3.2 Measurement of independent variables The measurement procedure of independent variables has been presented as under:
4.3.2.1 Gender
Gender of the respondents was referred as the sex of the respondent as Male or Female. The responses of the individuals were expressed in terms of frequency, percentage and chi-square value (Appendix-II).
4.3.2.2 Age
The age of the respondents were measured by a structured schedule developed by the investigator in light of the suggestion of the experts and the responses of the respondents were collected in three categories namely 20 years, 20 to 25 years and above 25 years and a score of 1, 2 and 3, respectively (Appendix-II).
4.3.2.3 Marital status
The marital status of the respondents were measured by a structured schedule developed by the investigator in light of the suggestion of the experts and the responses of the respondents were collected in two categories namely unmarried and married with a score of 1 and 2, respectively (Appendix-II).
4.3.2.4 Educational qualification
Educational qualification of the respondents were measured by a structured schedule developed by the investigator by getting experts opinion and the responses of the respondents were collected in to in to three group‟s viz., B.Sc. (Ag.) Hons, M.Sc. (Ag.) Hons and Ph.D. degree with a score of 1, 2 and 3, respectively (Appendix-II).
4.3.2.5 Academic achievement
The academic achievement of the respondents were measured by a structured schedule developed by the investigator by getting experts opinion and the responses of the respondents were collected in to four categories namely > 5.0 OGPA, 5.00 to 6.49 OGPA, 6.50 to 7.49 OGPA and above 7.5 OGPA with a score of 1, 2, 3 and 4, respectively (Appendix-II). 4.3.2.6 Education of father
The education of father of the respondents were measured by a structured schedule developed by the investigator in light of the suggestions of the experts and the responses of the respondents were collected in six categories namely Illiterate, Up to primary, Up to secondary, Up to senior secondary, Above senior secondary and below graduation and Graduation and above with a score of 0, 1, 2, 3, 4 and 5, respectively (Appendix-II).
4.3.2.7 Education of mother
The education of mother of the respondents were measured by a structured schedule developed by the investigator in light of the suggestions of the experts and the responses of the respondents were collected in six categories namely Illiterate, Up to primary, Up to secondary, Up to senior secondary, Above senior secondary and below graduation and Graduation and above with a score of 0, 1, 2, 3, 4 and 5, respectively (Appendix-II).
4.3.2.8 Occupation of father
The occupation of father of the respondents were measured by a structured schedule developed by the investigator by getting experts opinion and the responses of the respondents were collected in to three categories namely Service, Business and Agriculture with a score of 1 for “Yes” response and 0 for “No” response were given (Appendix-II).
4.3.2.9 Native place
The native place of the respondents were measured by a structured schedule developed by the investigator in light of the suggestions of the experts and the responses of the respondents were collected in two categories namely Rural and Urban with a score of 1 and 2, respectively (Appendix-II).
4.3.2.10 Type of family
The type of family of the respondents were measured by a structured schedule developed by the investigator by getting experts opinion and the responses of the respondents were collected in to two categories namely Nuclear family and Joint family with a score of 1 and 2, respectively (Appendix-II). 4.3.2.11 Size of family
The size of family of the respondents were measured by a structured schedule developed by the investigator in light of the suggestions of the experts and the responses of the respondents were collected in two categories namely Small family and Big family with a score of 1 and 2, respectively (Appendix-II).
4.3.2.12 Family income
The family income of the respondents were measured by a structured schedule developed by the investigator by getting experts opinion and the responses of the respondents were collected in to three categories namely Rupees upto to 10000 per month, Rupees 10000 to 25000 per month and more than 25000 Rupees per month with a score of 1, 2 and 3, respectively (Appendix-II).
4.3.2.13 Medium of instruction
The medium of instruction during school days of the respondents were measured by a structured schedule developed by the investigator in light of the suggestion of the experts and the responses of the respondents were collected into three categories namely Hindi medium of instruction, English medium of instruction and Others medium of instruction language with a score of 1, 2 and 3, respectively (Appendix-II).
4.3.2.14 Exposure to extra curricular activities
The participating in exposure to extra curricular activities of the respondents were measured by a structured schedule developed by the investigator by getting experts opinion and the responses of the respondents were collected in to eight categories namely Literary, Cultural, Games and sport, Debate/ lecturing etc. Arts, NCC, NSS and Other social activities and a score of 1 for “Yes” response and 0 for “No” response were given (Appendix-II).
4.3.2.15 Training being extended by the college library as how to use internet
The training being extended by the college library as how to use internet of the respondents were measured by a structured schedule developed by the investigator in light of the suggestions of the experts and the responses of the respondents were collected in two categories with a score of 1 for “Yes” response and 0 for “No” response were given (Appendix-II).
4.3.2.16 Study of any course to know the use of internet
The study of any course to know the use of internet of the respondents were measured by a structured schedule developed by the investigator in light of the suggestion of the experts and the responses of the respondents were collected in two categories with a score of 1 for “Yes” response and 0 for “No” response were given (Appendix-II).
4.3.2.17 Type of course studied
The type of course studied by the respondents were measured by a structured schedule developed by the investigator in light of the suggestions of the experts and the responses of the respondents were collected in five categories namely basic + tally course of computer, DCA course of computer, C++ course of computer, O level course of computer and No course of computer studied (Appendix-II).
4.3.2.18 Expertise in navigating the web
The expertise in navigating the web of the respondents were measured by a structured schedule developed by the investigator by getting experts opinion and the responses of the respondents were collected in to three categories namely Beginner, Intermediate and Advance with a score of 1, 2 and 3, respectively (Appendix-II).
4.3.2.19 Place of living at the time of education
The place of living at the time of education of the respondents were measured by a structured schedule developed by the investigator in light of the suggestions of the experts and the responses of the respondents were collected in two categories namely Non hosteller and Hosteller with a score of 1 and 2, respectively (Appendix-II).
4.3.2.20 Wish to migrate abroad
The wish to migrate abroad of the respondents were measured by a structured schedule developed by the investigator by getting experts opinion and the responses of the respondents were collected in to three categories namely No wish to go abroad, Wish to go abroad for study and Wish to go abroad for settling with a score of 1, 2 and 3, respectively (Appendix-II).
4.3.2.21 Wish to get higher academic degree
The wish to get higher academic degree of the respondents were measured by a structured schedule developed by the investigator in light of the suggestions of the experts and the responses of the respondents were collected in two categories namely Willing to have next degree and Not willing to have next degree with a score of 1 and 0, respectively (Appendix-II).
4.3.2.22 Frequency of library use
The frequency of library use of the respondents were measured by a structured schedule developed by the investigator in light of the suggestions of the experts and the responses of the respondents were collected in three point continuum namely Upto 1 hours, 2 to 3 hours and above 3 hours with a score of 1, 2 and 3, respectively (Appendix-II).
4.3.2.23 Wish to serve in different areas
The wish to serve in different areas of the respondents were measured by a structured schedule developed by the investigator by getting experts opinion and the responses of the respondents were collected in to ten categories namely Banking, Management, Government agricultural sector, Private agricultural sector, Own business, Military service, Administrative services, Railway services, Marketing and NGO with a score of 1 for “yes” response and 0 for “No‟ response were given (Appendix-II).
4.4 Tools and techniques of data collection
The data were collected with the help of an interview schedule. The interview schedule was prepared in consultation with the available literatures, experts in the field of extension and information technology and keeping in view the objectives of the study the schedule was prepared in a simple language. The interview schedule consists of four parts. The first part of the schedule consisted of questions pertaining to personal and family characteristics of the agricultural students, while the second part was used for measuring internet utilization pattern of the respondents. The third part pertains to effect of internet utilization on overall performance of the respondents and fourth part consists of constraints faced in effective use of internet services being provided to respondents. The data were collected with the help of the interview –schedule. Data collection was done by personally interviewing the respondents with the help of interview-schedule.
4.5 Statistical measures used for analysis of data
After collecting the data from 113 respondents (85 Male agricultural students and 28 female agricultural students) they were transferred to the work tables and tally sheets were prepared. They were processed, classified, analized and subjected to statistical analysis. The cross tables were prepared and the data were interpreted in the light of the objectives of the study.
Statistical measured used
To analyze the collected information‟s several statistical tools and methods were used. The following statistical methods were used for interpreting the data and testing the hypotheses.
4.5.1 Percentage and frequency: Simple comparison was made on the basis of percentage and frequency
4.5.2 Arithmetic mean : It was used to find out the mean (average) value of the dependent and independent variables
4.5.3 Mean score (MS) : MS was obtained by total scores of each statement divided by total number of respondents. Total score of a practice Mean Score = Total No. of respondents
4.5.4 Mean percent score (MPS) : MPS was obtained by multiplying total obtained score of the respondents by hundred and dividing by the maximum obtainable score under each practices. Total score obtained by the respondents MPS = x 100 Maximum obtainable score
4.5.5 Rank : Rank were awarded in the descending order according to the frequencies / MPS. 4.5.6 Standard deviation (SD) : It measures the absolute dispersion of variability of distribution. Here mean and SD were used in categorization of respondents in different categories. Standard deviation (σ) was calculated by the following formula 2 2 xi. xi S.D. = - N N Where, 2 xi = Sum of squares of the variables xi = Sum of values of the variables N = Number of respondents
4.5.7 Spearman’s rank correlation (rs)
This test was used to determine the relationship between the ranks assigned by the two categories of respondents.
2 6 Σdi rs = 1 ------n (n2-1) Where,
Di = difference of ranks of the big and small fenugreek growers, small and marginal fenugreek growers and big and marginal fenugreek growers
N = Number of items/ observations
For repeated values of an item the formula of rs was used as given under:
2 3 3 [6 (Σdi ) + 1 (t -t) + 1 (t -t)] 12 12 rs = 1------n (n2-1) Where,
T = Number of items, an item values was repeated, thus if measurement „X‟ is repeated two items then the value of „t‟ will be 2, if repeated three items then the value of „t‟ will be 3.
The significance of Spearman‟s rank correlation coefficient was tested by calculating the t-test as follows by using following formula: r n - 2 t = (1 - r2) The value of „r‟ always lies between -1 to +1. The positive value of „r‟ indicate a tendency of „x‟ and „y‟ to increase together. Where „r‟ is negative, large value of „x‟ are associated with small value of „y‟. For test of significance „r‟ tabulated is located at (n-2) degree of freedom.
4.5.8 Correlation coefficient : The correlation coefficient („r‟ value) was used to measure the reliability of the scale for measuring the information seeking behaviour . The correlation coefficient between two groups was calculated by using the following formula.
xiyi - (xi) (yi)/N r = 2 2 2 2 xi - (xi )/N yi - (yi) /N Where, r = Correlation coefficient N = Number of paired observations th xi = Value of x variable for i pair th yi = Value of y variable for i pair
The significance of correlation coefficient was tested by „t‟ value, which was measured by using following formula:
r N - 2 t = 1 - r2
d.f. = N – 2
The value of „r‟ always lies between -1 to +1. The positive value of „r‟ indicate a tendency of „x‟ and „y‟ to increase together. Where „r‟ is negative, large value of „x‟ are associated with small value of „y‟. For test of significance „r‟ tabulated is located at (n-2) degree of freedom.
4.5.9 Chi-square test
To study the association of two attributes the X2 test was used as the following formula:
m n 2 Σ Σ (Oij – Eij) x2 = j = i = 1 Eij 1
d.f. = (m-1) (n-1) Where Oij = Observed frequency of (i.j)th cell Eij = Expected frequency of (i.j)th cell 4.5.10 Contingency of coefficient To find out the high and low association between independent and dependent (Internet utilization pattern) variables, following formula was used: C – root X2\ X2 plus n
Where, C Contingency coefficient X2 Chi-square value N Sample size 4.5.11 Coefficient of variance
cv = σ / μ,
Where:
4.6.1 Derivation of hypotheses in null form
Considering the importance of the factors selected to be studied with reference to the objectives of the present study, the hypotheses for this study were framed in null form as follows:
H01 There is no significant agreement between the internet utilizing male and female agricultural students with reference to their Gender, Age, Marital status, Educational qualification, Academic achievement, Education of father, Education of mother, Occupation of father, Native place, Type of family, Size of family, Family income, Medium of instruction, Exposure to extra – curricular activities, Training being extended by the college library as to how to use Internet, Studied of any course to know use of Internet, Type of course studied, Expertise in navigating the web, Place of living at the time of education, Wish to migrate abroad, Wish to get higher academic degree, Frequency of library use and Wish to serve in different areas.
H02.1 There is no significant agreement between the internet utilizing male and female agricultural students with the reference of their Experience of internet use, Preference of place of access to Internet, Expenditure incurred to use Internet, Frequency of Internet use, Purpose of Internet use, Possession of E- mail ID, Frequency of E-mail use, Purpose of E-mail use, use of chatting to make communication, Frequency of chatting, Use of different search-engines, Rating the internet as sources of information, Satisfaction with internet facility, Preference of internet on other media for getting information, Browsing techniques required for getting information from the internet, Locating the desired information on the Internet, Activities during Internet use, Preference of timing of access to Internet and Orientation to Internet source.
H02.2 There is no significant agreement between internet utilizing male and female agricultural students with reference to their internet utilization level.
H03.1 There is no significant effect of internet utilization on the over all performance of the male and female agricultural students with reference to their academic performance.
H03.2 There is no significant effect of internet utilization on the over all performance of the male and female agricultural students with reference to their non academic performance.
H04.1 There is no significant association between the internet utilization of male and female agricultural students and their age.
H04.2 There is no significant association between the internet utilization of male and female agricultural students and their Marital status.
H04.3 There is no significant association between the internet utilization of male and female agricultural students and their educational qualification.
H04.4 There is no significant association between the internet utilization of male and female agricultural students and their academic achievement.
H04.5 There is no significant association between the internet utilization of male and female agricultural students and their education of father.
H04.6 There is no significant association between the internet utilization of male and female agricultural students and their education of mother.
H04.7 There is no significant association between the internet utilization of male and female agricultural students and their occupation of father.
H04.8 There is no significant association between the internet utilization of male and female agricultural students and their native place. H04.9 There is no significant association between the internet utilization of male and female agricultural students and their type of family.
H04.10 There is no significant association between the internet utilization of male and female agricultural students and their size of family.
H04.11 There is no significant association between the internet utilization of male and female agricultural students and their family income.
H04.12 There is no significant association between the internet utilization of male and female agricultural students and their medium of instruction.
H04.13 There is no significant association between the internet utilization of male and female agricultural students and their training being extended by the college library as to how to use Internet.
H04.14 There is no significant association between the internet utilization of male and female agricultural students and their studied of any course to know the use of Internet.
H04.15 There is no significant association between the internet utilization of male and female agricultural students and their type of course studied.
H04.16 There is no significant association between the internet utilization of male and female agricultural students and their expertise in navigating the web.
H04.17 There is no significant association between the internet utilization of male and female agricultural students and their place of living at the time of education.
H04.18 There is no significant association between the internet utilization of male and female agricultural students and their wish to migrate abroad.
H04.19 There is no significant association between the internet utilization of male and female agricultural students and wish to get higher academic degree.
H05.1 There is no significant agreement in perceiving the physical constraints faced by the internet utilizing male and female agricultural students.
H05.2 There is no significant agreement in perceiving the technical constraints faced by the internet utilizing male and female agricultural students. H05.3 There is no significant agreement in perceiving the economical constraints faced by the internet utilizing male and female agricultural students.
H05.4 There is no significant agreement in perceiving the operational constraints faced by the internet utilizing male and female agricultural students.
H05.5 There is no significant agreement in perceiving the psychological constraints faced by the internet utilizing male and female agricultural students.
Table 4.1 Locale of study and selection of sample
Registered students in 2008-09 Internet users Selected internet users
S.No. College Degree Male Female Total Male Female Total Male Female Total in which students students students students students students studying
1 S.K.N. B.Sc. 213 81 297 132 48 180 33 12 45 College of Agriculture, Jobner
M.Sc. 60 18 78 52 16 68 13 4 17
Ph.D. 27 8 35 24 6 30 6 2 8
Total 300 107 407 208 70 278 52 18 70
2 COA, B.Sc. 100 41 141 56 20 76 14 5 19 Bikaner
M.Sc. 66 11 77 56 12 68 14 3 17
Ph.D. 35 10 45 20 7 27 5 2 7 Total 201 62 263 132 39 171 33 10 43
Grand Total 501 169 670 340 109 449 85 28 113
5 RESULT AND DISCUSSION
This chapter deals with findings of the present study that have been derived subjecting data to statistical analysis and their interpretation. The results and their interpretation have been presented under following heads :
5.1 Personal and family characteristics of the Agricultural Students
5.2 Internet utilization pattern of Agricultural Students
5.3 Effect of internet utilization on overall performance of Agricultural students
5.4 Factors associated with the internet utilization of agricultural students.
5.5 Constraints faced in Internet utilization by Agricultural Students
5.1 Personal and family characteristics of the Agricultural Students
The internet utilizing male and female agricultural students personal characteristics like Gender, Age, Marital status, Educational qualification, Academic achievement, Education of father, Education of mother, Occupation of father, Native place, Type of family, Size of family, Family income, Medium of instruction, Exposure to extra – curricular activities, Training being extended by the college library as to how to use Internet, Study of any course to know the use of Internet, Type of course studied, Expertise in navigating the web, Place of living at the time of education, Wish to migrate abroad, Wish to get higher academic degree, Frequency of library use and wish to serve in different areas included. The data regarding the aspects has been presented in following heads:
5.1.1 Gender
It is evident from the table 5.1.1 that majority (75.22%) of the respondents were male, and the female comprised of only 24.78 per cent of the total respondents (Fig. 5.1.1). Table 5.1.1: Distribution of internet utilizing agricultural students according to their gender N= 113 S. No. Category Respondents F. % 1 Male 85 75.22 2 Female 28 24.78 Total 113 100.00 F= Frequency
5.1.2 Age
A perusal of table 5.1.2 indicate that majority of the internet utilizing male agricultural students (50.58 per cent) and female agricultural students (35.71 per cent) were aged between 21 – 25 years.
Table 5.1.2 Distribution of internet utilizing male and female agricultural students according to their age N= 113 S. Category Male Students Female Calculated value No. (N=85) Students (N=28)
F. % F. % X2 1 Upto 20 years 19 22.36 9 32.15 2 21 to 25 years 43 50.58 10 35.71 2.00 NS 3 Above 25 years 23 27.06 9 32.14 Total 85 100.00 28 100.00 2 X –tab value at 5 per cent level of significance = 5.991 d.f. = 2 NS = Non significant F= Frequency In case of male agricultural students 27.06 per cent were aged above 25 years and only 22.36 per cent were aged upto 20 years. While in female agricultural students 32.15 per cent were aged up to 20 years and 32.14 per cent were aged above 25 years (Fig. 5.1.2).
The calculated value of chi-square (2.00) is less than their tabulated value of chi- square (5.991) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their age.
5.1.3 Marital status
Table 5.1.3 indicated that majority of the internet utilizing male agricultural students (56.47 per cent) were unmarried while 43.53 percent of the respondents were married. In case of female agricultural students 57.14 were found married and 42.86 were unmarried (Fig. 5.1.3).
Table : 5.1.3: Distribution of internet utilizing male and female agricultural students according to their marital status N = 113 S. Category Male Students Female Students Calculated No. (N=85) (N=28) value
F. % F. % X2 1 Unmarried 48 56.47 12 42.86 1.57 NS
2 Married 37 43.53 16 57.14
Total 85 100.00 28 100.00 2 X –tab value at 5 per cent level of significance = 3.841 d.f. = 1 NS = Non significant F= Frequency
The calculated value of chi-square (1.57) is less than their tabulated value of chi- square (3.841) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their marital status.
5.1.4 Educational qualification
A perusal of table 5.1.4 revealed that majority of the internet utilizing male agricultural students (55.29 per cent) and female agricultural students (60.71 per cent) were studying in B. Sc. Degree programme. In case of male agricultural students 31.77 per cent were studying in M. Sc. Degree programme and 12.94 per cent were studying in Ph.D. Degree programme. While in case of female agricultural students 25.00 per cent were studying in M. Sc. Degree programme and 14.29 per cent were studying in Ph.D. Degree programme (Fig. 5.1.4).
Table 5.1.4a Distribution of internet utilizing male and female agricultural students according to their educational qualification
N = 113 S. Category Male Students (N=85) Female Students Calculated No. (N=28) value
F. % F. % X2 1 B.Sc. 47 55.29 17 60.71 2 M.Sc. 27 31.77 7 25.00 0.46 NS
3 Ph.D. 11 12.94 4 14.29
Total 85 100.00 28 100.00
2 X –tab value at 5 per cent level of significance = 5.991 d.f. = 2 NS = Non significant F= Frequency
The calculated value of chi-square (0.46) is less than their tabulated value of chi- square (5.991) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their educational qualification.
However while seeing the educational qualification wise distribution of all agricultural students as evident in table 5.1.4b it can be found that out of the total registered male agriculture students 68.86 per cent were utilizing the internet, whereas out of total registered female students 63.37 per cent were utilizing internet.
Table : 5.1.4b Educational qualification wise distribution of all agricultural students SKRAU, Bikaner according to their internet utilization S. Category Male students Female students No. Total No of % Total No of % registered internet registered internet utilization utilization 1 B.Sc. 313 188 60.06 122 68 55.73
2 M.Sc. 126 108 85.71 32 28 87.50
3 Ph.D. 62 44 70.96 18 13 72.22
Total 501 340 68.86 172 109 63.37
From the table it can also be concluded that among all the male agricultural
students registered in M.Sc. (Ag.) 85.71 per cent and among all the female agricultural
students 87.50 per cent were utilizing internet whereas in the total registered students in
Ph.D. 70.96 per cent male and 72.22 per cent female agricultural students were utilizing
internet, however among the students registered B.Sc. (Ag.) 60.06 per cent male and
55.73 per cent female agricultural students were utilizing internet. Hence it can be inferred that both the male and female agricultural students registered in M.Sc. (Ag.) had maximum utilization of internet whereas in the male and female students registered in B.Sc. (Ag.) the internet utilization was found low as compared to M.Sc. (Ag.) and Ph.D. students.
5.1.5 Academic achievement
A perusal of table 5.1.5 depicted that majority of the internet utilizing male agricultural students (61.18 per cent) and female agricultural students (42.85 per cent) had obtained OGPA in last semester in category 5.01 – 6.49 OGPA. In case of male agricultural students 20.00 per cent had obtained OGPA in last semester in category 7.5 and above OGPA and 10.58 per cent had obtained OGPA in last semester in category 6.50 – 7.49 OGPA and only 8.24 per cent had obtained in category less than 5.00 OGPA; While in case of female agricultural students 28.57 per cent had obtained OGPA in last semester in category 7.50 and above OGPA, 17.86 per cent had obtained OGPA in last semester in category 6.50 – 7.49 OGPA and only 10.71 per cent had obtained in category less than 5.00 OGPA in last semester (Fig. 5.1.5).
Table : 5.1.5: Distribution of internet utilizing male and female agricultural students according to their academic achievement (OGPA obtained during last semester) N = 113 S. Category Male Female Calculated No. Students (N=85) Students value (N=28) F. % F. % X2 1 Less than 5.0 OGPA 24 28.24 11 39.29
2 5.01 to 6.49 OGPA 52 61.18 12 42.85 2.98 NS
3 6.50 to 7.49 OGPA 9 10.58 5 17.86
4 7.50 and above OGPA 0 0.00 0 0.00
Total 85 100.00 28 100.00 2 X –tab value at 5 per cent level of significance = 7.815 d.f. = 3 NS = Non significant F= Frequency The calculated value of chi-square (2.99) is less than their tabulated value of chi- square (7.815) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their academic achievement.
5.1.6 Education of father
The table 5.1.6 indicated that fathers of majority of the internet utilizing male agricultural students (47.06 per cent) and female agricultural students (46.43 per cent) had above senior secondary and below graduation level of education. In case of fathers of male agricultural students 22.35 per cent had graduation and above level of education, 10.58 per cent had upto secondary level, 8.24 per cent had illiterate level, 8.24 per cent had upto senior secondary and 3.53 per cent had upto primary level of education; whereas in case of father of female agricultural students 21.43 per cent had graduation and above level of education, 14.29 per cent had upto senior secondary level, 10.71 per cent had upto secondary, 7.14 per cent had illiterate and none of the father of the respondents had upto primary level of education (Fig. 5.1.6).
Table : 5.1.6: Distribution of internet utilizing male and female agricultural students according to their fathers education N = 113 S. Category Male Female Calculated No. Students Students value (N=85) (N=28) F. % F. % X2 1 Illiterate 7 8.24 2 7.14
2 Up to primary 3 3.53 0 0.00
3 Up to secondary 9 10.58 3 10.71
4 Up to Senior secondary 7 8.24 4 14.29 1.82 NS 5 Above senior secondary and 40 47.06 13 46.43 below graduation
6 Graduation and above 19 22.35 6 21.43
Total 85 100.00 28 100.00 2 X –tab value at 5 per cent level of significance = 11.070 d.f. = 5 NS = Non significant F= Frequency The calculated value of chi-square (1.82) is less than their tabulated value of chi- square (11.070) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their education of father.
5.1.7 Education of mother
A perusal of table 5.1.7 depicted that mothers of majority of the internet utilizing male agricultural students (40.00 per cent) and female agricultural students (25.00 per cent) had above senior secondary and below graduation level of education. Table : 5.1.7: Distribution of internet utilizing male and female agricultural students according to their mothers education N = 113 S. Category Male Students Female Calculated No. (N=85) Students value (N=28) F. % F. % X2 1 Illiterate 11 12.94 6 21.43
2 Up to primary 11 12.94 3 10.71 3.04NS
3 Up to secondary 8 9.41 4 14.29 4 Up to Senior 7 8.24 3 10.71 secondary
5 Above senior secondary and below 34 40.00 7 25.00 graduation
6 Graduation and above 14 16.47 5 17.86
Total 85 100.00 28 100.00
2 X –tab value at 5 per cent level of significance = 11.070 d.f. = 5 NS = Non significant F= Frequency
In case of mother of male agricultural students 16.47 per cent had graduation and above level of education, 12.94 per cent had illiterate, 12.94 per cent had upto primary level, 9.41 per cent had upto secondary level and 8.24 per cent had upto senior secondary level of education; while in case of mother of female agricultural students 21.43 per cent had illiterate, 17.86 per cent had graduation and above level of education, 14.29 per cent had upto secondary level and 10.71per cent had upto senior secondary level and 10.71 per cent had upto primary level of education (Fig. 5.1.7).
The calculated value of chi-square (3.04) is less than their tabulated value of chi- square (11.070) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their education of mother.
5.1.8 Occupation of father
Table : 5.1.8: Distribution of internet utilizing male and female agricultural students according to their fathers occupation N = 113 S. Category Male Students Female Total Calculated No. (N=85) Students value (N=28) F. % F. % F % X2 1 Service 18 21.18 5 17.86 23 20.35
2 Business 12 14.12 6 21.43 18 15.93 0.87 NS 3 Agriculture 55 64.70 17 60.71 72 63.72 Total 85 100.00 28 100.00 113 100.00 2 X –tab value at 5 per cent level of significance = 5.991 d.f. = 2 NS = Non significant F= Frequency
The data incorporated in table 5.1.8 depicted that fathers of majority of the internet utilizing male agricultural students (64.70 per cent) and female agricultural students (60. 71 per cent) were having agricultural occupation. In case of father of male agricultural students 21.18 per cent were having occupation of service and 14.12 per cent were having occupation of business; whereas In case of father of female agricultural students 21.43 per cent were having occupation of business and 17.66 per cent were having occupation of service (Fig. 5.1.8).
The calculated value of chi-square (0.87) is less than their tabulated value of chi- square (5.991) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their father‟s occupation.
5.1.9 Native place
Table 5.1.9 depicted that majority of the internet utilizing male agricultural students (69.41 per cent) and female agricultural students (60.71 per cent) were from rural back ground. Table 5.1.9: Distribution of internet utilizing male and female agricultural students according to their native place N = 113
S. Category Male Students Female Students Calculated No. (N=85) (N=28) value
F. % F. % X2 1 Rural 59 69.41 17 60.71
2 Urban 26 30.59 11 39.29 0.72 NS
Total 85 100.00 28 100.00
2 X –tab value at 5 per cent level of significance = 3.841 d.f. = 1 NS = Non significant F= Frequency In case of male agricultural students 30.59 percent were from urban background; while In case of female agricultural students 39.29 percent were from urban background (Fig. 5.1.9). The calculated value of chi-square (0.72) is less than their tabulated value of chi-square (3.841) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their native place.
5.1.10 Type of family
A perusal of table 5.1.10 depicted that majority of the internet utilizing male agricultural students (64.71 per cent) and female agricultural students (71.43 per cent) were belonged to joint family. Following 35.29 per cent male agricultural students and 28.57 per cent female agricultural students were belonged to nuclear family (Fig. 5.1.10).
Table 5.1.10: Distribution of internet utilizing male and female agricultural students according to their type of family N = 113
S. Category Male Students Female Calculated No. (N=85) Students value (N=28)
F. % F. % X2 1 Nuclear family 30 35.29 8 28.57 0.43 NS
2 Joint family 55 64.71 20 71.43
Total 85 100.00 28 100.00
2 X –tab value at 5 per cent level of significance = 3.841 d.f. = 1 NS = Non significant F= Frequency
The calculated value of chi-square (0.43) is less than their tabulated value of chi- square (3.841) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their type of family.
5.1.11 Size of family
The table 5.1.11 indicated that majority of the internet utilizing male agricultural students (58.82 per cent) and female agricultural students (53.57 per cent) were belonged to big family. Following 41.18 per cent male agricultural students and 46.43 per cent female agricultural students were belonged to small family (Fig. 5.1.11). Table : 5.1.11: Distribution of internet utilizing male and female agricultural students according to their size of family N = 113 S. Category Male Female Students Calculated No. Students (N=28) value (N=85) F. % F. % X2 1 Small family (up to 35 41.18 13 46.43 five members)
2 Big family (above five 50 58.82 15 53.57 0.69 NS members)
Total 85 100.00 28 100.00
2 X –tab value at 5 per cent level of significance = 3.841 d.f. = 1 NS = Non significant F= Frequency
The calculated value of chi-square (0.69) is less than their tabulated value of chi- square (3.841) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their size of family.
5.1.12 Family income
The table 5.1.12 shows that majority of the internet utilizing male agricultural students‟ (44.71 per cent) had family income, ranged between Rupees 10001 to 25000 per month; whereas majority of the female agricultural students‟ (35.72 per cent) had family income, upto Rupees 10000 per month. About 36.47 per cent male agricultural students‟ had family income upto Rupees 10000 and 18.82 per cent had family income more than 25000 Rupees per month while; in case of the female agricultural students‟ 32.14 per cent students‟ had family income, ranged between Rupees 10000 to 25000 per month and 32.14 per cent students‟ family income more than 25000 rupees per month (Fig. 5.1.12).
Table 5.1.12: Distribution of internet utilizing male and female agricultural students according to their family income (Rs. per month)
N= 113
S. Category Male Students Female Calculated No. (N=85) Students value (N=28)
F. % F. % X2 1 Up to 10000 31 36.47 10 35.72 2 10001 to 25000 38 44.71 9 32.14 2.49 NS 3 Above 25000 16 18.82 9 32.14 Total 85 100.00 28 100.00 2 X –tab value at 5 per cent level of significance = 5.991 d.f. = 2 NS = Non significant F= Frequency
The calculated value of chi-square (2.49) is less than their tabulated value of chi- square (5.991) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their family income.
5.1.13 Medium of instructions
Table 5.1.13 depicted that majority of the internet utilizing male agricultural students (81.18 per cent) and female agricultural students (75.00 per cent) had hindi medium of instructions, followed by 18.82 per cent of male agricultural students and 25.00 percent female agricultural students had English medium of instructions (Fig. 5.1.13).
Table : 5.1.13: Distribution of internet utilizing male and female agricultural students according to their medium of instruction during school days
N= 113
S. Category Male Female Calculated No. Students Students value (N=85) (N=28) F. % F. % X2 1 Hindi 69 81.18 21 75.00 2 English 16 18.82 7 25.00 0.49 NS 3 Other 0 0.00 0 0.00 Total 85 100.00 28 100.00 2 X –tab value at 5 per cent level of significance = 5.991 d.f. = 2 NS = Non significant F= Frequency
The calculated value of chi-square (0.49) is less than their tabulated value of chi- square (5.991) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their medium of instructions.
5.1.14 Exposure to extra-curricular activities
The table 5.1.14 shows that majority of the male internet utilizing agricultural students (60.00 per cent) participated in debate / lecturing activities while; majority of female agricultural students (67.86 per cent) participated in cultural activities. In case of male agricultural students 57.65 percent participated in games and sports, 54.12 per cent participated in NSS, 49.41 per cent participated in literary activities, 31.76 percent participated in cultural activities, 25.88 per cent participated in NCC, 20.00 per cent participated in other social activities and 17.65 per cent participated in arts activities. While, In case of female agricultural students 60.71 percent participated in arts, 57.14 per cent participated in debate / lecturing, 50.00 per cent participated in literary activities, 42.86 per cent participated in NSS, 39.29 per cent participated in games and sports activities, 32.14 per cent participated in NCC and 25.00 per cent participated in other social activities (Fig. 5.1.14).
Table : 5.1.14: Distribution of internet utilizing male and female agricultural students according to their exposure to extra – curricular activities
N = 113
S. Category Male Students Female Calculated No. (N=85) Students value (N=28) F. % F. % X2 1 Literary 42 49.41 14 50.00 2 Cultural 27 31.76 19 67.86 19.20* 3 Games & Sports 49 57.65 11 39.29 4 Debate / lecturing etc. 51 60.00 16 57.14 5 Arts 15 17.65 17 60.71 6 NCC 22 25.88 9 32.14 7 NSS 46 54.12 12 42.86 8 Other social activities 17 20.00 7 25.00
2 X –tab value at 5 per cent level of significance = 3.841 d.f. = 6 * significant at 5 per cent level of significance F= Frequency The calculated value of chi-square (19.20) is less than their tabulated value of chi- square (12.592) at 5 per cent level of significance. Thus the null hypothesis is rejected and alternative hypothesis is accepted which meant that there is significant agreement between male and female agricultural students with respect to their exposure to extra curricular activities.
5.1.15 Training being extended by college library
The table 5.1.15 revealed that majority of the internet utilizing male agricultural students (82.35 per cent) and female agricultural students (78.57 per cent) did not get any training as how to use internet, followed by 17.65 per cent male agricultural students and 21.43 per cent female agricultural students received training as how to use internet (Fig. 5.1.15).
Table 5.1.15: Distribution of internet utilizing male and female agricultural students according to their training being extended by the college library as to how to use Internet (N= 113) S. No. Category Male Students Female Calculated (N=85) Students value (N=28)
F. % F. % X2 1 Trained by college 15 17.65 6 21.43 library
2 Not trained by college 70 82.35 22 78.57 0.20 NS library
Total 85 100.00 28 100.00
2 X –tab value at 5 per cent level of significance = 3.841 d.f. = 1 NS = Non significant F= Frequency
The calculated value of chi-square (0.20) is less than their tabulated value of chi- square (3.841) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their training being extended by college library.
5.1.16 Study of computer course to know use of internet
The data presented in table 5.1.16 indicated that majority of the male agricultural internet utilizing students (54.12 per cent) did not study of any course to know the use of internet and 45.88 per cent students studied course to know the use of internet, while; majority of female agricultural students (53.57 per cent) studied course to know the use of internet and 46.43 per cent students did not study of any course to know the use of internet (Fig. 5.1.16).
Table 5.1.16: Distribution of internet utilizing male and female agricultural students according to their study of any computer course, to know the use of Internet N= 113 S. Category Male Students Female Students Calculated No. (N=85) (N=28) value F. % F. % X2 1 Studied computer 39 45.88 15 53.57 course 2 Not studied computer 46 54.12 13 46.43 0.49 NS course Total 85 100.00 28 100.00
2 X –tab value at 5 per cent level of significance = 3.841 d.f. = 1 NS = Non significant F= Frequency
The calculated value of chi-square (0.49) is less than their tabulated value of chi- square (3.841) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their study of course to know use of internet.
5.1.17 Type of course studied
A perusal of table 5.1.17 depicted that majority of the internet utilizing male agricultural students (54.12 per cent) and female agricultural students (46.43 per cent) did not study of any type of computer course. In case of male agricultural students 22.35 per cent studied basic Basic + Tally course, 10.58 per cent studied DCA course, 8.24 per cent studied O level course and 4.71 per cent studied C ++ computer course, whereas in case of female agricultural students 24.78 per cent studied basic Basic + Tally course, 10.62 per cent studied DCA course, 7.97 per cent studied O level course and 4.42 per cent studied C ++ computer course (Fig. 5.1.17).
Table 5.1.17: Distribution of internet utilizing male and female agricultural students according to their type of course studied N = 113 S. Category Male Students Female Grand Total No. (N=85) Students (N =113) (N=28) F. % F. % F. % 1 Basic + Tally 19 22.35 9 32.15 28 24.78
2 DCA 9 10.58 3 10.71 12 10.62
3 C ++ 4 4.71 1 3.57 5 4.42
4 O level 7 8.24 2 7.14 9 7.97
5 No course 46 54.12 13 46.43 59 52.21 Total 85 100.00 28 100.00 113 100.00
Calculated X2 = 1.15NS 2 X –tab value at 5 per cent level of significance = 9.488 d.f. = 4 NS = Non significant F= Frequency
The calculated value of chi-square (1.15) is less than their tabulated value of chi- square (9.488) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their type of course studied.
5.1.18 Expertise in navigating the web
The table 5.1.18 revealed that majority of the internet utilizing male agricultural students (56.47 per cent) and female agricultural students (46.43 per cent) perceived themselves as intermediate in navigating the web. In case of male agricultural students 25.88 perceived themselves as advance and 17.65 per cent perceived themselves as beginner, while; in case of female agricultural students 32.14 per cent perceived themselves as advance and 21.43 per cent perceived themselves as beginner in navigating the web (Fig. 5.1.18).
Table 5.1.18 Distribution of internet utilizing male and female agricultural students according to their expertise in navigating the web N = 113
S. Category Male Students Female Students Calculated No. (N=85) (N=28) value F. % F. % X2 1 Beginner 15 17.65 6 21.43
2 Intermediate 48 56.47 13 46.43 0.86 NS
3 Advanced 22 25.88 9 32.14
Total 85 100.00 28 100.00
2 X –tab value at 5 per cent level of significance = 5.991 d.f. = 2 NS = Non significant F= Frequency
The calculated value of chi-square (0.86) is less than their tabulated value of chi- square (5.991) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their expertise in navigating the web.
5.1.19 Place of living at the time of education Table 5.1.19 Distribution of internet utilizing male and female agricultural students according to their place of living at the time of education N = 113 S. Category Male Students Female Calculated No. (N=85) Students value (N=28)
F. % F. % X2 1 Non hosteller 10 11.76 5 17.86 2 Hosteller 75 88.24 23 82.14 0.68 NS
Total 85 100.00 28 100.00 2 X –tab value at 5 per cent level of significance = 3.841 d.f. = 1 NS = Non significant F= Frequency
The data incorporated in table 5.1.19 depicted that majority of the internet utilizing male agricultural students (88.24 per cent) and female agricultural students (82.14 per cent) belonged to hosteller category, followed by 11.76 per cent male agricultural students and 17.86 per cent female agricultural students belonged to non hosteller category (Fig. 5.1.19).
The calculated value of chi-square (0.68) is less than their tabulated value of chi- square (3.841) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their place of living at the time of education.
5.1.20 Wish to migrate abroad
Table 5.1.20 : Distribution of internet utilizing male and female agricultural students according to their wish to migrate abroad N = 113 S. Category Male Female Calculated No. Students Students value (N=85) (N=28) F. % F. % X2 1 No wish to go abroad 22 25.88 13 46.43
2 Wish to go abroad for study 10 11.77 10 35.71 17.80 * 3 Wish to go abroad for settling 53 62.35 5 17.86
Total 85 100.00 28 100.00 2 X –tab value at 5 per cent level of significance = 5.991 d.f. = 2 * significant at 5 per cent level of significance ```F= Frequency
The data presented in table 5.1.20 indicated that majority of the male agricultural internet utilizing students (62.35 per cent) had desire to go abroad for settling whereas majority of the female agricultural students (46.43 per cent) had no desire to go abroad. In case of male agricultural students 25.88 per cent had no desire to go abroad and 11.77 per cent had desire to go for study purpose, while in case of female agricultural students 35.71per cent had desire to go abroad for study and 17.86 per cent had desire to go abroad for settling (Fig. 5.1.20).
The calculated value of chi-square (17.80) is less than their tabulated value of chi- square (5.991) at 5 per cent level of significance. Thus the null hypothesis is rejected and alternative hypothesis is accepted which meant that there is significant agreement between male and female agricultural students with respect to their wish to migrate abroad.
5.1.21 Wish to get higher academic degree
Table 5.1.21 Distribution of internet utilizing male and female agricultural students according to their wish to get higher academic degree
N = 113
S. Category Male Female Calculated No. Students Students value (N=85) (N=28)
F. % F. % X2 1 Willing to have next degree 61 71.76 18 64.29 2 Not willing to have next 24 28.24 10 35.71 0.56 NS degree Total 85 100.00 28 100.00 2 X –tab value at 5 per cent level of significance = 3.841 d.f. = 1 NS = Non significant F= Frequency The table 5.1.21 revealed that majority of the internet utilizing male agricultural students (71.76 per cent) and female agricultural students (64.29 per cent) had wish to have their next higher academic degree, followed by 28.24 per cent male agricultural students and 35.71 per cent female agricultural students had no wish to have their next higher academic degree (Fig. 5.1.21).
The calculated value of chi-square (0.56) is less than their tabulated value of chi- square (3.841) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their wish to get higher academic degree.
5.1.22 Frequency of library use
The table 5.1.22 depicted that majority of the internet utilizing male agriculture students (68.24%) and female agricultural students (60.72%) were utilized library every day. In case of male agricultural students 23.53 percent students utilized library twice in week, 5.88 percent students utilized library once in a week and 2.35 per cent students utilized library once in month, while; in case of female agricultural students 25.00 per cent students utilized library twice in week, 10.71 percent students utilized library once in a week and 3.57 per cent students utilized library once in month (Fig. 5.1.22).
The calculated value of chi-square (1.01) is less than their tabulated value of chi- square (7.815) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their frequency of library use.
5.1.23 Wish to serve in different areas
The data presented in table 5.1.23 indicated that majority of the male internet utilizing agricultural students (61.18 per cent) had wish to serve in banking, whereas; majority of the female agricultural students (67.86 per cent) had wish to serve in government agricultural sector. In case of male agricultural students 49.41 per cent had wish to serve in government agricultural sector, 44.71 per cent had wish to serve in management sector, 34.12 per cent had wish to serve in own business, 30.59 percent students had wish to serve in administrative service, 21.18 per cent students had wish to serve in private agricultural sector, 18.82 per cent students had wish to serve in military,18.82 per cent students had wish to serve in marketing and 14.12 per cent had wish to serve in railway service, while; in case of female agricultural students 64.29 per cent had wish to serve in banking sector, 53.57 per cent had wish to serve in management sector, 28.57 per cent had wish to serve in military services, 21.43 per cent students had wish to serve in own business, 17.86 per cent students had wish to serve in private agricultural sector, 17.86 per cent students had wish to serve in marketing, 14.29 per cent students had wish to serve in administrative services and 10.71 per cent had wish to serve in railway services (Fig 5.1.23). The calculated value of chi-square (31.60) is less than their tabulated value of chi- square (16.919) at 5 per cent level of significance. Thus the null hypothesis is rejected and alternative hypothesis is accepted which meant that there is significant agreement between male and female agricultural students with respect to their wish to serve in different areas.
From the data presented in table 5.1.1 to 5.1.23 it can be concluded that majority of the internet utilizing agricultural students were male, were aged between 20 to 25 years, were studying in B.Sc. degree programme, had obtained OGPA in last semester in category 5.00-6.49 OGPA, had father‟s and mother‟s education above senior secondary and below graduation level, were having occupation of agriculture of their father‟s, were from rural back ground, were belonged to joint family, were belonged to big family, had hindi medium of instructions, did not get any training as how to use internet, studied basic
+ tally course of computer, perceived themselves as intermediate in navigating the web, belonged to hostller category, had wish to have their next higher academic degree, were utilized library every day upto one hour. Majority of male agricultural students were unmarried whereas majority of female agricultural students were married, male agricultural student‟s family income per month ranged between rupees 10001 to 25000 had family income upto rupees 10000 per month, participated in debate/ lecturing participated in cultural activities, did not study any course to know use of internet studied course to know use of internet, had desire to go abroad for settling and had no desire to go abroad, male students had wish to serve in banking and wish to serve in government agricultural sector.
The findings are in conformity with the findings of (Goh 1997; Lee 1997; King and Martin 1999; Sherif and Khan 2000; Anonymous 2001; Bonk 2002; Curtis 2002 and Ali 2004).
5.2 Internet Utilization Pattern of Agricultural Students
For measuring the internet utilization pattern of the agricultural students 19 indicators were identified on the basis of review of literature and discussion with the subject experts as describe in the chapter methodology. The findings regarding these indicators have been presented under following heads:
5.2.1 Experience of internet use
A perusal of Table 5.2.1 indicated that majority of internet utilizing male agriculture students (71.76%) and female agriculture students (53.57%) were using the internet from more than two years. In case of male agriculture students 20.00 per cent internet users were using the internet from 1 to 2 years and 8.24 per cent were using from one year, whereas in case of female agriculture students 25.00 per cent internet users were using the internet from 1 to 2 years and 21.43 per cent were using the internet from the last year only (Fig. 5.2.1).
Table 5.2.1 Experience of internet use of internet utilizing male and female agricultural students N = 113 S. Category Male Students Female Students Calculated No. (N=85) (N=28) value F. % F. % X2 1 Upto 1 year 7 8.24 6 21.43 2 From 1-2 years 17 20.00 7 25.00 4.47 NS 3 More than two years 61 71.76 15 53.57 Total 85 100.00 28 100.00 2 X –tab value at 5 per cent level of significance = 5.991 d.f. = 2 NS = Non significant F= Frequency The calculated value of chi-square (4.47) is less than their tabulated value of chi- square (5.991) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with regard to their experience of internet use.
The results implied that respondents who had more years of internet usage might have acquainted themselves well with the new medium, and might have realized the easy access and usefulness of latest information while exploring the latest information.
5.2.2 Preference of access to internet The data in table 5.2.2 depicted that the male agriculture students mostly preferred college library (MPS 70.59) which was ranked first followed by private cyber cafe (MPS 44.12), division / department (MPS 41.18), hostel (MPS 20.00), own house (MPS 18.82), friends and relative homes (MPS 2.94) which were ranked second, third, fourth, five and six, respectively. Whereas, the female agriculture students mostly preferred college library (MPS 66.07) which was ranked first followed by private cyber cafe (MPS 51.79), division / department (MPS 28.57), own house (MPS 25.00), friends and relatives home (MPS 1.79), hostel (MPS Zero per cent) which were ranked second, third, fourth, five and six, respectively (Fig. 5.2.2).
The values of rank order correlation (rs) between “male and female agricultural students”, were found to be 0.96 for which the calculated values of „t‟ was found higher than the tabulated value at 1 per cent level of significance which indicates a positive and highly significant correlation between male and female agricultural students Hence, the null hypotheses (Ho) was therefore rejected and alternate hypothesis was accepted. This leads to the conclusion that there is a highly significant correlation between the internet utilizing male and female agricultural students in perceiving the preference of access of internet.
The findings might be so due to the region that the best source/ place for using internet. It can be observed that the best source/ place accessed by the respondents were college library. Since the sufficient internet facility was available at college library, the students had to prefer the private cyber café at their own expenses.
5.2.3 Expenditure incurred to use internet (Rs. per month) The table 5.2.3 indicated that majority of internet utilizing male agriculture students (38.82 per cent) and female agriculture students (35.72 per cent) had spent Rs. 50 to 100 Rs. per month to use internet. In case of male agriculture students 27.06 per cent internet users not spending any amount, 14.12 per cent spending 101 to 200 Rs. per month and 10.59 per cent spending 201 to 300 Rs. per month and 9.41 per cent spending around 301 to 400 Rs. per month, whereas female agriculture students 28.57 per cent internet users not spending any amount, 17.86 per cent spending 101 to 200 Rs. Per month,10.71 per cent spending201 to 300 Rs. Per month and 7.14 spending 301 to 400 Rs. Per month (Fig. 5.2.3).
Table 5.2.3 : Expenditure incurred in using internet (Rs. Per month) by internet utilizing male and female agricultural students N=113 S. Category Male Students Female Students Calculated No. (N=85) (N=28) value F. % F. % X2 1 Nil 23 27.06 8 28.57
2 Rs 50-100 33 38.83 10 35.72 0.39 NS 3 Rs 101-200 12 14.12 5 17.86
4 Rs 201-300 9 10.59 3 10.71
5 Rs 301-400 8 9.41 2 7.14
Total 85 100.00 28 100.00 2 X –tab value at 5 per cent level of significance = 9.488 d.f. = 4 NS = Non significant F= Frequency
The calculated value of chi-square (0.39) is less than their tabulated value of chi- square (9.488) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students.
Majority of the respondents spent around Rs. 50-100 per month. It may be because of the reason that, most of the students had access to internet at the private cyber café after the college library because of flexibility in timing, high speed and availability of varied tariff plans.
5.2.4 Frequency of Internet use
The table 5.2.4 indicated that majority of internet utilizing male agriculture students (51.76%) had used internet facility every day out of which 56.82 per cent, 34.09 per cent and 9.09 per cent used internet for upto 1 hours, 2-3 hours and above 3 hours, respectively whereas about (53.57 per cent) female agriculture students had used internet facility every day out of which 60.00 per cent, 26.67 per cent and 13.33 per cent use internet upto 1 hours, 2-3 hours and above 3 hours. In case of male agriculture students (25.88 per cent) had used internet facility once in a week out of which 50.00 per cent, 36.36 per cent and 13.64 per cent use internet for upto 1 hours, 2-3 hours and above 3 hours, respectively, (7.06%) students had used internet facility on occasions out of which half of students used upto 1 hours and 50.00 per cent used upto 2-3 hours, (7.06 %) students had used internet facility once in month, 7.06 per cent had used internet facility once in a month out of which 83.33 per cent used upto 1 hours and 16.67 per cent used above 3 hours (4.71%) had used internet facility twice in a week out of which 75.00 per cent, 25.00 per cent and no students used internet for upto 1 hours, 2-3 hours and above 3 hours and (3.53%) had used internet facility once in fortnight out of which whole students used internet facility upto 2-3 hours,. In case of female agriculture students (21.43%) had used internet facility once in a week out of which 50.00 per cent, 33.33 per cent and 16.67 per cent used upto 1 hours, 2-3 hours and above 3 hours, (7.14%) had used internet facility twice in a week out of which whole students used upto 1 hours, (7.14%) used internet facility once in fortnight out of which whole students used internet upto 2-3 hours, (7.14%) had used internet facility on occasions out of which whole students used internet upto 1 hours and (3.57%) had used internet facility once in a month out of which whole student used upto 1 hours (Fig. 5.2.4).
The calculated value of chi-square (0.418) is less than their tabulated value of chi- square (12.592) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their frequency of internet use.
The findings might be so due to reason that the internet provided variety of information at low cost and have updated information very short period of time, thus more hours spent at internet may be attributed to browsing of latest information among respondents.
5.2.5 Purpose of internet use
The data in presented in table 5.2.5 indicated that majority of the internet utilizing male agriculture students preferred the best purpose on internet use were “e-mail to friends and relatives” (MPS 87.65) while female agriculture students (MPS 83.93) and was ranked first. In case of male agriculture students “searching useful sites for career development” (MPS 87.06), was ranked second followed by “to send or receive e-mails” (MPS 80.00), “to collect information for class assignments” (MPS 78.24), “For sending message” (MPS 72.35), “to collect information for higher studies” (MPS 70.59), “for entertainment” (MPS 61.76), “for preparation of competitive exams” (MPS 58.82), “to collect information for research references” (MPS 57.65), “to send application for job” (MPS 54.71), “to send research articles for publication in research journals” (MPS 41.76), “to collect information‟s to class notes” (MPS 40.00), “chatting” (MPS 38.24), “to collect information for abroad studies” (MPS 32.94), “for generating self employment” (MPS 29.41), “to collect information to attend seminar/ conferences etc. (25.88), “to satisfy curiosity” (MPS 24.12), “just for time pass” (MPS 21.76), “for matrimonial purpose” (MPS 20.00), “for telephony communication” (MPS 12.94) and “to develop own website” (1.76) which were ranked third, fourth, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty and twenty one, respectively. In case of female agriculture students, “searching useful sites for career development” (MPS 80.36), was ranked second followed by “to collect information for class assignments” (MPS 71.43), “to send application for job” (MPS 67.86), “to collect information for higher studies” (MPS 64.29), “to collect information for research references” (MPS 64.29), “to send or receive e-mails” (MPS 64.29), “for sending message” (MPS 62.50), “for entertainment” (MPS 53.57), “to send research articles for publication in research journals” (MPS 46.43), “for preparation for competitive exams” (MPS 44.64), “to collect information‟s to class notes” (MPS 44.64), “to collect information to attend seminar/ conferences etc.” (MPS 33.93), “to collect information for abroad studies” (MPS 32.14), “for generating self employment” (MPS 28.57), “to satisfy curiosity” (MPS 17.86), “chatting” (MPS 14.29), “just for time pass” (MPS 10.71), “for matrimonial purpose” (7.14), “for telephony communication” (MPS 5.36) and “to develop own website” (MPS 0.00) to which were ranked third, fourth, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty and twenty one, respectively (Fig. 5.2.5).
The values of rank order correlation (rs) between “male and female agricultural students” were calculated and tested. The calculated values of „t‟ were found less than their tabulated values which leads to the conclusion that there is a non significant correlation between the internet utilizing male and female agricultural students in perceiving the purpose of internet use. There is no correlation between internet utilizing male and female agricultural students with respect to their purpose of internet use.
Thus, by carefully analyzing the purposes, it is quite obvious that majority of the students required to communicate with each other at least once in a day by e-mail, and of course, every student was found to be very much interested regarding their career development.
5.2.6 Possession of E-mail ID
The data in table 5.2.6 revealed that in case of male agriculture students, 40.00 per cent internet users possessed more than two E-mail ID and followed by 36.47 per cent were having two E-mail ID and 15.29 per cent were having one E-mail ID and 8.24 per cent internet users did not possess any E-mail ID in case of female agriculture students (46.43%) were having two E-mail ID, followed by 17.86 per cent were having more than two E-mail ID and 25.00 per cent were having one E-mail ID and 10.71 per cent internet users did not possess any E-mail ID (Fig. 5.2.6).
Table 5.2.6 : Possession of E-mail ID of internet utilizing male and female agricultural students N=113 S. Category Male Students Female Students Calculated No. (N=85) (N=28) value
F. % F. % X2
1 Nil 7 8.24 3 10.71
2 One E-mail ID 13 15.29 7 25.00 4.80 NS
3 Two E-mail ID 31 36.47 13 46.43 4 More than two E- mail ID 34 40.00 5 17.86
Total 85 100.00 28 100.00 2 X –tab value at 5 per cent level of significance = 7.815 d.f. = 3 NS = Non significant F= Frequency
The calculated value of chi-square (4.80) is less than their tabulated value of chi- square (7.815) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their possession of e-mail ID.
This might be due to the fact that e-mail ID is available free of cost and, users may also require more storage space to save their mails for longer period. This could be the motivational force among the respondents to have two or more than two e-mail IDs.
5.2.7 Frequency of e-mail use
The table 5.2.7 revealed that majority internet utilizing male agriculture students (42.35%) were utilizing e-mail facility every day, out of which 36.11 per cent, 44.44 per cent and 19.44 per cent male agriculture students used one, 2-3 and more than 3 e-mails at a time, respectively and female agriculture students (42.86%) were utilizing e-mail facility every day, out of which 16.67 per cent, 50.00 per cent and 33.33 per cent used one, 2-3 and more than 3 e-mails at a time, respectively. In case of male agriculture students 25.88 per cent, 4.71 per cent, 3.53 per cent, 5.88 per cent and 17.65 per cent students utilized e-mail facility once in a week, twice in a week, once in fortnight, once in a month and on occasions, respectively. In case of female agriculture students 39.29 per cent, 10.71 per cent and 7.14 per cent of the students utilized e-mail facility once in a week, once in a fortnight and once in a month, respectively. On the whole there were not found any student which was never utilized e-mail facility once in a week and on occasions, any time (Fig. 5.2.7).
The calculated value of chi-square (9.66) is less than their tabulated value of chi- square (12.592) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their frequency of e-mail use.
The result showed that majority of the respondents utilized e-mail facility either every day or once in a week. It means that majority of the respondents might have well acquainted with the new medium of communication and might have realized its effectiveness in terms of time and cost.
5.2.8 Purpose of E-mail use
The table 5.2.8 indicated that majority of internet utilizing male agriculture students (49.41%) and female agriculture students (46.43%) used e-mail for personal purpose. In case of male agriculture students 27.06 per cent internet users used e-mail for academic purpose, 11.76 per cent for pleasure purpose, 8.24 per cent for other purpose and 3.53 per cent for advertisement purpose; whereas among female agriculture students 35.72 per cent internet users used e-mail for academic purpose, 10.71 per cent for pleasure purpose, 7.14 per cent for other purpose and no student used e-mail for advertisement purpose (Fig. 5.2.8).
Table 5.2.8 Purpose of E-mail use of internet utilizing male and female agricultural students N=113 S. Category Male Students Female Students Grand Total No. (N=85) (N=28) (N =113) F. % F. % F. % 1 Pleasure 10 11.76 3 10.71 13 11.50 2 Personal 42 49.41 13 46.43 55 48.67 3 Academic 23 27.06 10 35.72 33 29.21 4 Advertisement 3 3.53 0 0.00 3 2.66 5 Others 7 8.24 2 7.14 9 7.96 Total 85 100.00 28 100.00 113 100.00 2 X –tab value at 5 per cent level of significance = 9.488 d.f. = 4 NS = Non significant F= Frequency The calculated value of chi-square (1.62) is less than their tabulated value of chi- square (9.488) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their purpose of e-mail use.
5.2.9 Use of chatting to make communication
The data in table 5.2.9 revealed that in case of male agriculture students, 64.71 per cent internet users use chatting to make communication and 35.29 per cent internet users not used chatting to make communication. In case of female agriculture students 53.57 per cent internet users not used chatting to make communication and 46.43 per cent internet users used chatting to make communication (Fig. 5.2.9).
Table 5.2.9 Chatting to make communication by internet utilizing male and female agricultural students N=113 S. No. Category Male Students (N=85) Female Students Calculated (N=28) value F. % F. % X2 1 Chatting 55 64.71 13 46.43
2 No chatting 30 35.29 15 53.57 2.94 NS
Total 85 100.00 28 100.00 2 X –tab value at 5 per cent level of significance = 3.841 d.f. = 1 NS = Non significant F= Frequency
The calculated value of chi-square (2.94) is less than their tabulated value of chi- square (3.841) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their use of chatting to make communication.
5.2.10 Frequency of chatting
The data in table 5.2.10 indicated that majority of the male agriculture students (25.88%) were utilizing chatting facility once in a week out of which 50.00 per cent, 36.36 per cent and 13.64 per cent used upto 1 hour, 2-3 hour and more than 3 hours, while; majority of the female agriculture students (17.86%) were utilizing chatting facility once in a week out of which 80.00 per cent and 20.00 per cent used upto 1 hour and 2-3 hour. In case of male agriculture students 18.82 per cent, 4.71 per cent, 4.71 per cent, 3.53 per cent and 7.06 per cent students were utilizing chatting facility every day, twice in a week, once in a fortnight, once in a month and on occasion, respectively and 35.29 per cent of the students never utilized chatting facility. In case of female agriculture students 10.71 per cent, 7.14 per cent and 10.71 per cent were utilizing chatting facility every day, once in a week and on occasion, respectively and 53.57 per cent female agricultural students never utilized chatting facility (Fig. 5.2.10).
The calculated value of chi-square (6.05) is less than their tabulated value of chi- square (12.592) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their frequency of chatting.
The findings might be so due to the reason that instant massages are extremely fast in exchanging messages at a time, than the e-mail service. This is the best way available on internet to establish line contact between friends, relative, professors and others.
5.2.11 Use of different search-engines The data in table 5.2.11 depicted that majority of the internet utilizing male agricultural students (MPS 91.18) and female agricultural students (MPS 91.07) used google and was accorded it first rank, followed by Rediff (MPS 85.29), Yahoo (MPS 84.12), Live (MPS 61.76), India times (MPS 55.29), MSN (MPS 47.65), Khoj (MPS 35.88), Ask jeeves (MPS 33.53), Alta vista (MPS 24.12),Info seek (MPS 18.24), Bing (MPS 15.88), Lycos (MPS 15.88), Netscape (MPS 10.59) and Vibisimo (MPS 7.65) which were ranked second, third, fourth, five, six, seven, eight, nine, ten, eleven, twelve thirteen and fourteen, respectively. Whereas, the female agriculture students used yahoo (MPS 85.71), Rediff (MPS 83.93), Live (MPS 64.29), MSN (MPS 51.79), India times (MPS 51.79), Ask jeeves (MPS 41.07), Khoj (MPS 41.07), Info seek (MPS 30.36), Bing (MPS 25.00), Alta vista (MPS 25.00) Lycos (MPS 17.86), Netscape (MPS 12.50) and Vibisimo (MPS 10.71), which were ranked second, third, fourth, five, six, seven, eight, nine, ten, eleven, twelve thirteen and fourteen, respectively (Fig. 5.2.11).
The values of rank order correlation (rs) between male and female agricultural students, were found to be 0.95 for which the calculated values of „t‟ was found higher than their tabulated values at 1 per cent level of significance which indicates a positive and highly significant correlation between male and female agricultural students Hence, the null hypotheses (Ho) was, therefore rejected and alternate hypothesis was accepted. This leads to the conclusion that there is a highly significant correlation between the internet utilizing male and female agricultural students in perceiving the use of different search engines.
This might be due to the reason that the Yahoo and Google search engines are oldest search engines have been made available from very beginning and they are easy to assess and speedy as compared to others. This might be the reason to prefer Google and Yahoo more as compared to other search engines by the research scholars.
5.2.12 Rating internet as sources of information
The result in table 5.2.12 indicated that majority of internet utilizing male agriculture students (60.00%) and female agriculture students (64.29%) rated internet as an excellent source of information. In case of male agriculture students 28.24 per cent rated them as good and 11.76 per cent internet users rated them as satisfactory source of information. In female agriculture students 28.57 per cent rated internet as good source and 7.14 per cent internet users rated it as satisfactory source of information. No male or female agriculture students rated internet as unsatisfactory source (Fig. 5.2.12).
Table 5.2.12 Rating Internet as sources of information by internet utilizing male and female agricultural students N=113 S. Category Male Students Female Students Calculated No. (N=85) (N=28) value
F. % F. % X2 1 Unsatisfactory 0 0.00 0 0.00
2 Satisfactory 10 11.76 2 7.14 0.48 NS
3 Good 24 28.24 8 28.57
4 Excellent 51 60.00 18 64.29
Total 85 100.00 28 100.00
2 X –tab value at 5 per cent level of significance = 7.815 d.f. = 3 NS = Non significant F= Frequency
The calculated value of chi-square (0.48) is less than their tabulated value of chi- square (7.815) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students.
The findings might be so due to the reason that more credibility and trustworthiness of the internet sources among the respondents.
5.2.13 Satisfaction with internet facility
The data presented in table 5.2.13 showed that majority of the internet utilizing male agriculture students (60.00%) and female agriculture students (46.43%) were fully satisfied with internet facility. In case of male agriculture students 30.59 per cent were partially satisfied with internet facility and 9.41 were least satisfied with internet facility. Whereas, in female agriculture students 35.71 per cent internet users were partially satisfied with internet facility and 17.86 per cent were least satisfied with internet facility, no male and female agriculture students were found not satisfied with internet facility (Fig. 5.2.13).
Table 5.2.13 Satisfaction with Internet facility of internet utilizing male and female agricultural students N=113 S. Category Male Students Female Students Calculated No. (N=85) (N=28) value
F. % F. % X2 1 Not satisfied 0 0.00 0 0.00
2 Least satisfied 8 9.41 5 17.86 2.16 NS
3 Partially satisfied 26 30.59 10 35.71 4 Fully satisfied 51 60.00 13 46.43
Total 85 100.00 28 100.00 2 X –tab value at 5 per cent level of significance = 7.815 d.f. = 3 NS = Non significant F= Frequency
The calculated value of chi-square (2.16) is less than their tabulated value of chi- square (7.815) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students.
5.2.14 Preference of internet on other media for getting information
The table 5.2.14 revealed that the majority of male agriculture students preferred “internet” (MPS 92.94) and was ranked first followed by “face to face communication” (MPS 89.02), “newspaper” (MPS 85.88), “television” (MPS 65.49), “magazine” (MPS 50.98), “posters/ charts” (MPS 24.71), “radio” (MPS 18.04), “exhibition” (MPS 15.29) and “kisan mela” (MPS 13.73) which were ranked second, third, fourth, five, six, seven, eight and nine, respectively. Whereas, majority of the female agriculture students preferred “internet” (MPS 85.71) and was ranked first followed by “newspaper” (MPS 84.52), “face to face communication” (MPS 85.95), “television” (MPS 67.86), “magazine” (MPS 48.81), “posters/charts” (MPS 33.33), “exhibition” (MPS 23.81), “kisan mela” (MPS 22.62) and “radio” (MPS 17.86) which were ranked second, third, fourth, five, six, seven, eight and nine, respectively (Fig. 5.2.14). The values of rank order correlation (rs) between male and female agricultural students, were found to be 0.94 for which the calculated values of „t‟ were found higher than their tabulated values at 1 per cent level of significance which indicates a positive and highly significant correlation between male and female agricultural students Hence, the null hypotheses Ho were, therefore rejected and alternate hypotheses were accepted. This leads to the conclusion that there is a highly significant correlation between the internet utilizing male and female agricultural students in perceiving the preference of internet on other media for getting information.
5.2.15 Browsing technique for getting required information
The table 5.2.15 indicated that the majority of the male agriculture students browse the required information from the internet through “use search engines” (MPS 87.06) and was ranked first followed by “typing the web address directly” (MPS 79.41), “printed ads. Newspapers magazines etc”. (MPS 51.76) and “use subscription database” (MPS 25.88) which were ranked second, third and fourth, respectively. Whereas majority of the female agriculture students browse the required information from the internet through “use search engines” (MPS 87.50) and was ranked first followed by followed “type the web address directly” (MPS 64.29), “use subscription database” (MPS 50.00) and “printed ads. Newspapers magazines etc.” (MPS 37.50) which were ranked second, third and fourth, respectively (Fig. 5.2.15).
The values of rank order correlation (rs) between male and female agricultural students, were found to be 0.98 for which the calculated value of „t‟ was found higher than the tabulated value at 1 per cent level of significance which indicates a positive and highly significant correlation between male and female agricultural students Hence, the null hypotheses Ho were, therefore rejected and alternate hypotheses were accepted. This leads to the conclusion that there is a highly significant correlation between the internet utilizing male and female agricultural students in perceiving the browsing technique. The findings due to the fact that most of the respondents were not aware about the subscription data bases.
5.2.16 Frequency of locating the desired information on the internet
The perusal of table 5.2.16 revealed that majority of the internet utilizing male agriculture students (64.70%) and female agriculture student (53.57%) were getting the information on the internet frequently. Both the male agriculture students 27.06 per cent and female agriculture students 28.57 per cent were getting the information on the internet sometime, both the male agriculture students 8.24 per cent and female agriculture students 17.86 per cent were getting the information on the internet rarely and there were no male and female agriculture students mentioned that they never got the desired information on internet (Fig. 5.2.16).
Table 5.2.16 Frequency of locating the desired information on the Internet by internet utilizing male and female agricultural students
N=113 S. Category Male Students Female Students Calculated No. (N=85) (N=28) value F. % F. % X2 1 Never 0 0.00 0 0.00
2 Rarely 7 8.24 5 17.86 2.88 NS
3 Sometime 23 27.06 8 28.57
4 Frequently 55 64.70 15 53.57
Total 85 100.00 28 100.00
2 X –tab value at 5 per cent level of significance = 7.815 d.f. = 3 NS = Non significant F= Frequency
The calculated value of chi-square (2.88) is less than their tabulated value of chi- square (7.815) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their frequency of locating the desired information on the internet.
5.2.17 Activities during internet use
The table 5.2.17 indicated that during internet use of the majority male agriculture students (70.59%) and female agriculture students (57.14 per cent) were writing useful information on separate pages, Whereas 29.41 per cent male agriculture students and 42.86 per cent female agriculture students preferred Internet just for watching and not marking any useful information. It means that research scholars of Swami Keshwanand Agricultural University had seriously exploited Internet facility provided by the Institution (Fig. 5.2.17).
Table 5.2.17 Activities during Internet use by internet utilizing male and female agricultural students N=113 S. Category Male Students Female Calculated No. (N=85) Students value (N=28) F. % F. % X2 1 Just watching Internet 25 29.41 12 42.86
2 Write--useful information‟s 60 70.59 16 57.14 1.73 NS on separate pages
Total 85 100.00 28 100.00 2 X –tab value at 5 per cent level of significance = 3.841 d.f. = 1 NS = Non significant F= Frequency
The calculated value of chi-square (1.73) is less than their tabulated value of chi- square (3.841) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their activities during internet use.
Thus, it might be due to the reason that at the time of exploring Internet, research scholars of Swami Keshwanand Rajasthan Agricultural University executed proper activities to take full advantages of Internet.
5.2.18 Preference of timing of access to internet
The data presented in table 5.2.18 revealed that regarding the preference of timing of access to internet majority of male agricultural students (76.47 %) and female agricultural students (71.43 %) preferred college library and most of them preferred noon time to access the internet. In case of male agricultural students 54.12 per cent were preferred private cyber café and most of them preferred evening time to access the internet, 45.88 per cent preferred division department and most of them preferred morning time to access the internet, 23.53 per cent preferred hostel and most of them preferred night time to access the internet, 18.82 per cent preferred own house and most of them preferred night time to access the internet and 5.88 percent preferred friends and relatives home and most of them preferred evening time to access the internet to access the internet. While; in case of female agricultural students 60.71 per cent were preferred private cyber café and most of them preferred evening time to access the internet, 42.86 per cent preferred division department and most of them preferred morning time to access the internet, 25.00 per cent preferred own house and most of them preferred night time to access the internet, 3.57 per cent preferred hostel and most of them preferred evening time to access the internet and 3.57 percent preferred friends and relatives home and most of them preferred evening time to access the internet to access the internet (Fig. 5.1.18).
The calculated value of chi-square (5.32) is less than their tabulated value of chi- square (11.070) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their preference of timing of access to internet.
5.2.19 Orientation to internet source
The results indicated in table 5.2.19 that majority of the internet utilizing male agriculture students (57.64%) and female agriculture students (50.00%) got orientation towards internet use through self surfing around the net, whereas, 21.18 per cent male agriculture students and 32.14 per cent female agriculture students got orientation towards internet uses through classmates and friends followed by, 14.12 per cent male agriculture students and 7.14 female agriculture students got orientation towards internet uses through other sources and 4.06 per cent male agriculture students and 10.72 per cent female agriculture students got orientation towards internet uses through library staff guidance (Fig. 5.1.19).
Table 5.2.19 Orientation to Internet source of internet utilizing male and female agricultural students N=113 S. Category Male Students Female Grand Total No. (N=85) Students (N =113) (N=28) F. % F. % F. % 1 From my classmates & 18 21.18 9 32.14 27 23.89 friends 2 On my own, by surfing 49 57.65 14 50.00 63 55.75 around the Internet
3 Library staff guidance 6 7.06 3 10.72 9 7.97
4 Other 12 14.12 2 7.14 14 12.39
Total 85 100.00 28 100.00 113 100.00
Calculated X2 = 2.46 NS 2 X –tab value at 5 per cent level of significance = 7.815 d.f. = 3 NS = Non significant F= Frequency
The calculated value of chi-square (2.46) is less than their tabulated value of chi- square (7.815) at 5 per cent level of significance. Thus the null hypothesis is accepted and alternative hypothesis is rejected which meant that there is no significant agreement between male and female agricultural students with respect to their orientation to internet source.
5.2.20 Internet utilization level
For measuring the internet utilization level of the agricultural students. The sources obtained by them in all 19 indicators were summed up, which was called internet utilization score of that particular students. To get in over view of internet utilization level of the selected internet utilizing male and female agricultural students, they were categorized into three internet utilization levels on the basis mean and standard deviation of their internet utilization score viz. low, medium and high. The result has been presented in table 5.2.20 and fig. 5.2.20.
Table 5.2.20: Internet utilization level of internet utilizing male and female agricultural students N=113 S. Category Male Female Grand Total No. Students Students (N =113) (N=85) (N=28) F. % F. % F. %
1 Low utilization (X-σ) 15 17.65 4 14.29 19 16.81
Medium utilization (X- 2 σ to 58 68.24 21 75.00 79 69.91 (X+σ)
3 High utilization (>X+σ ) 12 14.12 3 10.71 15 13.27
Total 85 100.00 28 100.00 113 100.00
Mean = 105.82 SD = 5.22 Calculated X2 = 0.463 NS 2 X –tab value at 5 per cent level of significance = 5.919 d.f. = 2 NS = Non significant F= Frequency
A perusal of data presented in the table visualizes that majority of the male (68.24 per cent) and female (75.00 per cent) agricultural students had medium internet utilization level followed by 17.65 per cent male and 14.29 per cent female agricultural students were having low internet utilization level, whereas only 14.12 per cent male and 10.71 per cent female agricultural students were having level of internet utilization.
It is also clear that majority of the total respondents were belonged to medium level of internet utilization, which indicates that still there is more scope to achieve the effective utilization of the internet facilities.
The calculated value of chi-square (0.463) is less than tabulated value of chi- square (5.919) at 5 per cent level of significance. The null hypothesis accepted and alternate hypothesis rejected which meant that there is no significant agreement between the internet utilization male of female agricultural students with reference to their internet utilization level. Hence it can be concluded that the male and female agricultural students differ in their internet utilization level.
From the data presented in table 5.2.1 to 5.2.20 it can be concluded that majority of the internet utilizing male and female agricultural students were using internet from more than two years, mostly preferred college library, had spent Rs. 50 to 100 per month to use internet, used internet facility every day, considered the best purpose of internet use as “e-mail to friends and relatives”, having more than two e-mails ID, were utilizing e- mail every day upto two to three e-mails, preferred to do the e-mail use for personal use, were utilizing chatting facility once in a week upto one hour, used google as search engine, rated internet as an excellent source of information, were fully satisfied with internet facility, preferred “internet” on other media for getting information, browse the required information from the internet through using search engines, getting the information on the internet frequently, were writing useful information on separate pages during internet use, preferred college library in noon to access the internet, got orientation towards internet use through self surfing around the net and had medium level of internet utilization. Majority of the male agricultural students used chatting to make communication whereas the female agricultural students not used chatting to make communication. The findings are in conformity with the findings of (Patil 1999; Voorbij 1999;
Amritpal Kaur 2000; Chi-Cheng Chang 2001; Anonymous 2002; Kim Deok 2002; Maniar
2002; Teresa et al. 2003; Kalra 2004; Patel 2004; Chouhan 2005 and Patel and Chouhan
2005).
5.3 Effect of internet utilization on overall performance of Agricultural students
In the present investigation an attempt has been made to find out the effect of internet use on academic performances and non academic performances. This was studied by asking simple questions, as how the students perceive the effect of internet services in their academic and non academic performances. The data collected in this respect is presented under the following heads:
5.3.1 Effect of internet use on academic performance of the agricultural students
The data presented in table 5.3.1 indicated that among the different academic performances the „Internet services facilitate improvement in systems of communication‟ was perceived as the most important effect on the academic performance of the male agricultural students (MPS 90.35) and female agricultural students (MPS 87.86) and was accorded first rank. The „Internet facilitates to retrieve latest information through number of sources found‟ was perceived as the second most important effect on the academic performance of the male agricultural students (MPS 89.18) and female agricultural students (MPS 85.71) and was accorded second rank and third rank, respectively (Fig. 5.3.1).
On the other hand „Due to Internet usage, there is a decrease in actual study- hours and live discussions with friends‟ was the least perceived effect on the academic performance of the male agricultural students (MPS 59.06) as well as female agricultural students (MPS 59.29) and was accorded last rank by both male and female agricultural students.
The value of rank order correlation (rs) between male and female agricultural students, was found to be 0.93 for which the calculated value of „t‟ were found higher than the tabulated value at 1 per cent level of significance which indicates a positive and highly significant correlation between the effect internet on the academic performance the male and female agricultural students Hence, the null hypothesis (Ho3.1) was therefore rejected and alternate hypothesis was accepted. This leads to the conclusion that there is a highly significant correlation between the effect of internet on the academic performance of the agricultural students.
5.3.2 Effect of internet use on non academic performance of the agricultural students
The data presented in table 5.3.2 revealed that among the different non academic performances the „Internet services facilitate to maintain a wide circle of friends‟ was perceived as the most important effect on the non-academic performance of the male agricultural students (MPS 82.59) and female agricultural students (MPS 79.29) and was accorded first rank. The „Internet use has increased dependency on Internet‟ was perceived as the second most important effect on the non-academic performance of the male agricultural students (MPS 64.71) and female agricultural students (MPS 61.43) and was accorded second and third rank, respectively (Fig. 5.3.2).
On the other hand „Due to Internet use, there is a decrease in participation in the extra curricular activities at the college/ university level‟ was the least perceived non academic performance by the male agricultural students (MPS 47.76) as well as by the female agricultural students (MPS 49.29) and was accorded last rank by both categories of respondents.
The value of rank order correlation (rs) between male and female agricultural students, was found to be 0.98 for which the calculated value of „t‟ was found higher than the tabulated value at 1 per cent level of significance which indicates a positive and highly significant correlation between male and female agricultural students Hence, the null hypotheses (Ho3.2) were, therefore rejected and alternate hypotheses were accepted. This leads to the conclusion that there is a highly significant correlation between the internet utilizing male and female agricultural students in perceiving the effect of non academic performances.
From the data presented in table 5.1.1 to 5.3.2 it can be concluded that Majority of the internet utilizing male and female agricultural students perceived that the “internet services facilitate improvement in systems of communication” as the most important effect on the academic performance and the “internet services facilitate to maintain a wide circle of friends” as the most important effect on the non-academic performance. The findings are in conformity with the findings of (Richard C. Sharman 1997; Singh
2000; Gagnon and Krovi 2000; Jones 2002 and Chauhan 2004).
5.4 Factors associated with the internet utilization of
agricultural students.
The association between the internet utilization pattern (dependent variable) of male and female agricultural students and the selected independent variables of the male and female agricultural students was worked out by calculating the chi-square between them. On the basis of operational measures used for the variables, research hypotheses in null form were tested for their significance of association on the basis of the values of chi-square and co-efficient of contingency (strength of association), as described below (Fig. 5.4.1 and 5.4.2).
5.4.1 Association of age of internet utilizing male and female agricultural students with their internet utilization
The study of table 5.4.1.reveals that calculated chi-square value between the age and internet utilization for male agricultural student was 1.57 and 3.38 for female agricultural students which were less than their tabulated value at 5 per cent level of significance. Thus the null hypothesis (Ho4.1) which asserts that there is no significant association between their age and internet utilization pattern was accepted. Thus reveals that there is no association between age and internet utilization pattern of the male and female agricultural students.
The result was not in confirmatory with the result of Patel (2004),
Shah (2006) and Patel (2006).
5.4.2 Association of marital status of internet utilizing male and female agricultural
students with their internet utilization The study of table 5.4.2 indicates that calculated chi-square value between marital status and internet utilization for male agricultural student was 5.79 and 2.08 for female agricultural students which were less than their tabulated value at 5 per cent level of significance. Thus the null hypothesis (Ho4.2) which asserts that there is no significant association between their marital status and internet utilization pattern was accepted. Thus reveals that there is no association between marital status and internet utilization pattern of the male and female agricultural students.
5.4.3 Association of educational qualification of internet utilizing male and female
agricultural students with their internet utilization
The data incorporated in table 5.4.3 shows that the calculated chi-square value between educational qualification and internet utilization was 14.62 for male agricultural student and 14.68 for female agricultural students which were significant at 1 per cent level of significance. Thus the null hypothesis (Ho4.3) which asserts that there is no significant association between their educational qualification and internet utilization was rejected and alternative hypothesis was accepted. Further coefficient of contingency was worked out in order to see the strength of association and it was found to be 0.3830 for male and 0.5864 for female agricultural students which can be interpreted that the strength of relationship between the internet utilization pattern and student‟s educational qualification variable exerted highly significant effect on internet utilization pattern of agricultural students.
The result was confirmatory with the result of Jessic et al. (2001), Patel (2004) and Shah (2006). The result was not in line with the result reported by Patel (2006).
5.4.4 Association of academic achievement (OGPA) of internet utilizing male and female agricultural students with their internet utilization
The study of table 5.4.4 indicates that calculated chi-square value between their academic achievement and internet utilization was 10.80 for male agricultural student and
7.27 for female agricultural students which were less than their tabulated value at 5 per cent level of significance. Thus the null hypothesis (Ho4.4) which asserts that there is no significant association between their academic achievement and internet utilization pattern was accepted. Thus reveals that there is no association between academic achievement and internet utilization pattern of the male and female agriculture students.
5.4.5 Association of education of father of internet utilizing male and female agricultural students with their internet utilization
The study of table 5.4.5.shows that calculated chi-square value between their fathers education and internet utilization was 9.43 for male agricultural student and 8.66 for female agricultural students which were less than their tabulated value at 5 per cent level of significance. Thus the null hypothesis (Ho4.5) which asserts that there is no significant association between their fathers education and internet utilization pattern was accepted. Thus reveals that there is no association between education of father and internet utilization pattern of the male and female agricultural students.
The result was in line with the result of Chauhan (2004), Patel and Chauhan (2005) and Chauhan (2005).
5.4.6 Association of education of mother of internet utilizing male and female agricultural students with their internet utilization
The data incorporate in table 5.4.6 indicates that calculated chi-square value between their mothers education and internet utilization was 3.26 for male agricultural student and 8.66 for female agricultural students which were less than their tabulated value at 5 per cent level of significance. Thus the null hypothesis (Ho4.6) which asserts that there is no significant association between their mothers education and internet utilization pattern was accepted. Thus reveals that there is no association between education mother of and internet utilization pattern of the male and female agricultural students.
The result was in line with the result of Patel (2004) and Patel and Chauhan (2005).
5.4.7 Association of occupation of father of internet utilizing male and female agricultural students with their internet utilization The study of table 5.4.7 reveals that calculated chi-square value between their fathers occupation and internet utilization was 4.72 for male agricultural student and 1.51 for female agricultural students which were less than their tabulated value at 5 per cent level of significance. Thus the null hypothesis (Ho4.7) which asserts that there is no significant association between their fathers occupation and internet utilization pattern was accepted. Thus reveals that there is no association between occupation of father and internet utilization pattern of the respondents.
5.4.8 Association of native place of internet utilizing male and female agricultural students with their internet utilization
The study of table 5.4.8 shows that the calculated chi-square value was 9.71 for male agricultural student and 9.23 for female agricultural students which were significant at 1 per cent level of significance. Thus the null hypothesis (Ho4.8) which asserts that there is no significant association between the native place of internet utilization was rejected and alternative hypothesis was accepted. Further coefficient of contingency was worked out in order to see the strength of association and it was found to be 0.3201 for male and 0.4979 for female agricultural students which can be interpreted that the strength of relationship between the internet utilization pattern and student‟s native place variable exerted highly significant effect on internet utilization pattern of agricultural students.
The result was not in line with the result of Anonymous (2001**), Patel and Chauhan (2005), Patel (2004), Chauhan (2004), Chauhan (2005) Patel (2006) and Shah (2006).
5.4.9 Association of type of family of internet utilizing male and female agricultural students with their internet utilization
The data incorporate in table 5.4.9 indicates that calculated chi-square value between their family type and internet utilization was 0.96 for male agricultural student and 0.49 for female agricultural students which were less than their tabulated value at 5 per cent level of significance. Thus the null hypothesis (Ho4.9) which asserts that there is no significant association between their family type and internet utilization pattern was accepted. Thus reveals that there is no association between type of family and internet utilization pattern of the male and female agriculture students.
The result was in line with the result of Patel and Chauhan (2005) and Chauhan (2005).
5.4.10 Association of size of family of internet utilizing male and female agricultural students with their internet utilization
The study of table 5.4.10 reveals that calculated chi-square value between their size of family and internet utilization was 1.57 for male agricultural student and 1.24 for female agricultural students which were less than their tabulated value at 5 per cent level of significance. Thus the null hypothesis (Ho4.10) which asserts that there is no significant association between their size of family and internet utilization pattern was accepted. Thus reveals that there is no association between size of family and internet utilization pattern of the male and female agricultural students.
It means that the research scholars either from small or big size family or say research scholars either from such family with more number or small number of the members in family had approximately one and the same degree of encouragement from their family members to craft hopeful and creative use of Internet.
The result was in line with the result of in line with the result of Patel and Chauhan (2005) and Patel (2004).
5.4.11 Association of family income of internet utilizing male and female agricultural students with their internet utilization
The data incorporate in table 5.4.11 indicates that the calculate chi-square value was 10.62 for male agricultural student and 10.23 for female agricultural students were significant at 5 per cent level of significance. Thus the null hypothesis (Ho4.11) which asserts that there is no significant association between their family income and internet utilization was rejected and alternative hypothesis was accepted. Further coefficient of contingency was worked out in order to see the strength of association and it was found to be 0.3333 for male and 0.5173 for female agricultural students which can be interpreted that the strength of relationship between the internet utilization pattern and student‟s family income variable exerted highly significant effect on internet utilization pattern of agricultural students.
5.4.12 Association of medium of instruction during school days of internet utilizing male and female agricultural students with their internet utilization Table 5.4.12 depicts that calculated chi-square value between their medium of instruction and internet utilization was 0.73 for male agricultural student and 3.17 for female agricultural students which were less than their tabulated value at 5 per cent level of significance. Thus the null hypothesis (Ho4.12) which asserts that there is no significant association between their medium of instruction and internet utilization pattern was accepted. Thus reveals that there is no association between medium of instruction during school days and internet utilization pattern of the male and female agriculture students.
5.4.13 Association of training being extended by the college library to internet utilizing male and female agricultural students with their internet utilization
Table 5.4.13 indicates that the calculated chi-square value between training being extended by the college library and internet utilization was 6.70 for male agricultural student and 7.35 for female agricultural students were significant at 5 per cent level of significance. Thus the null hypothesis (Ho) which asserts that there is no significant association between their training being extended by the college library and internet utilization was rejected and alternative hypothesis was accepted. Further coefficient of contingency was worked out in order to see the strength of association and it was found to be 0.2702 for male and 0.4560 for female agricultural students which can be interpreted that the strength of relationship between the internet utilization pattern and student‟s training being extended by the college library variable exerted highly significant effect on internet utilization pattern of agricultural students
The result reported was in agreement with the result reported by Veena (2001).
5.4.14 Association of computer course studied to know use of internet by internet utilizing male and female agricultural students with their internet utilization
The data incorporate in table 5.4.14 reveals that the calculated chi-square value between their course to know use of internet and internet utilization was 6.82 for male agricultural student and 7.32 for female agricultural students were significant at 5 per cent level of significance. Thus the null hypothesis (Ho4.14) which asserts that there is no significant association between their course to know use of internet and internet utilization was rejected and alternative hypothesis was accepted. Further coefficient of contingency was worked out in order to see the strength of association and it was found to be 0.2726 for male and 0.4553 for female agricultural students which can be interpreted that the strength of relationship between the internet utilization pattern and students course to know use of internet variable exerted highly significant effect on internet utilization pattern of agricultural students.
The result of findings was not in line with the finding reported by Shah (2006).
5.4.15 Association of study of type of computer course studied to know use of internet by internet utilizing male and female agricultural students with their internet utilization
Table 5.4.15 shows that the calculated chi-square value between their study of type of computer course of know use of internet and internet utilization was 17.30 for male agricultural student and 16.48 for female agricultural students were significant at 5 per cent level of significance. Thus the null hypothesis (Ho4.15) which asserts that there is no significant association between their study of course to know use of internet and internet utilization was rejected and alternative hypothesis was accepted. Further coefficient of contingency was worked out in order to see the strength of association and it was found to be 0.4112 for male and 0.6087 for female agricultural students which can be interpreted that the strength of relationship between the internet utilization pattern and student‟s study of course to know use of internet variable exerted highly significant effect on internet utilization pattern of agricultural students.
5.4.16 Association of expertise in navigating web of internet utilizing male and female agricultural students with their internet utilization
The study of table 5.4.16 reveals that the calculated chi-square value between their expertise in navigating and internet utilization was 10.46 for male agricultural student and 10.46 for female agricultural students were significant at 5 per cent level of significance. Thus the null hypothesis (Ho4.16) which asserts that there is no significant association between their expertise in navigating web and internet utilization was rejected and alternative hypothesis was accepted. Further coefficient of contingency was worked out in order to see the strength of association and it was found to be 0.3309 for male and 0.5215 for female agricultural students which can be interpreted that the strength of relationship between the internet utilization pattern and student‟s expertise in navigating web variable exerted highly significant effect on internet utilization pattern of agricultural students. 5.4.17 Association of place of living at the time of education of internet utilizing male and female agricultural students with their internet utilization
The data incorporate in table 5.4.17 depicts that the calculated chi-square value between their place of living and internet utilization was 6.74 for male agricultural student and 6.00 for female agricultural students which were significant at 5 per cent level of significance. Thus the null hypothesis (Ho4.17) which asserts that there is no significant association between their place of living at the time of education and internet utilization was rejected and alternative hypothesis was accepted. Further coefficient of contingency was worked out in order to see the strength of association and it was found to be 0.2710 for male and 0.4202 for female agricultural students which can be interpreted that the strength of relationship between the internet utilization pattern and student‟s place of living at the time of education variable exerted highly significant effect on internet utilization pattern of agricultural students.
The result reported was in agreement with the result reported by Veena (2001).
5.4.18 Association of wish to migrate abroad of internet utilizing male and female agricultural students with their internet utilization
Table 5.4.18 indicates that the calculated chi-square value between their wish to migrate abroad and internet utilization was 14.44 for male agricultural student and 10.81 for female agricultural students which were significant at 1 and 5 per cent level of significance. Thus the null hypothesis (Ho4.18) which asserts that there is no significant association between their wish to migrate abroad and internet utilization was rejected and alternative hypothesis was accepted. Further coefficient of contingency was worked out in order to see the strength of association and it was found to be 0.3810 for male and 0.5277 for female agricultural students which can be interpreted that the strength of relationship between the internet utilization pattern and students wish to migrate abroad variable exerted highly significant effect on internet utilization pattern of agricultural students.
The result was not in line with the result of Chauhan (2004) and Patel and Chauhan (2005).
5.4.19 : Association of wish to get higher academic degree of internet utilizing male and female agricultural students with their internet utilization Table 5.4.19 depicts that calculated chi-square value between their wish to get higher academic degree and internet utilization was 3.46 for male agricultural student and 1.50 for female agricultural students which were less than their tabulated value at 5 per cent level of significance. Thus the null hypothesis (Ho4.19) which asserts that there is no significant association between their wish to get higher academic degree and internet utilization pattern was accepted. Thus reveals that there is no association between wish to get higher academic degree and internet utilization pattern of the male and female agriculture students.
The result reported was in agreement with the result reported by Patel (2004) Chauhan (2004), Chauhan (2005) and Shah (2006).
5.5 Constraints faced in Internet utilization by Agricultural Students
In this section, it was tried to find out the constraints in utilization of internet by the agricultural students in the study area. All the possible constraints, faced by the respondents were grouped in to five major categories viz. Physical constraints, Technical constraints, Economic constraints, Operational constraints and Psychological constraints and the data regarding the constraints faced by internet utilizing male and female agricultural students has been presented into following sub heads.
5.5.1 Physical constraints faced in Internet utilization by Agricultural Students
5.5.2 Technical constraints faced in Internet utilization by Agricultural Students
5.5.3 Economic constraints faced in Internet utilization by Agricultural Students
5.5.4 Operational constraints faced in Internet utilization by Agricultural Students
5.5.5 Psychological Constraints faced in Internet utilization by Agricultural Students 5.5.1 Physical constraints faced in Internet utilization by Agricultural Students
The data presented in table 5.5.1 revealed that among the different physical constraints the „Inadequate availability of computer and Internet facilities‟ was perceived as the most severe constraint at top priority by the male agricultural students (MPS 76.86) and was accorded first rank. Whereas the female agricultural students (MPS 77.38) were perceived it as the third most severe constraint and accorded it third rank. The „Lack of adequate infrastructure facilities‟ was perceived as the most severe constraint by the female agricultural students (MPS 83.33) and was accorded first rank, whereas it was perceived as the second most severe constraint by the male agricultural students (MPS 70.59).
On the other hand the „Lack of knowledge about availability of Internet source‟ was the least perceived physical constraint by the male agricultural students (MPS 61.18) as well as by the female agricultural students (MPS 67.86) and was assigned last rank.
The value of rank order correlation (rs) between male and female agricultural students, was found to be 0.97 for which the calculated value of „t‟ was found higher than the tabulated value at 5 per cent level of significance which indicates a positive and highly significant correlation between male and female agricultural students Hence, the null hypothesis (Ho5.1) was therefore rejected and alternate hypothesis was accepted. This leads to the conclusion that there is a highly significant correlation agreement between the internet utilizing male and female agricultural students in perceiving the severity of different physical constraints (Fig. 5.5.1).
The constraint of inadequate availability of computer and internet facility might be due to the reason that the agriculture college has no sufficient number of computers according to the students strengths and thus the agricultural students face difficulty in access to the internet. The constraint of Lack of adequate infrastructure facilities might be due to the reason that the agriculture colleges had in sufficient sitting arrangement and few computers reserved for girls and thus the students had less access to the internet. The constraint of inadequate accessibility to internet service might be due to lack of the different infrastructural facility and due to the technical problems.
The reason behind the constraint Lack of knowledge about availability of internet source might be due to lack of awareness among the students about the availability of internet source.
5.5.2 Technical constraints faced in Internet utilization by Agricultural Students
The data presented in table 5.5.2 indicated that among the different technical constraints the „Slow access speed‟ was perceived as the most severe constraint at top priority by both the male agricultural students (MPS 74.51) and female agricultural students (MPS 86.90) and was accorded first rank. The constraints „Takes more time to download/ view pages‟ was perceived as the second most severe constraint by the male agricultural students (MPS 65.49) and was accorded second rank, whereas it was perceived as the third most severe constraint by the female agricultural students (MPS 66.67).
On the other hand the „Privacy problem‟ was the least perceived technical constraint by the male agricultural students (MPS 41.96) as well as by the female agricultural students (MPS 42.86) and was assigned last rank.
The value of rank order correlation (rs) between male and female agricultural students, was found to be 0.94 for which the calculated value of „t‟ was found higher than the tabulated value at 1 per cent level of significance which indicates a positive and highly significant correlation between male and female agricultural students Hence, the null hypothesis (Ho5.2) was therefore rejected and alternate hypothesis was accepted. This leads to the conclusion that there is a highly significant agreement between the internet utilizing male and female agricultural students in perceiving the severity of different technical constraints (Fig. 5.5.2).
The constraint of slow access speed might be due to lack of adequate internet connection and frequency. The constraint of taking more time to download / view page might be due to the slow speed of internet. The reason behind constraint of virus threats might be due to lack of technical staff and availability of adequate anti virus softwares. The constraint of Electricity failure might be due to lack of availability of generator and battery system in college library and departments. The constraints of opening of Pop-up mails and Online advertisements distract attention might be due to lack of adequate knowledge about blocked the pop-up mails and lack of training as how to use the internet among the students. The constraint of Server break down might be due lack of suitable channel of connection, overloading of information on server and lack of receiving the frequency.
The reason behind the constraint of Privacy problem might be due to lack of knowledge about use the internet because recently, some websites allow users to stuff off targeted advertising on its web sites.
5.5.3 Economic constraints faced in Internet utilization by Agricultural Students
The data presented in table 5.5.3 revealed that among the different economic constraints the „Variations in charges demanded at different cyber cafes‟ was perceived as the most severe constraint at top priority by the male agricultural students (MPS 52.16) and was accorded first rank. Whereas the female agricultural students (MPS 48.81) perceived it as the second most severe constraint and accorded it second rank. The „Availability of Internet facility at higher price‟ was perceived as the most severe constraint by the female agricultural students (MPS 57.14) and was accorded first rank, whereas it was perceived as the second most severe constraint by the male agricultural students (MPS 49.41).
On the other hand the „High cost of Internet training‟ was the least perceived economics constraints by the male agricultural students (MPS 47.06) as well as by the female agricultural students (MPS 44.05) and was accorded last rank.
The value of rank order correlation (rs) between male and female agricultural students, was calculated and tested. The calculated value of „t‟ was found less than the tabulated value hence the null hypothesis (Ho5.3) was accepted which leads to the conclusion that there is no significant agreement between the internet utilizing male and female agricultural students in perceiving the severity of different economical constraints. Thus there is no correlation between male and female agricultural students (Fig. 5.5.3).
The constraints of Variation in charges at different cyber cafes and Availability of internet facility at higher price might be due to the reason that the cyber cafes had variation in charges of internet facility according to its location and number of customers. In rural and semi-urban areas cyber cafes had high price of internet facility.
The reason behind the constraint of High cost of internet training might be due to the lack of internet training provided by the colleges to the students and the computer training institutes had not provided a particular course of internet training.
5.5.4 Operational constraints faced in Internet utilization by Agricultural Students
The data presented in table 5.5.4 indicated that among the different operational constraints the „Lack of Internet oriented education and training‟ was perceived as the most severe constraint at top priority by the male agricultural students (MPS 75.69) and female agricultural students (MPS 72.62) was accorded first rank. The „Lack of adequate knowledge about hard wares, softwares and Internet explorer‟ was perceived as the second most severe constraint by the male agricultural students (MPS 59.22) and female agricultural students (MPS 60.71) and was accorded second rank.
On the other hand the „Overload of information on Internet‟ was the least perceived operational constraint by the male agricultural students (MPS 41.96) as well as by the female agricultural students (MPS 41.67) and was accorded last rank.
The value of rank order correlation (rs) between male and female agricultural students, was found to be 0.98 for which the calculated value of „t‟ was found higher than the tabulated value at 1 per cent level of significance which indicates a positive and highly significant correlation between male and female agricultural students Hence, the null hypothesis (Ho5.4) were, therefore rejected and alternate hypothesis were accepted. This leads to the conclusion that there is a highly significant agreement between the internet utilizing male and female agricultural students in perceiving the severity of different operational constraints (Fig. 5.5.4).
The constraints of Lack of internet oriented education and training and lack of adequate knowledge about hardware software‟s and internet explorer might be due to the reason that the computer training centers and institutes had not provided the particular course of internet and half of the total agricultural students did not study of any course to know the use of internet. The constraint of Difficulty in finding out relevant information might be due to lack of adequate knowledge about the exact key words related to the information and research study. The constraint of Lack of knowledge about paid and un-paid sites might be due to lack of knowledge about the use of internet which might be due to the lack of internet oriented courses.
The reason behind the constraint of Overload of information on internet might be due to the reason that recently, internet had provided every information to the peoples and thus the web sites had a problem of overloading.
5.5.5 Psychological Constraints faced in Internet utilization by Agricultural Students
The data presented in table 5.5.5 indicated that among the different psychological constraints the „Lack of free time to use Internet‟ was perceived as the most severe constraint at top priority by the male agricultural students (MPS 43.92) and female agricultural students (MPS 44.50) was accorded first rank. The „Lack of interest to use Internet‟ was perceived as the second most severe constraint by the female agricultural students (MPS 42.86) and was accorded second rank, whereas it was perceived as the third most severe constraint by the male agricultural students (MPS 37.65). The „Unfavorable attitude of seniors and family members‟ was perceived as the third most severe constraint by the female agricultural students (MPS 35.71) and was accorded third rank, whereas it was perceived as the second most severe constraint by the male agricultural students (MPS 43.14) and was accorded second rank.
The value of rank order correlation (rs) between male and female agricultural students was calculated and tested. The calculated value of „t‟ was found less than the tabulated value hence the null hypothesis (Ho5.5) which leads to the conclusion that there is a non significant agreement between the internet utilizing male and female agricultural students in perceiving the severity of different psychological constraints. Thus there is no correlation between male and female agricultural students (Fig. 5.5.5).
The constraint of Lack of free time to use internet might be de to the reason that the agricultural students had spent maximum time in attending their classes and research work and they had less time to use the internet. The constraint of Unfavourable attitude of seniors and family members might be due to the lack of sufficient number of computers in college library and department and thus the seniors had not provided the chance to their junior students to use the internet.
The reason behind the constraint of Lack of interest might be due to lack of awareness among the students about the internet.
6 SUMMARY AND CONCLUSIONS
"The internet is a global system of public and private computer networks that allow desktop computer to exchange data. Messages and files with any of the millions of other computer with connections to the internet". The internet is an existing area where you can find information about almost every topic you have books, encyclopedias, magazines, articles and every other type of reference material at your fingertips.
The internet offers many options for computer users to communicate with others like chat, mail, telephone, browse special field for references and so on. The imperative necessity is to mount intense national as well as international efforts in the interest of achieving a bright common future by using the internet technology for all humanity on our planet. So, for this purpose there is a need to develop human resources.
In India, the internet services were officially made available to public from 15th August 1995 onwards through Videsh Sancher Nigam limited (VSNL). Today there are many service providers offering internet services.
The most common use of internet is electronic mail (e-mail). By using e-mail a user can send text, pictures, sounds, programmes or even movies to any other person anywhere in the world. There are a number of news group on the internet. The messages sent to a news group are simply posted on the electronic notice board. Anyone can see these messages.
According to India broadband forum upto 31st March (2008), the number of Internet users in Asia is 5,29,701,704. Though Asia has only 16% of populations of the world, 37.6% of total internet users are Asian which is great. Of them around 60 million are from India. India is 3rd in Asia (1st is China (220 million) and 2nd is Japan (87.5 million)) and 4th in world ((1st is China (220 million), 2nd is USA (216 million) and 3rd is Japan (87.5 million)) as per as internet users are concerned. India has 13% of internet users in Asia and 7.36% that of the world. But the sorrowful fact is only 5.3% of people in India use internet. The reason of this is most of the people in India don‟t know computer. 70% of people who know computer have used internet which is a healthy sign.
Today, Agricultural colleges are playing an important role in imparting technical education. The Agriculturist, who are the outcomes of these colleges, require the latest and pinpointed information in their respective fields. Due to the high cost of Agricultural information resources, developing countries cannot provide these resources to their users. But the Internet with its advantages, make the way for the developing countries to access information at a very low cost.
The Internet is an inseparable part of today‟s Agricultural educational system. Agricultural colleges invest a good deal of amount on providing this facility to both the teachers and students. Despite the young age of the Internet, it has grown at an extremely rapid pace due largely to how easily accessible it has become to users. Each day, something new emerges via the Internet, whether it be a game, a user-created video, or a piece of music that is shared with the world.
Keeping all these facts in mind the present investigation “Internet Utilization Behaviour of Agricultural Students of Swami Keshwanand
Rajasthan Agricultural University, Bikaner”. was undertaken with following specific objectives:
(vi) To study the personal and family characteristics of the respondents. (vii) To analyze the internet utilization pattern of the agricultural students.
(viii) To find out the effect of internet utilization on over all performance of the agricultural students.
(ix) To study the factors associated with the internet utilization of agricultural students.
(x) To identify the constraints faced in internet utilization by the agricultural students.
The present study was conducted in Rajasthan Agricultural University, Bikaner, which was purposively selected due to the reasons that SKRAU, Bikaner is only the sole agricultural university in Rajasthan which has maximum number of agricultural colleges (3) as compared to another Agricultural University i.e. Maharana Pratap University of Agricultural and Technology (MPUAT), Udaipur. SKRAU, Bikaner is the University which provides admission to more number of agricultural Students in an academic session as compared to other Agricultural Universities in Rajasthan. Swami Keshwanand Rajasthan Agricultural University, Bikaner has three constituent Colleges, i.e SKNCOA, Jobner, COA, Bikaner and COA, Lalsot; out of which two agricultural colleges namely SKNCOA, Jobner and COA, Bikaner was selected purposively due to the reason that all the students of these colleges have been provided internet facility at free of cost for UG students in college library and for PG and Ph.D. students in their concerned departments. From the two selected agricultural colleges separate lists of male and female students from B.Sc. (Ag.) Hons, M.Sc. (Ag.) Hons. and Ph.D. degree, registered in 2008-09 and using the internet were prepared with the help of records of student sections and internet cell registers of the respective colleges and a sample of 25 per cent male and female students from B.Sc. (Ag.) Hons, M.Sc. (Ag.) Hons. and Ph.D. degree, was selected by using simple random sampling with proportionate allocation method. In this way a total sample comprised of 113 students (85 male and 28 female students) from B.Sc (Ag.) Hons., M.Sc. (Ag.) Hons. and Ph.D. degrees were selected for the present investigation.
An interview schedule consisting the measuring devices of dependent and independent variables along with the face data of the internet utilizing agricultural students was used for collecting responses of the internet utilizers. For measuring the personal and family characteristics, internet utilization pattern, effect of internet utilization on over all performance and constraints faced by the agricultural students a schedule was developed by the investigator in light of the suggestion of the experts.
The data were collected by personal interview method. The data collected were classified, tabulated and inferences were drawn after subjecting the data to appropriate statistical analysis which led to the following major findings.
SALIENT FINDINGS
6.1 Personal and family characteristics of the respondents
6.1.1 Majority of the internet utilizing agricultural students (75.22%) were male, whereas the female comprised of only 24.78 per cent of the total respondents.
6.1.2 Majority of the internet utilizing students in both male agricultural students (50.58 per cent) and female agricultural students (35.71 per
cent) fell in 20 – 25 years age group. 6.1.3 Majority of the internet utilizing male agricultural students (56.47 per cent) were unmarried and 43.53 percent of the respondents were married. In case of female agricultural students 57.14 per cent were found married and 42.86 per cent were unmarried.
6.1.4 Majority of the internet utilizing students in both male agricultural students (55.29 per cent) and female agricultural students (60.71 per cent) were studying in B. Sc. Degree programme.
6.1.5 Majority of the internet utilizing male agricultural students (61.18 per cent) and female agricultural students (42.85 per cent) had obtained
OGPA 5.01 – 6.49 OGPA in last semester.
6.1.6 Fathers of majority of the internet utilizing male agricultural students (47.06 per cent) and female agricultural students (46.43 per cent) had above senior secondary and below graduation level of education.
6.1.7 Mothers of majority of the internet utilizing male agricultural students (40.00 per cent) and female agricultural students (25.00 per cent) had above senior secondary and below graduation level of education.
6.1.8 Fathers of majority of the internet utilizing male agricultural students (64.70 per cent) and female agricultural students (60. 71 per cent) were having agricultural occupation.
6.1.9 Majority of the internet utilizing male agricultural students (69.41 per cent) and female agricultural students (60.71 per cent) were from rural back ground. 6.1.10 Majority of the internet utilizing male agricultural students (64.71 per cent) and female agricultural students (71.43 per cent) were belonged to joint family.
6.1.11 Majority of the internet utilizing male agricultural students (58.82 per cent) and female agricultural students (53.57 per cent) belonged to big family.
6.1.12 Majority of the internet utilizing male agricultural students‟ (44.71 per cent) had family income, ranging between 10001 to 25000 per
month whereas majority of the female agricultural students‟ (35.72 per cent) had family income ranging between upto Rs 10000.
6.1.13 Majority of the internet utilizing male agricultural students (81.18 per cent) and female agricultural students (75.00 per cent) had Hindi medium of instructions.
6.1.14 Majority of the internet utilizing male agricultural students (60.00 per cent) participated in debate / lecturing activities while; majority of female agricultural students (67.86 per cent) participated in cultural activities.
6.1.15 Majority of the internet utilizing male agricultural students (82.35 per cent) and female agricultural students (78.57 per cent) did not get any training to use internet.
6.1.16 Majority of the internet utilizing male agricultural students (54.12 per cent) had not studied any course to know the use of internet while; majority of female agricultural students (53.57 per cent) studied course to know the use of internet. 6.1.17 About 22.35 per cent internet utilizing male agricultural students and 24.78 per cent of female agricultural students studied basic Basic + Tally computer course.
6.1.18 Majority of the internet utilizing male agricultural students (56.47 per cent) and female agricultural students (46.43 per cent) were intermediate in navigating the web.
6.1.19 Majority of the internet utilizing male agricultural students (88.24 per cent) and female agricultural students (82.14 per cent) belonged to hosteller category.
6.1.20 Majority of the internet utilizing male agricultural students (62.35 per cent) had desire to go abroad for settling whereas majority of the female agricultural students (46.43 per cent) had no desire to go abroad.
6.1.21 Majority of the internet utilizing male agricultural students (71.76 per cent) and female agricultural students (64.29 per cent) had wish to have their next higher academic degree.
6.1.22 Majority of the internet utilizing male agriculture students (68.24%) and female agricultural students (60.72%) were utilized library every day.
6.1.23 Majority of the internet utilizing male agricultural students (61.18 per cent) had wish to serve in banking, whereas; majority of the female agricultural students (67.86 per cent) had wish to serve in government agricultural sector.
6.2 internet utilization pattern of the agricultural students 6.2.1 Majority of internet utilizing male agriculture students (71.76%) and female agriculture students (53.57%) had more than two years experience of internet use age group.
6.2.2 Majority of the internet utilizing male agriculture students (MPS 70.59) and female agriculture students (MPS 66.07) preferred college library for internet use.
6.2.3 Majority of internet utilizing male agriculture students (38.83%) and female agriculture students (75.71%) fell in the category of Rs. 50 to 100 per month expenditure incurred to use internet.
6.2.4 Majority of internet utilizing male agriculture students (51.76%) and (53.57%) female agriculture students had used internet facility every day.
6.2.5 Majority of the internet utilizing male (MPS 87.65) and female (MPS 83.93) agricultural students preferred the best purpose of internet use as “e-mail to friends and relatives”.
6.2.6 About 40.00 per cent internet utilizing male agriculture students were having more than two E-mail ID, while; 38.94 per cent female agriculture students were having two E-mail ID.
6.2.7 Majority of internet utilizing male agriculture students (42.35%) and female agriculture students (42.86%) were utilizing e-mail facility every day.
6.2.8 Majority of the internet utilizing male agriculture students (49.41%) and female agriculture students (46.43%) used e-mail for personal purpose. 6.2.9 Majority of internet utilizing male agriculture students (64.71%) used chatting to make communication, whereas; majority of female agriculture students (53.57%) not used chatting to make communication.
6.2.10 about 25.88 per cent internet utilizing male agriculture students and 17.86 per cent female agriculture students were utilizing chatting facility once in a week.
6.2.11 Majority of the internet utilizing male agricultural students (MPS 91.18) and female agricultural students (MPS 91.07) used google as search engine.
6.2.12 Majority of internet utilizing male agriculture students (60.00%) and female agriculture students (64.29%) considered internet as the excellent source of information.
6.2.13 Majority of the internet utilizing male agriculture students (60.00%) and female agriculture students (46.43%) were fully satisfied with internet facility.
6.2.14 Majority of the internet utilizing male agriculture students (MPS 92.94) and female agriculture students (MPS 85.71) preferred “internet” on other media for getting information.
6.2.15 Majority of the internet utilizing male agriculture students (MPS 27.06) and female agriculture students (MPS 87.50) browse the required information from the internet through using search engines.
6.2.16 Majority of the internet utilizing male agriculture students (64.70%) and female agriculture student (53.57%) were frequently locating the desired information on the internet. 6.2.17 Majority of the internet utilizing male agriculture students (70.59%) and female agriculture students (57.14%) were writing useful information on separate pages during internet use.
6.2.18 Majority of the internet utilizing male agricultural students (76.47 %) and female agricultural students (71.43 %) preferred college library to use internet in noon.
6.2.19 Majority of the internet utilizing male agriculture students 57.65 per cent and female agriculture students 50.00 per cent got orientation towards internet use through self surfing around the net.
6.2.20 Majority of the internet utilizing male (68.24 per cent) and female (75.00 per cent) agricultural students had medium level of internet utilization where as 17.65 per cent male and 14.29 per cent female agricultural students had low internet utilization and only 14.12 per cent male and 10.71 per cent female agricultural students had high level of internet utilization.
6.3 Effect of internet utilization on over all performance of the agricultural students
6.3.1 Among the different academic performances the „Internet services facilitate improvement in systems of communication‟ was perceived as the most important effect on the academic performance at top priority by both male (MPS 90.35) and female agricultural students (MPS 87.86).
There is a highly significant correlation between the internet utilizing male and female agricultural students in perceiving the effect of academic performances. 6.3.2 Among the different non academic performances the „Internet services facilitate to maintain a wide circle of friends‟ was perceived as the most important effect non-academic performance at top priority by both male (MPS 82.59) and female agricultural students (MPS 79.29).
There is a highly significant correlation between the internet utilizing male and female agricultural students in perceiving the effect of non academic performances.
6.4 Factors associated with the internet utilization of agricultural students.
6.4.1 There was a significant association between the internet utilization level of the male and female agricultural students. Educational qualification, native place, family income, training being extended by the college library, course offered to know use of internet, course studied, expertise in navigating web, place of living at the time of education and wish to migrate abroad.
6.4.2 Personal and family characteristics of the respondents like age, marital status, academic achievement, education of father, education of mother, occupation of father, type of family, size of family, medium of instruction during school days and wish to get higher academic degree were found non associated with internet utilization level of the male and female agricultural students. 6.5 Constraints faced in Internet utilization by Agricultural Students
6.5.1 Among the different physical constraints the „Inadequate availability of computer and Internet facilities‟ was perceived as the most severe constraint at top priority by the male agricultural students (MPS 76.86). Whereas; the „Lack of adequate infrastructure facilities‟ was perceived as the most severe constraint by the female agricultural students (MPS 83.33). There is a highly significant correlation between the internet utilizing male and female agricultural students in perceiving the severity of different physical constraints.
6.5.2 Among the different technical constraints the „Slow access speed‟ was perceived as the most severe constraint at top priority by both the male agricultural students (MPS 74.51) and female agricultural students (MPS 86.90). There is a highly significant correlation between the internet utilizing male and female agricultural students in perceiving the severity of different technical constraints.
6.5.3 Among the different economic constraints the „Variations in charges demanded at different cyber cafes‟ was perceived as the most severe constraint at top priority by the male agricultural students (MPS 52.16), while; the „Availability of Internet facility at higher price‟ was perceived as the most severe constraint by the female agricultural students (MPS 57.14). There is a non significant correlation between the internet utilizing male and female agricultural students in perceiving the severity of different economics constraints. Thus there is no correlation between male and female agricultural students.
6.5.4 Among the different operational constraints the „Lack of Internet oriented education and training‟ was perceived as the most severe constraint at top priority by both male agricultural students (MPS 75.69) and female agricultural students (MPS 72.62). There is a highly significant correlation between the internet utilizing male and female agricultural students in perceiving the severity of different operational constraints.
6.5.5 Among the different psychological constraints the „Lack of free time to use Internet‟ was perceived as the most severe constraint at top priority by both male agricultural students (MPS 43.92) and female agricultural students (MPS 44.50). There is a non significant correlation between the internet utilizing male and female agricultural students in perceiving the severity of different psychological constraints. Thus there is no correlation between male and female agricultural students.
Conclusion
1. Majority of the internet utilizing agricultural students were male, were aged between 20 to 25 years, were studying in B.Sc. degree programme, had obtained OGPA in last semester in category 5.00-
6.49 OGPA, had father‟s and mother‟s education above senior secondary and below graduation level, were having occupation of
agriculture of their father‟s, were from rural back ground, were belonged to joint family, were belonged to big family, had hindi medium of instructions, did not get any training as how to use internet, studied basic + tally course of computer, perceived themselves as intermediate in navigating the web, belonged to hestller category, had wish to have their next higher academic degree, were utilized library every day upto one hour. Majority of male agricultural students were unmarried whereas majority of female agricultural students were married, male agricultural student‟s family income per month ranged between rupees 10001 to 25000 had family income upto rupees 10000 per month, participated in debate/ lecturing participated in cultural activities, did not study any course to know use of internet studied course to know use of internet, had desire to go abroad for settling and had no desire to go abroad, male students had wish to serve in banking and wish to serve in government agricultural sector.
2. Majority of the internet utilizing male and female agricultural students were using internet from more than two years, mostly preferred college library, had spent Rs. 50 to 100 per month to use internet, used internet facility every day, considered the best purpose of
internet use as “e-mail to friends and relatives”, having more than two e-mails ID, were utilizing e-mail every day upto two to three e- mails, preferred to do the e-mail use for personal use, were utilizing chatting facility once in a week upto one hour, used google as search engine, rated internet as an excellent source of information,
were fully satisfied with internet facility, preferred “internet” on other media for getting information, browse the required information from the internet through using search engines, getting the information on the internet frequently, were writing useful information on separate pages during internet use, preferred college library in noon to access the internet, got orientation towards internet use through self surfing around the net and had medium level of internet utilization. Majority of the male agricultural students used chatting to make communication whereas the female agricultural students not used chatting to make communication.
3. Majority of the internet utilizing male and female agricultural students perceived that the “internet services facilitate improvement in systems of communication” as the most important effect on the academic performance and the “internet services facilitate to maintain a wide circle of friends” as the most important effect on the non-academic performance.
4. There was a significant association between the internet utilization level of the male and female agricultural students and their educational qualification, native place, family income, training being extended by the college library, course offered to know use of internet, course studied, expertise in navigating web, place of living at the time of education and wish to migrate abroad.
5. Majority of the internet utilizing male agricultural students perceived
the constraints about “inadequate availability of computer and internet facilities”, “lack of adequate infrastructure facilities”, “slow access speed”, “variation in charges demanded at different cyber cafes”, “availability of internet facility at higher price”, “lack of internet oriented education and training” and “lack of free time to use internet”.
Recommendation
1. It is evident from the present study that only moderate level of internet utilization pattern prevailed among respondents. Hence efforts should be made to improve their internet utilization level by improving good internet facility in the college and by motivating students for academic and scholastic uses of internet.
2. Since majority of the internet utilizing students felt the problem of “inadequate availability of computer and internet facility” so efforts should be made to increase the number of computers in college library. 3. Since, majority of the internet utilizing students felt the problem of
“slow access speed”, so efforts should be made for providing adequate connection of the internet.
4. Since, majority of the internet utilizing students felt the problem of
“lack of internet oriented education and training” so efforts should be made to provide training related to internet orientation. There should be provision of appropriate training for agricultural students on educational use of internet.
5. The students should be motivated for computer education and proper use of internet.
6. Since majority of the internet utilizing students felt the problem of
“inadequate availability of computer and internet facilities” so adequate infrastructure facility should be provided by college library.
7. Since majority of the internet utilizing students felt the problem of
“takes more time to download / view pages” so more computers with latest specifications and multimedia kit should be installed in college library.
8. Since majority of the internet utilizing students felt the problem of
“lack of adequate knowledge about hardwires, software‟s and internet explorer” so technical assistant should be appointed in the internet section of the colleges.
Suggestions for future research
The present investigation was confined to a particular institution i.e. SKRAU, Bikaner. The study needs to be replicated on large samples covering large area, so that the inferences drawn can be generalized to a greater extent and explore various theoretical explanations. One can study comparative analysis of SKRAU, Bikaner and MPUAT, Udaipur regarding internet utilization pattern, among students or among teachers. A study of internet utilization behaviour of the farmers may prove worthwhile. Another study could be devoted towards the content analysis of information pertaining to agriculture and allied fields, available on the internet.
Internet Utilization Behaviour of Agricultural Students of Swami Keshwanand Rajasthan Agricultural University, Bikaner
Suresh Garhwal* Dr. Ishaq Mohammed Khan** (Research Scholar) (Major Advisor)
ABSTRACT Internet as a substantial communication tool is characterized by information, versatility and interactivity. Use of internet has become a part of college students daily routine. Considering the importance of the internet utilization the present investigation “Internet Utilization Behaviour of Agricultural Students of Swami Keshwanand Rajasthan Agricultural University, Bikaner”. was undertaken with following specific objectives:
(xi) To study the personal and family characteristics of the respondents.
(xii) To analyze the internet utilization pattern of the agricultural students.
(xiii) To find out the effect of internet utilization on over all performance of the agricultural students.
(xiv) To study the factors associated with the internet utilization of agricultural students.
(xv) To identify the constraints faced in internet utilization by the agricultural students. The present study was undertaken in the purposively selected two agricultural colleges namely SKNCOA, Jobner and COA,
* Post Graduate Student, Department of Extension Education SKN COA, Jobner (Raj.).
** Assistant Professor, Department of Extension Education, S.K.N. College of Agriculture, Jobner (Rajasthan).
Bikaner due to the reason that all the UG and PG students of these colleges have been provided internet facility at free of cost. From the two selected agricultural colleges a total sample comprised of 113 agricultural students (85 male and 28 female students) from B.Sc (Ag.) Hons., M.Sc. (Ag.) Hons. and Ph.D. degrees were selected proportionately by using simple random sampling. An interview schedule consisting the measuring devices of dependent and independent variables along with the face data of the internet utilizing agricultural students was used for collecting responses of the internet utilizers. The data were collected by personal interview method. The data collected were classified, tabulated and inferences were drawn after subjecting the data to appropriate statistical analysis which led to the following major findings. 1. The present study revealed that majority of the internet utilizing male and female agricultural students were in the middle age group, having medium level of fathers and mothers education, having agriculture as a occupation of father, having joint and big family and were having rural background. Majority of the respondents perceived themselves as intermediate in navigating the web, were hosteller, willing to have their next higher academic degree and used the library every day. 2. The result clearly indicated that the majority of the internet utilizing male and female agricultural students were having more than two years experience of internet use, mostly preferred college library, low expenditure incurred to use internet, had used internet facility every day, utilizing e-mail facility every day, used e-mail for personal use, mostly used google as search engine, considered internet as excellent source of information, preferred “internet” on other media for getting information, browse the required information from the internet through using search engines, were frequently locating the desired information on the internet, preferred college library in noon, got orientation towards internet use through self surfing around the net and were belonged to medium level of internet utilization.
3. It was observed that the “Internet services facilitate improvement in systems of communication” was perceived as the most important effect on the academic performance and the “Internet services facilitate to maintain a wide circle of friends” was perceived as the most important effect on the non-academic performance of the male and female agricultural students. 4. There was a significant association between the internet utilization pattern of the male and female agricultural students and their educational qualification, native place, family income, training being extended by the college library, course offered to know use of internet, course studied, expertise in navigating web, place of living at the time of education and wish to migrate abroad. 5. Majority of the internet utilizing agricultural students faced serious constraints about “inadequate availability of computer and internet facilities”, “lack of adequate infrastructure facilities”, “slow access speed”, “variation in charges demanded at different cyber cafes”, “availability of internet facility at higher price”, “lack of internet oriented education and training” and “lack of free time to use internet”. Based on the study, it is recommended that for improving the internet utilization behaviour and over all performance of the male and female agricultural students, the factors having significant agreement in male and female agricultural students should be taken care of and the constraints faced by the internet utilizing students should be solved by the administrators, planners and policy makers of academic institutions in future by formulating effective strategies on exploitation of internet services.
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APPENDIX-I (Covering letter sent to the experts)
From : Dr. I.M. Khan No. ………………. Asstt. Professor Dated : …...…/2009 Deptt. of Extension Education S.K.N. College of Agriculture Jobner (Jaipur) Rajasthan
To, ------Dear Sir
One of my M.Sc. (Ag.) student Mr. Suresh Garhwal, has undertaken a research study entitled, “Internet Utilization Behaviour of Agricultural Students of Rajasthan Agricultural University, Bikaner” for completion of M.Sc. (Ag.) degree in Department of Extension Education. We are trying to develop a comprehensive schedule for measuring following objectives of the said study. (i) To study the personal and family characteristics of the respondents. (ii) To analyze the internet utilization pattern of the agricultural students. (iii) To find out the effect of internet utilization on over all performance of the agricultural students. (iv) To study the factors associated with the internet utilization of agricultural students. (v) To identify the constraints faced in internet utilization by the agricultural students. The statements in the schedule have been developed on the basis of relevant literature, reviewed, personal experience, discussions held with subject matter specialists and extension personnel. In this context, we want to take advantage of your vast experience and knowledge. Kindly spare some time and go through the schedule very critically and feel free to comment upon / add / delete and or modify the statements, if necessary, so that the final schedule can be developed prior to undertake the study. Kindly mail the schedule to the undersigned after your necessary comments in the self addressed stamped envelop attached with schedule.
Thanking you for kind co-operation. Encl: As above
Your’s faithfully
(I.M. Khan) APPENDIX-II
INTERNET UTILIZATION BEHAVIOUR OF AGRICULTURAL STUDDENTS OF RAJASTHAN AGRICULTURAL UNIVERSITY, BIKANER
INTERVIEW SCHEDULE
A. Personal and Family Characteristics of the Agricultural Students
Name : ------1. Gender: a) Male b) Female 2. Age ------years S.No. Category Score a Upto 20 1 years b 21 to 25 2 years c Above 25 3 years
3. Marital status S.No. Category Score A Unmarried 1 B Married 2
4. Educational qualification: S.No. Category Score A B.Sc. 1 B M.Sc. 2 C Ph.D. 3 5. Academic achievement (OGPA obtained during last semester) : S.No. Category Score A Less than 1 5.00 B 5.01 to 6.49 2 C 6.50 to 7.49 3
d 7.50 and 4 above
6. Education of father S.No. Category Score A Illiterate 0 B Up to primary 1 C Up to 2 secondary d Up to Senior 3 secondary E Above senior 4 secondary and below graduation f Graduation 5 and above
7. Education of mother S.No. Category Score A Illiterate 0 B Up to primary 1 C Up to 2 secondary d Up to senior 3 secondary E Above senior 4 secondary and below graduation f Graduation 5 and above
8. Occupation of father
S.No. Activities Yes (1) No (0) A Service B Business C Agriculture
9. What is your native place?...... S.No. Category Score A Rural 1 B Urban 2
10. Type of family S.No. Category Score A Nuclear 1 family B Joint family 2
11. Size of family S.No. Category Score A Small family 1 (up to five members) B Big family 2 (above five members)
12. Family income (Rs. per month) : ------S.No. Category Score A Up to 10000 1
B 10001 to 2 25000 C Above 25000 3
13. Medium of instruction during school days S.No. Category Score A Hindi 1 B English 2 C Others 3
14. Exposure to extra – curricular activities S.No. Activities Yes (1) No (0) A Literary B Cultural C Games & Sports D Debate / lecturing etc. E Arts F NCC G NSS H Other social activities
15. Did you get any training being extended by the college library, as to how to use Internet? S.No. Category Score A Yes 1 B No 0
16. Have you studied any course to know use of Internet?
S.No. Category Score A Yes 1 B No 0
17. If yes, which course you have studied a. ………………………… b. …………………………… c. ………………………….. d. ……………………………..
18. Your expertise in navigating the web is at what level? S.No. Category Score
A Beginner 1 B Intermediate 2 C Advanced 3
19. Place of living at the time of education S.No. Category Score A Non hosteller 1 B Hosteller 2
20. Wish to migrate abroad S.No. Category Score A No wish to 1 go abroad B Wish to go 2 abroad for study C Wish to go 3 abroad for settling
21. Wish to get higher academic degree S.No. Category Score A Willing to 1 have next degree B Not willing to 0 hav e next degree
22. Frequency of library use S.No. Frequency of library Up to 1 hour 2 – 3 hour More than 3 use hour (1) (2) (3) 1 Every day 2 Once in a week 3 Twice in week 4 Once in month
23. Wish to serve in different areas
S.No. Activities Yes (1) No (0) (If yes give your priority) A Banking B Management C Government Agricultural sector D Private Agricultural sector E Own business F Military services G Administrative services H Railway services I Marketing J NGO
B. INTERNET UTILIZATION PATTERN OF AGRICULTURAL STUDENTS
1. Experience of internet use S.No. Category Score A Upto 1 year 1 B From 1-2 2 years C More than 3 two years
2. Preference of access to Internet S.No. Category Mostly (2)
1 College library 2 Own house 3 Division / department 4 Private cyber café 5 Hostel (own) 6 Friends and relatives home
3. Expenditure incurred to use Internet (Rs. per month) ------
S.No. Category Score a Nil 0 b Rs 50- 100 1 c Rs 101-200 2 d Rs 201-300 3 e Rs 301-400 4
4. Frequency of Internet use : S.No. Category Time duration (Hours) Up to 1 hours 2 to 3 hours Above 3 hours (1) (2) (3) 1 Everyday 2 Once in a week 3 Twice in a week 4 Once in fortnight 5 Once in a month 6 On occasions 7 Never
5. Purpose of Internet use S.No. Purpose Mostly Sometimes Never (1) (2) (3)
1 To collect information for class assignments 2 To collect information for research references 3 To send research articles for publication in research journals 4 To collect information for abroad studies 5 To collect information for higher studies 6 To collect information to attend seminar/ conferences etc. 7 Searching useful sites for career development 8 For preparation of competitive exams 9 For generating self employment 10 To send application for job 11 For entertainment 12 E-mail to friends and relatives 13 Chatting 14 Just for time pass 15 For matrimonial purpose 16 For sending message 17 For telephony communication 18 To send or receive E-mails 19 To develop own website 20 To satisfy curiosity 21 To collect informations to class notes
6. Possession of E-mail ID S.No. Category Score a Nil 0 b One E-mail 1 ID c Two E-mail 2 ID d More than 3 two E-mail ID
7. Frequency of E-mail use : S.NO. Category Number of e- mail Up to 1 2 to 3 Above 3 (1) (2) (3) 1 Everyday 2 Once in a week 3 Twice in a week 4 Once in fortnight 5 Once in a month 6 On occasions 7 Never 8. Purpose of E-mail use
S.No. Activities Yes (1) No (0) a Pleasure b Personal c Academic d Advertisement e Others
9. Do you chat to make communication? S.No. Category Score a Yes 1 b No 0
10. If yes indicate frequency of Chatting S.NO. Category Time duration (Hours) Up to 1 2 to 3 Above 3 (1) (2) (3) 1 Everyday 2 Once in a week 3 Twice in a week 4 Once in fortnight 5 Once in a month 6 On occasions 7 Never 11. Have you used following search-Engines? S.NO. Name of search engine Frequency of use Mostly Some times Never (2) (1) (0) 1 Google 2 Yahoo 3 Ask jeeves 4 Alta vista 5 Lycos 6 Info seek 7 Netscape 8 Khoj 9 Rediff 10 India times 11 Vibisimo 12 Bing 13 MSN 14 Live 15 Any other a b c
12. How do you rate Internet as sources of information? S.No. Category Score
a Unsatisfactory 1
b Satisfactory 2
c Good 3
d Excellent 4
13. User satisfaction with Internet facility S.No. Category Score
a Not satisfied 1
b Least 2
satisfied
c Partially 3
satisfied
d Fully 4
satisfied
14. Preference of Internet on other media for getting information? S.NO. Media for getting Preference information Most Less Not preferred preferred preferred (3) (1) (0)
(2) 1 Radio 2 Newspaper 3 Television 4 Magazine 5 Exhibition 6 Posters/ charts 7 Kisan mela 8 Internet 9 Face to face communication
15. How do you browse the required information from the Internet S.No. Browsing Browsing technique pattern Mostly Some times Never (2) (1) (0) 1 Type the web address directly 2 Use search engines 3 Use subscription database 4 Printed Ads. Newspapers, Magazines etc.
16. How often you are able to locate the desired information on the Internet? S.No. Category Score
a Never 0
b Rarely 1 c Sometime 2 d Frequently 3
17. Activity during Internet use S.No. Category Score a Just 1 watching Internet b Write useful 2 informations on separate pages
18. Preference of timing of access to Internet
S.No. Timing preference Morning Noon Evening Night 1 College library 2 Own house 3 Division / Department 4 Private cyber cafe 5 Hostel 6 Friends and relatives home
19. Orientation to Internet source (a) From my classmates & friends (b) On my own, by surfing around the Internet (c) Library staff guidance (d) Other
C. Effect of Internet Utilization on Overall Performance of Agricultural Students (Please indicate that with the availability of Internet facilities at your disposal, up to what extent, they have affected your overall performance?) (I) Academic benefits S.No. Performance indicators Strongly Agree Neutral Disagree Strongly agree disagree (5) (4) (3) (2) (1) A. Internet facilitates to retrieve latest information through number of sources found B Due to Internet usage, there is a decrease in actual study- hours and live discussions with friends C Internet facilitates saving in terms of time and energy looking for information D Internet services are cost- effective E Due to Internet usage there is a decrease in frequency of reading printed materials like books, journals, news papers, etc F Internet services facilitate improvement in systems of communication G The Internet had a positive impact on academic experience in general H Due to Internet usage there is a decrease in frequency of visit to library as well as preparation of hand-written notes. I Internet improved the professional competence of the students J Internet expedited the research process conducted by the students
II Non academic benefits S.No Performance Strongly Agree Neutral Disagree Strongly indicators agree disagree (5) (4) (3) (2) (1) A. Internet services facilitate to maintain a wide circle of friends B Internet use disturbs the “live” social interaction with friends C Due to Internet use, there is a decrease in my participation in the extra curricular activities at the college/ university level
D Due to Internet use, I get health-related problems like eye-pain, back-pain neck-pain and head ache, etc. E Internet use has disturbed my sleeping- pattern erratically. F Internet use has increased my dependency on Internet
D. Constraints faced in Internet utilization by Agricultural students
(Please tick mark in front of all appropriate constraints, which you are facing while utilizing Internet): S. Up to Up to Up to No high medium low extent extent extent
A. Physical constraints 1. Inadequate availability of computer and Internet facilities 2. Inadequate accessibility to Internet services 3. Lack of adequate infrastructure facilities 4. Lack of knowledge about availability of Internet source B Technical constraints 1 Slow access speed 2 Server breakdown 3 Electricity failure 4 On-line advertisements distract attention 5 Virus threats 6 Opening of pop-up mails 7 Privacy problem 8 Takes more time to download/ view pages C Economic constraints 1 Availability of Internet facility at higher price 2 Variations in charges demanded at different cyber cafes 3 High cost of Internet training D Operational constraints 1 Lack of adequate knowledge about hard wares, softwares and Internet explorer 2 Difficulty in finding out relevant information 3 Lack of knowledge about paid and un-paid sites 4. Lack of Internet oriented education and training 5 Overload of information on Internet E Psychological constraints 1. Lack of free time to use Internet 2 Lack of interest to use Internet 3 Unfavorable attitude of seniors and family members F Any other
1. 2. 3.
Table : 5.1.22 : Distribution of internet utilizing male and female agricultural students according to their frequency of library use N = 113
S.No. Category Male students (N =85) Female students (N=28) Upto 1 hour Upto 2-3 More Total Upto 1 Upto 2- More than Total hour than 3 hour 3 hour 3 hour hour
1 Every day 28 22 8 58 10 5 2 17 (48.28) (37.93) (13.79) (68.24) (58.82) (29.41) (11.77) (60.72) 2 Once in a week 3 2 0 5 2 1 0 3 (60.00) (40.00) (0.00) (5.88) (66.67) (33.33) (0.00) (10.71) 3 Twice in week 7 10 3 20 3 3 1 7 (35.00) (50.00) (15.00) (23.53) (42.86) (42.86) (14.28) (25.00) 4 Once in month 0 2 0 2 0 1 0 1 (0.00) (100.00) (0.00) (2.35) (0.00) (100.00) (0.00) (3.57) X2 1.01NS X2 –tab value at 5 per cent level of significance = 7.815 d.f. = 3 NS = Non significant Figures in parenthesis indicate percentage
Table 5.1.23 : Distribution of internet utilizing male and female agricultural students according to their wish to serve in different areas N = 113 S.No. Category Male students (N =85) Female students (N=28) Ist IInd IIIrd Total Ist IInd IIIrd Total
1 Banking 22 16 14 52 9 5 4 18 (42.31) (30.77) (26.92) (61.18) (50.00) (27.78) (22.22) (64.29) 2 Management 16 8 14 38 6 5 4 45 (42.11) (21.05) (36.84) (44.71) (40.00) (33.33) (26.67) (53.57) 3 Government Agricultural sector 27 10 5 42 13 2 4 19 (64.29) (23.81) (11.90) (49.41) (68.42) (10.53) (21.05) (67.86) 4 Private Agricultural sector 3 12 3 18 0 4 1 5 (16.67) (66.67) (16.67) (21.18) (0.00) (80.00) (20.00) (17.86) 5 Own business 7 13 9 29 1 1 4 6 (24.14) (44.83) (31.03) (34.12) (16.67) (16.67) (66.67) (21.43) 6 Military services 0 7 9 16 0 3 5 8 (0.00) (43.75) (56.25) (18.82) (0.00) (37.50) (62.50) (28.57) 7 Administrative services 8 7 11 26 0 2 2 4 (30.77) (26.92) (42.31) (30.59) (0.00) (50.00) (50.00) (14.29) 8 Railway services 0 2 10 12 0 2 1 3 (0.00) (16.67) (83.33) (14.12) (0.00) (66.67) (33.33) (10.71) 9 Marketing 1 7 8 16 0 2 3 5 (6.25) (43.75) (50.00) (18.82) (0.00) (40.00) (60.00) (17.86) 10 NGO 0 0 0 0 0 0 0 0 (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) Calculated X2 = 31.60* X2 –tab value at 5 per cent level of significance = 16.919 d.f. = 9 * significant at 5 per cent level of significance Figures in parenthesis indicate percentage Table 5.2.2 : Preference of access to internet of internet utilizing male and female agricultural students N=113 S.No. Category Male students (N =85) Female students (N=28) Mostly Some Never MPS Rank Mostly Some Never MPS Rank time time
1 College library 56 8 21 70.59 I 16 5 7 66.07 I (65.88) (9.41) (24.71) (57.14) (17.86) (25.00) 2 Own house 16 0 69 18.82 V 7 0 21 25.00 IV (18.82) (0.00) (81.18) (25.00) (0.00) (75.00) 3 Division / department 29 12 44 41.18 III 6 4 18 28.57 III (34.12) (14.12) (51.76) (21.43) (14.29) (64.28) 4 Private cyber cafe 29 17 39 44.12 II 12 5 11 51.79 II (34.12) (20.00) (45.88) (42.86) (17.86) (39.28) 5 Hostel (own) 13 8 64 20.00 IV 0 0 28 0.00 VI (15.29) (9.41) (75.30) (0.00) (0.00) (100.00) 6 Friends and relatives 0 5 80 2.94 VI 0 1 27 1.79 V home (0.00) (5.88) (94.12) (0.00) (3.57) (96.43)
rs = 0.9642** rs = Rank correlation t = 0.828 **significant at 1% level Figures in parenthesis indicate percentage
Table 5.2.4: Frequency of Internet use of internet utilizing male and female agricultural students N=113 S.No. Category Male students (N =85) Female students (N=28) Upto 1 Upto 2 to Above 3 Total Upto 1 Upto 2 to 3 Above 3 Total hours 3 hours hours hours hours hours
1 Everyday 25 15 4 44 9 4 2 15 (56.82) (34.09) (9.09) (51.76) (60.00) (26.67) (13.33) (53.57) 2 Once in a week 11 8 3 22 3 2 1 6 (50.00) (36.36) (13.64) (25.88) (50.00) (33.33) (16.67) (21.43) 3 Twice in a week 3 1 0 4 2 0 0 2 (75.00) (25.00) (0.00) (4.71) (100.00) (0.00) (0.00) (7.14) 4 Once in fortnight 0 3 0 3 0 2 0 1 (0.00) (100.00) (0.00) (3.53) (0.00) (100.00) (0.00) (7.14) 5 Once in a month 5 0 1 6 1 0 0 2 (83.33) (0.00) (16.67) (7.06) (100.00) (0.00) (0.00) (3.57) 6 On occasions 3 3 0 6 2 0 0 2 (50.00) (50.00) (0.00) (7.06) (100.00) (0.00) (0.00) (7.14) 7 Never 0 0 0 0 0 0 0 0 (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) Calculated X2 = 0.418NS X2 –tab value at 5 per cent level of significance = 12.592 d.f. = 6 NS= Non significant Figures in parenthesis indicate percentage
Table 5.2.5: Purpose of internet use of internet utilizing male and female agricultural students N= 113 S. Category Male students (N =85) Female students (N=28) No Mostly Some Never MPS Rank Mostly Some time Never MPS Rank (2) time (1) (0) (2) (1) (0) 1 To collect information for class 57 19 9 78.24 IV 17 6 5 71.43 III assignments (67.06) (22.35) (10.59) (60.71) (21.43) (17.86) 2 To collect information for research 19 60 6 57.65 IX 11 14 3 64.29 V references (22.35) (70.59) (7.06) (39.29) (50.00) (10.71) 3 To send research articles for 26 19 40 41.76 XI 10 6 12 46.43 X publication in research journals (30.59) (22.35) (47.06) (35.71) (21.43) (42.86) 4 To collect information for abroad 23 10 52 32.94 XIV 6 6 16 32.14 XIV studies (27.06) (11.76) (61.18) (21.43) (21.43) (57.14) 5 To collect information for higher 55 10 20 70.59 VI 16 4 8 64.29 V studies (64.71) (11.76) (23.53) (57.14) (14.29) (28.57) 6 To collect information to attend 14 16 55 25.88 XVI 6 7 15 33.93 XIII seminar / conferences etc. (16.47) (18.82) (64.71) (21.43) (25.00) (53.57) 7 Searching useful sites for career 66 16 3 87.06 II 20 5 3 80.36 II development (77.65) (18.82) (3.53) (71.43) (17.86) (10.71) 8 For preparation of competitive exams 40 20 25 58.82 VIII 8 9 11 44.64 XI (47.06) (23.53) (29.41) (28.57) (32.14) (39.29) 9 For generating self employment 16 18 51 29.41 XV 5 6 17 28.57 XV (18.82) (21.18) (60.00) (17.86) (21.43) (60.71) 10 To send application for job 27 39 19 54.71 X 13 12 3 67.86 IV (31.77) (45.88) (22.35) (46.43) (42.86) (10.71) 11 For entertainment 45 15 25 61.76 VII 11 8 9 53.57 IX (52.94) (17.65) (29.41) (39.29) (28.57) (32.14) Cont.d…
12 E-mail to friends and relatives 66 17 2 87.65 I 22 3 3 83.93 I (77.65) (20.00) (2.35) (78.58) (10.71) (10.71) 13 Chatting 22 21 42 38.24 XIII 3 2 23 14.29 XVII (25.88) (24.71) (49.41) (10.71) (7.14) (82.14) 14 Just for time pass 6 25 54 21.76 XVIII 0 6 22 10.71 XVIII (7.06) (29.41) (63.53) (0.00) (21.43) (78.57) 15 For matrimonial purpose 8 18 59 20.00 XIX 0 4 24 7.14 XIX (9.41) (21.18) (69.41) (0.00) (14.29) (85.71) 16 For sending message (53 17 15 72.35 V 14 7 7 62.50 VIII 62.35) (20.00) (17.65) (50.00) (25.00) (25.00) 17 For telephony communication 4 14 67 12.94 XX 0 3 25 5.36 XX (4.71) (16.47) (78.82) (0.00) (10.71) (89.29) 18 To send or receive E-mails 59 18 8 80.00 III 14 8 6 64.29 V (69.41) (21.18) (9.41) (50.00) (28.57) (21.43) 19 To develop own website 0 3 82 1.76 XXI 0 0 28 0.00 XXI (0.00) (3.53) (96.47) (0.00) (0.00) (100.00) 20 To satisfy curiosity 11 19 55 24.12 XVII 3 4 21 17.86 XVI (12.94) (22.35) (64.71) (10.71) (14.29) (75.00) 21 To collect information’s to class 21 26 38 40.00 XII 8 9 11 44.64 XI notes (24.71) (30.59) (44.70) (28.57) (32.14) (39.29)
rs = Rank correlation rs = 0.4202 NS NS = Non signifiant t = 1.9610 Figures in parenthesis indicate percentage
Table 5.2.7: Frequency of e-mail use of internet utilizing male and female agricultural students N= 113 S. Category Male students (N =85) Female students (N=28) No. Upto 1 Upto 2-3 More than 3 Total Upto 1 Upto 2-3 More than 3 Total hour hour hour hour hour hour (1) (2) (3) (1) (2) (3)
1 Everyday 13 16 7 36 2 6 4 12 (36.11) (44.44) (19.44) (42.35) (16.67) (50.00) (33.33) (42.86) 2 Once in a week 10 7 5 22 5 4 2 11 (45.45) (31.82) (22.73) (25.88) (45.45) (36.36) (18.18) (39.29) 3 Twice in a week 0 0 4 4 0 0 0 0 (0.00) (0.00) (100.00) (4.71) (0.00) (0.00) (0.00) (0.00) 4 Once in fortnight 0 0 3 3 0 0 3 3 (0.00) (0.00) (100.00) (3.53) (0.00) (0.00) (100.00) (10.71) 5 Once in a month 1 0 4 5 1 0 1 2 (20.00) (0.00) (80.00) (5.88) (50.00) (0.00) (50.00) (7.14) 6 On occasions 4 6 5 15 0 0 0 0 (26.67) (40.00) (33.33) (17.65) (0.00) (0.00) (0.00) (0.00) 7 Never 0 0 0 0 0 0 0 0 (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) Calculated X2 = 9.66NS X2 –tab value at 5 per cent level of significance = 12.592 d.f. = 6 NS= Non significant Figures in parenthesis indicate percentage
Table 5.2.10: Frequency of Chatting of internet utilizing male and female agricultural students N= 113 S. Category Male students (N =85) Female students (N=28) No. Upto 1 Upto 2-3 More than Total Upto 1 Upto 2-3 More than Total hour hour 3 hour hour hour 3 hour (1) (2) (3) (1) (2) (3) 1 Everyday 13 3 0 16 3 0 0 3 (81.25) (18.75) (0.00) (18.82) (100.00) (0.00) (0.00) (10.71) 2 Once in a week 11 8 3 22 4 1 0 5 (50.00) (36.36) (13.64) (25.88) (80.00) (20.00) (0.00) (17.86) 3 Twice in a week 3 1 0 4 0 2 0 2 (75.00) (25.00) (0.00) (4.71) (0.00) (100.00) (0.00) (7.14) 4 Once in fortnight 2 2 0 4 0 0 0 0 (50.00) (50.00) (0.00) (4.71) (0.00) (0.00) (0.00) (0.00) 5 Once in a month 3 0 0 3 0 0 0 0 (100.00) (0.00) (0.00) (3.53) (0.00) (0.00) (0.00) (0.00) 6 On occasions 5 1 0 6 2 1 0 3 (83.33) (16.67) (0.00) (7.06) (66.67) (33.33) (0.00) (10.71) 7 Never 0 0 0 30 0 0 0 15 (0.00) (0.00) (0.00) (35.29) (0.00) (0.00) (0.00) (53.57) Calculated X2 = 6.05NS X2 –tab value at 5 per cent level of significance = 12.592 d.f. = 6 NS= Non significant Figures in parenthesis indicate percentage
Table 5.2.11 : Use of different search-engines by internet utilizing male and female agricultural students N= 113 S. No. Category Male students (N =85) Female students (N=28) Mostly Some times Never MPS Rank Mostly Some times Never MPS Rank (2) (1) (0) (2) (1) (0) 1 Google 72 11 2 I 23 5 0 I (84.71) (12.94) (2.35) 91.18 (82.14) (17.86) (0.00) 91.07 2 Yahoo 66 11 8 III 23 2 3 II (77.65) (12.94) (9.41) 84.12 (82.14) (7.14) (10.71) 85.71 3 Ask jeeves 15 27 43 VIII 7 9 12 VII (17.65) (31.76) (50.59) 33.53 (25.00) (32.14) (42.86) 41.07 4 Alta vista 11 19 55 IX 3 8 17 X (12.94) (22.35) (64.71) 24.12 (10.71) (28.57) (60.71) 25.00 5 Lycos 8 11 66 XI 2 6 20 XII (9.41) (12.94) (77.65) 15.88 (7.14) (21.43) (71.43) 17.86 6 Info seek 12 7 66 X 6 5 17 IX (14.12) (8.23) (77.65) 18.24 (21.43) (17.86) (60.72) 30.36 7 Netscape 4 10 71 XIII 1 5 22 XIII (4.71) (11.76) (83.53) 10.59 (3.57) (17.86) (78.57) 12.50 8 Khoj 18 25 42 VII 8 7 13 VII (21.18) (29.41) (49.41) 35.88 (28.57) (25.00) (46.43) 41.07 9 Rediff 62 21 2 II 21 5 2 III (72.94) (24.71) (2.35) 85.29 (75.00) (17.86) (7.14) 83.93 10 India times 29 36 20 V 9 11 8 V (34.12) (42.35) (23.53) 55.29 (32.14) (39.29) (28.57) 51.79 11 Vibisimo 0 13 72 XIV 0 6 22 XIV (0.00) (15.29) (84.71) 7.65 (0.00) (21.43) (78.57) 10.71 12 Bing 10 7 68 XI 5 4 19 X (11.76) (8.24) (80.00) 15.88 (17.86) (14.28) (67.86) 25.00 13 MSN 24 33 28 VI 7 15 6 V (28.24) (38.82) (32.94) 47.65 (25.00) (53.57) (21.43) 51.79 14 Live 37 31 17 IV 12 12 4 IV (43.53) (36.47) (20.00) 61.76 (42.86) (42.86) (14.28) 64.29 15 Any other 0 0 0 XV 0 0 0 XV (0.00) (0.00) (0.00) 0.00 (0.00) (0.00) (0.00) 0.00 rs = 0.9535** t = 11.4116 rs = Rank correlation **significant at 1% level of significance Figures in parenthesis indicate percentage Table 5.2.14 : Preference of Internet on other media for getting information by internet utilizing male and female agricultural students N= 113 S. Category Male students (N =85) Female students (N=28) No. Most Preferred Less Not MPS Rank Most Preferred Less Not MPS Rank preferred preferred preferred preferred preferred preferred (3) (2) (1) (0) (3) (2) (1) (0) 1 Radio 0 4 38 43 18.04 VII 0 2 11 15 17.86 IX (0.00) (4.71) (44.70) (50.59) (0.00) (7.14) (39.29) (53.57) 2 Newspaper 55 24 6 0 85.88 III 18 7 3 0 84.52 II (64.71) (28.23) (7.06) (0.00) (64.29) (25.00) (10.71) (0.00) 3 Television 23 40 18 4 65.49 IV 10 9 9 0 67.86 IV (27.06) (47.06) (21.18) (4.70) (35.72) (32.14) (32.14) (0.00) 4 Magazine 14 33 22 16 50.98 V 5 9 8 6 48.81 V (16.47) (38.83) (25.88) (18.82) (17.86) (32.14) (28.57) (21.43) 5 Exhibition 1 9 18 57 15.29 VIII 1 5 7 15 23.81 VII (1.18) (10.58) (21.18) (67.06) (3.57) (17.86) (25.00) (53.57) 6 Posters/ charts 7 10 22 46 24.71 VI 3 6 7 12 33.33 VI (8.24) (11.76) (25.88) (54.12) (10.71) (21.43) (25.00) (42.86) 7 Kisan mela 0 7 21 57 13.73 IX 0 4 11 13 22.62 VIII (0.00) (8.24) (24.70) (67.06) (0.00) (14.28) (39.29) (46.43) 8 Internet 67 18 0 0 92.94 I 19 6 3 0 85.71 I (78.82) (21.18) (0.00) (0.00) (67.86) (21.43) (10.71) (0.00) 9 Face to face 62 18 5 0 89.02 II 15 10 3 0 80.95 III communication (72.94) (21.18) (5.88) (0.00) (53.57) (35.72) (10.71) (0.00) rs = 9444** t =7.6026 rs = Rank correlation **significant at 1% level of significance Figures in parenthesis indicate percentage
Table 5.2.15: Browsing techniques for getting required information from the Internet by internet utilizing male and female agricultural students N= 113 S. Category Male students (N =85) Female students (N=28) No Mostly Some Never MPS Rank Mostly Some Never MPS Rank (2) times (1) (0) (2) times (1) (0)
1 Type the web address directly 54 27 4 79.41 II 12 12 4 64.29 II (63.53) (31.76) (4.71) (42.86) (42.86) (14.28)
2 Use search engines 63 22 0 87.06 I 21 7 0 87.50 I (74.12) (25.88) (0.00) (75.00) (25.00) (0.00)
3 Use subscription database 13 18 54 25.88 IV 11 6 11 50.00 III (15.29) (21.18) (63.53) (39.29) (21.42) (39.29)
4 Printed-advertisements 35 18 32 51.76 III 8 5 15 37.50 IV Newspapers, Magazines etc. (41.18) (21.18) (37.64) (28.57) (17.86) (53.57) rs = 0.9861 t = 15.7086** rs = Rank correlation **significant at 1% level of significance Figures in parenthesis indicate percentage
Table 5.2.18 : Preference of timing of access to internet by internet utilizing male and female agricultural students N= 113 S. Category Male students (N =85) Female students (N=28) No Morning Noon Evening Night Total Morning Noon Evening Night Total 1 College library 24 41 0 0 65 5 15 0 0 20 (36.92) (63.08) (0.00) (0.00) (76.47) (25.00) (75.00) (0.00) (0.00) (71.43) 2 Own house 0 0 5 11 16 0 0 0 7 7 (0.00) (0.00) (31.25) (68.75) (18.82) (0.00) (0.00) (0.00) (100.00) (25.00) 3 Division / Department 28 11 0 0 39 9 3 0 0 12 (71.79) (28.21) (0.00) (0.00) (45.88) (75.00) (25.00) (0.00) (0.00) (42.86) 4 Private cyber cafe 6 0 32 8 46 1 0 12 4 17 (13.04) (0.00) (69.57) (17.39) (54.12) (5.88) (0.00) (70.59) (23.53) (60.71) 5 Hostel 3 0 3 14 20 0 0 1 0 1 (15.00) (0.00) (15.00) (70.00) (23.53) (0.00) (0.00) (100.00) (0.00) (3.57) 6 Friends and relatives home 0 0 5 0 5 0 0 1 0 1 (0.00) (0.00) (100.00) (0.00) (5.88) (0.00) (0.00) (100.00) (0.00) (3.57)
Calculated X2 = 5.32NS X2 –tab value at 5 per cent level of significance = 11.070 d.f. = 5 NS= Non significant Figures in parenthesis indicate percentage
Table 5.3.1: Effect of internet utilization on the academic performance of the male and female agricultural students N = 113 S. Category Male students (N =85) Female students (N=28) No. SA (5) A (4) N (3) DA (2) SDA MPS Rank SA (5) A (4) N (3) DA (2) SDA MPS Rank (1) (1) 1 Internet facilitates to 45 35 4 1 0 89.18 II 14 10 2 2 0 85.71 III retrieve latest (52.94) (41.18) (4.71) (1.18) (0.00) (50.00) (35.71) (7.14) (7.14) (0.00) information through number of sources found 2 Due to Internet 12 15 20 33 5 59.06 IX 4 6 5 11 2 59.29 IX usage, there is a (14.12) (17.65) (23.53) (38.82) (5.88) (14.29) (21.43) (17.86) (39.29) (7.14) decrease in actual study- hours and live discussions with friends 3 Internet facilitates 41 40 2 2 0 88.24 III 14 12 1 1 0 87.86 I saving in terms of (48.24) (47.06) (2.35) (2.35) (0.00) (50.00) (42.86) (3.57) (3.57) (0.00) time and energy looking for information 4 Internet services are 21 43 15 4 2 78.12 V 5 14 5 2 2 72.86 VI cost-effective (24.71) (50.59) (17.65) (4.71) (2.35) (17.86) (50.00) (17.86) (7.14) (7.14) 5 Due to Internet 9 23 16 29 8 59.06 IX 5 7 3 10 3 60.71 VIII usage there is a (10.59) (27.06) (18.82) (34.12) (9.41) (17.86) (25.00) (10.71) (35.71) (10.71) decrease in frequency of reading printed materials like books, journals, news papers, etc
6 Internet services facilitate 47 35 3 0 0 90.35 I 14 11 3 0 0 87.86 I improvement in systems of (55.29) (41.18) (3.53) (0.00) (0.00) (50.00) (39.29) (10.71) (0.00) (0.00) communication 7 The Internet had a positive 35 39 9 2 0 85.18 IV 12 10 4 2 0 82.86 IV impact on academic (41.18) (45.88) (10.59) (2.35) (0.00) (42.86) (35.71) (14.29) (7.14) (0.00) experience in general 8 Due to Internet usage there 15 25 9 29 7 62.82 VIII 5 6 5 7 5 59.29 IX is a decrease in frequency (17.65) (29.41) (10.59) (34.12) (8.24) (17.86) (21.43) (17.86) (25.00) (17.86) of visit to library as well as preparation of hand-written notes. 9 Internet improved the 17 18 18 25 7 63.06 VII 5 6 5 11 1 62.14 VII professional competence of (20.00) (21.18) (21.18) (29.41) (8.24) (17.86) (21.43) (17.86) (39.29) (3.57) the students 10 Internet expedited the 29 23 19 14 0 75.76 VI 10 8 6 4 0 77.14 V research process (34.12) (27.06) (22.35) (16.47) (0.00) (35.71) (28.57) (21.43) (14.29) (0.00) conducted by the students rs = 0.9357** t = 7.5025 rs = Rank correlation **significant at 1% level of significance SA = Strongly agree; A= Agree, N=Netural; DA= Disagree; SDA=Strongly disagree Figures in parenthesis indicate percentage
Table: 5.3.2 Effect of internet utilization on the non academic performance of the male and female agricultural students N=113
S. Category Male students (N =85) Female students (N=28) No. SA (5) A (4) N (3) DA (2) SDA MPS Rank SA (5) A (4) N (3) DA (2) SDA MPS Rank (1) (1) 1 Internet 31 41 7 5 1 82.59 I 8 15 3 0 2 79.29 I services (36.47) (48.24) (8.24) (5.88) (1.18) (28.57) (53.57) (10.71) (0.00) (7.14) facilitate to maintain a wide circle of friends 2 Internet use 4 21 10 42 8 53.18 IV 2 5 3 15 3 51.43 V disturbs the (4.71) (24.71) (11.76) (49.41) (9.41) (7.14) (17.86) (10.71) (53.57) (10.71) “live” social interaction with friends 3 Due to Internet 3 10 9 58 5 47.76 VI 1 5 3 16 3 49.29 VI use, there is a (3.53) (11.76) (10.59) (68.24) (5.88) (3.57) (17.86) (10.71) (57.14) (10.71) decrease in my participation in the extra curricular activities at the college/ university level
4 Due to Internet 9 23 15 29 9 58.59 III 4 9 5 7 3 62.86 II use, I get (10.59) (27.06) (17.65) (34.12) (10.59) (14.29) (32.14) (17.86) (25.00) (10.71) health-related problems like eye-pain, back- pain neck-pain and head ache, etc. 5 Internet use 5 16 14 45 5 53.18 IV 2 5 5 14 2 53.57 IV has disturbed (5.88) (18.82) (16.47) (52.94) (5.88) (7.14) (17.86) (17.86) (50.00) (7.14) my sleeping- pattern erratically. 6 Internet use 18 26 9 22 10 64.71 II 7 6 3 6 6 61.43 III has increased (21.18) (30.59) (10.59) (25.88) (11.76) (25.00) (21.43) (10.71) (21.43) (21.43) my dependency on Internet
rs = 0.9821** t = 10.4407 rs = Rank correlation **significant at 1% level of significance SA = Strongly agree; A= Agree, N=Netural; DA= Disagree; SDA=Strongly disagree Figures in parenthesis indicate percentage
Table -5.5.1: Physical constraints faced by the internet utilizing male and female agricultural students N=113 S.No. Category Male students (N =85) Female students (N=28) Upto Upto Upto MPS Rank Upto Upto Upto MPS Rank high medium low high medium low extent extent extent extent extent extent (2) (1) (0) (2) (1) (0) A. Physical constraints 1. Inadequate availability of computer 40 31 14 76.86 I 14 9 5 77.38 III
and Internet facilities (47.06) (36.47) (16.47) (50.00) (32.14) (17.86)
2. Inadequate accessibility to Internet 21 35 29 63.53 III 13 12 3 78.57 II
services (24.70) (41.18) (34.12) (46.43) (42.86) (10.71)
3. Lack of adequate infrastructure 30 35 20 70.59 II 17 8 3 83.33 I
facilities (35.29) (41.18) (23.53) (60.72) (28.57) (10.71)
4. Lack of knowledge about 16 39 30 61.18 IV 8 13 7 67.86 IV
availability of Internet source (18.82) (45.88) (35.30) (28.57) (46.43) (25.00)
rs = 0.9732* t = 5.9866 rs = Rank correlation *Significant at 5% level of significance Figures in parenthesis indicate percentage
Table -5.5.2: Technical constraints faced by the internet utilizing male and female agricultural students N=113 S.No. Category Male students (N =85) Female students (N=28) Upto Upto Upto MPS Rank Upto Upto Upto MPS Rank high medium low high medium low extent extent extent extent extent extent (2) (1) (0) (2) (1) (0) B Technical constraints 1 Slow access speed 33 39 13 74.51 I 19 7 2 86.90 I (38.82) (45.88) (15.30) (67.86) (25.00) (7.14) 2 Server breakdown 13 13 59 48.63 VII 4 5 19 48.81 VII (15.29) (15.29) (69.42) (14.28) (17.86) (67.86) 3 Electricity failure 17 31 37 58.82 IV 7 5 16 55.95 VI (20.00) (36.47) (43.53) (25.00) (17.86) (57.14) 4 On-line advertisements distract 17 12 56 51.37 VI 9 7 12 63.10 IV attention (20.00) (14.12) (65.88) (32.14) (25.00) (42.86) 5 Virus threats 23 25 37 61.18 III 18 7 3 84.52 II (27.06) (29.41) (43.53) (64.29) (25.00) (10.71) 6 Opening of pop-up mails 14 25 46 54.12 V 6 9 13 58.33 V (16.47) (29.41) (54.12) (21.43) (32.14) (46.43) 7 Privacy problem 6 10 69 41.96 VIII 3 2 23 42.86 VIII (7.06) (11.76) (81.18) (10.71) (7.14) (82.15) 8 Takes more time to download/ 29 24 32 65.49 II 10 8 10 66.67 III view pages (34.12) (28.23) (37.65) (35.71) (28.58) (35.71) rs = 0.9466** t = 7.1792 rs = Rank correlation **Significant at 1% level of significance Figures in parenthesis indicate percentage Table -5.5.3: Economic constraints faced by the internet utilizing male and female agricultural students N=113 S.No. Category Male students (N =85) Female students (N=28) Upto Upto Upto MPS Rank Upto Upto Upto MPS Rank high medium low high medium low extent extent extent extent extent extent (2) (1) (0) (2) (1) (0) C Economic constraints 1 Availability of Internet facility at 13 15 57 49.41 II 6 8 14 57.14 I higher price (15.29) (17.65) (67.06) (21.43) (28.57) (50.00) 2 Variations in charges demanded at 15 18 52 52.16 I 4 5 19 48.81 II different cyber cafes (17.65) (21.18) (61.17) (14.28) (17.86) (67.86) 3 High cost of Internet training 10 15 60 47.06 III 3 3 22 44.05 III (11.76) (17.65) (70.59) (10.71) (10.71) (78.58) rs = 0.9940 NS t = 9.1241 rs = Rank correlation NS = Non-significant Figures in parenthesis indicate percentage Table -5.5.4: Operational constraints faced by the internet utilizing male and female agricultural students N=113 S.No. Category Male students (N =85) Female students (N=28) Upto Upto Upto MPS Rank Upto Upto Upto MPS Rank high medium low high medium low extent extent extent extent extent extent (2) (1) (0) (2) (1) (0) D Operational constraints 1 Lack of adequate knowledge about 21 24 40 59.22 II 7 9 12 60.71 II hard wares, softwares and Internet (24.70) (28.24) (47.06) (25.00) (32.14) (42.86) explorer 2 Difficulty in finding out relevant 14 12 59 49.02 III 5 4 19 50.00 IV information (16.47) (14.12) (69.41) (17.86) (14.28) (67.86) 3 Lack of knowledge about paid and 14 11 60 48.63 IV 6 8 14 57.14 III un-paid sites (16.47) (12.94) (70.59) (21.43) (28.57) (50.00) 4. Lack of Internet oriented education 37 34 14 75.69 I 12 9 7 72.62 I and training (43.53) (40.00) (16.47) (42.86) (32.14) (25.00) 5 Overload of information on Internet 5 12 68 41.96 V 2 3 23 41.67 V (5.88) (14.12) (80.00) (7.14) (10.71) (82.15) rs = 0.9892** t = 11.7368 rs = Rank correlation **Significant at 1% level of significance Figures in parenthesis indicate percentage Table -5.5.5: Psychological constraints faced by the internet utilizing male and female agricultural students N=113 S.No. Category Male students (N =85) Female students (N=28) Upto Upto Upto MPS Rank Upto Upto Upto MPS Rank high medium low high medium low extent extent extent extent extent extent (2) (1) (0) (2) (1) (0) E Psychological constraints 1. Lack of free time to use Internet 6 15 64 43.92 I 3 3 22 44.05 I (7.06) (17.65) (75.29) (10.71) (10.71) (78.58) 2 Lack of interest to use Internet 3 5 77 37.65 III 1 6 21 42.86 II (3.53) (5.88) (90.59) (3.57) (21.43) (75.00) 3 Unfavorable attitude of seniors 6 13 66 43.14 II 1 0 27 35.71 III and family members (7.06) (15.29) (77.65) (3.57) (0.00) (96.43) rs = 0.9940 NS t = 9.1241 rs = Rank correlation NS = Non-significant Figures in parenthesis indicate percentage
Table 5.4.1 Association of age of internet utilizing male and female agricultural students with their internet utilization N=113
S. Category Male students (N=85) Female students (N=28) No. Low Medium High Total Low Medium High Total (i) 20 years 5 12 2 19 1 8 0 9
(3.35) (12.96) (2.68) (22.35) (1.29) (6.75) (0.96) (32.14)
(ii) 20 to 25 years 7 30 6 43 1 8 1 10
(7.59) (29.34) (6.07) (50.59) (1.43) (7.50) (1.07) (35.71)
(iii) Above 25 years 3 16 4 23 2 5 2 9
(4.06) (15.69) (3.25) (27.06) (1.29) (6.75) (0.96) (32.14)
Total 15 58 12 85 4 21 3 28
(17.65) (68.23) (14.12) (100.00) (14.29) (75.00) (10.71) (100.00)
X2 = 1.57 NS X2 = 3.38 NS
X2 –tab value at 5 per cent level of significance = 9.488 d.f. = 4 NS = Non significant Figures in parenthesis indicate percentage
Table 5.4.2 Association of marital status of internet utilizing male and female agricultural students with their internet utilization N=113
S. Category Male students (N=85) Female students (N=28) No. Low Medium High Total Low Medium High Total (i) Unmarried 8 33 8 49 2 8 2 (12
(8.65) (33.44) (6.92) (57.65) (0.29) (1.50) (0.21) 42.86)
(ii) Married 7 25 4 36 (2 13 1 16
(6.35) (24.56) (5.08) (42.35) 0.14) (0.75) (0.11) (57.14)
Total 15 58 12 85 4 21 3 28
(17.65) (68.23) (14.12) (100.00) (14.29) (75.00) (10.71) (100.00)
X2 = 5.79 NS X2 = 2.08 NS
X2 –tab value at 5 per cent level of significance = 5.991 d.f. = 2 NS = Non significant Figures in parenthesis indicate percentage
Table 5.4.3 Association of educational qualification of internet utilizing male and female agricultural students with their internet utilization N=113
S. Category Male students (N=85) Female students (N=28) No. Low Medium High Total Low Medium High Total (i) B.Sc. 11 35 1 47 2 15 0 17
(8.29) (32.07) (6.64) (55.29) (12.75) (1.82) (2.43) (60.71)
(ii) M.Sc. 4 15 8 27 0 4 3 7
(4.76) (18.42) (3.81) (31.76) (5.25) (0.75) (1.00) (25.00)
(iii) Ph.D. 0 8 3 11 2 2 0 4
(1.94) (7.51) (1.55) (12.94) (3.00) (0.43) (0.57) (14.29)
Total 15 58 12 85 4 21 3 28
(17.65) (68.23) (14.12) (100.00) (14.29) (75.00) (10.71) (100.00)
X2 = 14.62** X2 = 14.68** C value = 0.3830 C value = 0.5864 X2 –tab value at 1 per cent level of significance = 13.277 d.f. = 4 ** significant at 1 per cent level of significance Figures in parenthesis indicate percentage
Table 5.4.4 Association of Academic achievement (OGPA) of internet utilizing male and female agricultural students with their internet utilization N=113
S. Category Male students (N=85) Female students (N=28) No. Low Medium High Total Low Medium High Total (i) < 5.0 7 15 2 24 3 9 0 12
(4.24) (16.38) (3.39) (28.24) (1.71) (9.00) (1.29) (42.86)
(ii) 5.00 to 6.49 5 40 7 52 0 8 3 11
(9.18) (35.48) (7.34) (61.18) (1.57) (8.25) (1.18) (39.29)
(iii) 6.50 to 7.49 3 3 3 9 1 4 0 5
(1.59) (6.14) (1.27) (10.59) (0.71) (3.75) (0.54) (17.86)
(iv) 7.5 and above 0 0 0 0 0 0 0 0
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
Total 15 58 12 85 4 21 3 28
(17.65) (68.23) (14.12) (100.00) (14.29) (75.00) (10.71) (100.00)
X2 = 10.19 NS X2 = 7.31NS
X2 –tab value at 5 per cent level of significance = 12.592 d.f. = 6 NS = Non significant Figures in parenthesis indicate percentage
Table 5.4.5 Association of Education of father of internet utilizing male and female agricultural students with their internet utilization N=113
S. Male students (N=85) Female students (N=28) No. Low Medium High Total Low Medium High Total (i) Illiterate 1 5 1 7 0 5 1 6 (1.24) (4.78) (0.99) (8.24) (0.86) (4.50) (0.64) (21.43) (ii) Up to primary 1 2 0 3 0 2 1 3 (0.53) (2.05) (0.42) (3.53) (0.43) (2.25) (0.32) (10.71) (iii) Up to secondary 2 5 2 9 2 1 1 4 (1.59) (6.14) (1.27) (10.59) (0.57) (3.00) (0.43) (14.29) (iv) Up to Senior secondary 4 2 1 7 0 3 0 3 (1.24) (4.78) (0.99) (8.24) (0.43) (2.25) (0.32) (10.71) (v) Above senior secondary 4 30 6 40 1 6 0 7 and below graduation (7.06) (27.29) (5.65) (47.06) (1.00) (5.25) (0.75) (25.00) (vi) Graduation and above 3 14 2 19 1 4 0 5 (3.35) (12.96) (2.68) (22.35) (0.71) (3.75) (0.54) (17.86) Total 15 58 12 85 4 21 3 28 (17.65) (68.23) (14.12) (100.00) (14.29) (75.00) (10.71) (100.00) X2 = 9.43 NS X2 = 8.66 NS
X2 –tab value at 5 per cent level of significance = 18.360 d.f. = 10 NS = Non significant Figures in parenthesis indicate percentage
Table 5.4.6 Association of Education of mother of internet utilizing male and female agricultural students with their internet utilization N=113
S. Male students (N=85) Female students (N=28) No. Low Medium High Total Low Medium High Total (i) Illiterate 1 9 1 11 0 5 1 6 (1.94) (7.51) (1.55) (12.94) (0.86) (4.50) (0.64) (21.43) (ii) Up to primary 3 7 1 11 0 2 1 3 (1.94) (7.51) (1.55) (12.94) (0.43) (2.25) (0.32) (10.71) (iii) Up to secondary 2 5 1 8 2 1 1 4 (1.41) (5.46) (1.13) (9.41) (0.57) (3.00) (0.43) (14.29) (IV) Up to Senior 1 4 2 7 0 3 0 3 secondary (1.24) (4.78) (0.99) (8.24) (0.43) (2.25) (0.32) (10.71) (V) Above senior 6 22 6 34 1 6 0 7 secondary and (6.00) (23.20) (4.80) (40.00) (1.00) (5.25) (0.75) (25.00) below graduation (VI) Graduation and 2 11 1 14 1 4 0 5 above (2.47) (9.55) (1.98) (16.47) (0.71) (3.75) (0.54) (17.86) Total 15 58 12 85 4 21 3 28 (17.65) (68.23) (14.12) (100.00) (14.29) (75.00) (10.71) (100.00)
X2 = 3.26 NS X2 = 8.66 NS
X2 –tab value at 5 per cent level of significance = 18.307 d.f. = 10 NS = Non significant Figures in parenthesis indicate percentage
Table 5.4.7 Association of occupation of father of internet utilizing male and female agricultural students with their internet utilization N=113
S. Category Male students (N=85) Female students (N=28) No. Low Medium High Total Low Medium High Total (i) Service 4 13 1 18 1 3 1 5 (3.18) (12.28) (2.54) (21.18) (0.71) (3.75) (0.54) (17.86) (ii) Business 4 7 1 12 1 4 1 6 (2.12) (8.19) (1.69) (14.12) (0.86) (4.50) (0.64) (21.43) (iii) Agriculture 7 38 10 55 2 14 1 17 (9.71) (37.53) (7.76) (64.71) (2.43) (12.75) (1.82) (60.71) Total 15 58 12 85 4 21 3 28 (17.65) (68.23) (14.12) (100.00) (14.29) (75.00) (10.71) (100.00) X2 = 4.72 NS X2 = 1.51 NS
X2 –tab value at 5 per cent level of significance = 9.488 d.f. = 4 NS = Non significant Figures in parenthesis indicate percentage
Table 5.4.8 Association of native place of internet utilizing male and female agricultural students with their internet utilization N=113
S. Category Male students (N=85) Female students (N=28) No. Low Medium High Total Low Medium High Total (i) Rural 13 42 4 59 0 16 1 17 (10.41) (40.26) (8.33) (69.41) (2.43) (12.75) (1.82) (60.71) (ii) Urban 2 16 8 26 4 5 2 11 (4.59) (17.74) (3.67) (30.59) (1.57) (8.25) (1.18) (39.29) Total 15 58 12 85 4 21 3 28 (17.65) (68.23) (14.12) (100.00) (14.29) (75.00) (10.71) (100.00) X2 = 9.71** X2 = 9.23** C value = 0.3201 C value = 0.4979
X2 –tab value at 1 per cent level of significance = 9.210 d.f. = 2 ** significant at 1 per cent level of significance Figures in parenthesis indicate percentage
Table 5.4.9 Association of type of family of internet utilizing male and female agricultural students with their internet utilization N=113
S. Category Male students (N=85) Female students (N=28) No. Low Medium High Total Low Medium High Total (i) Nuclear family 5 21 4 30 0 7 1 8 (5.29) (20.47) (4.24) (35.29) (1.14) (6.00) (0.86) (28.57) (ii) Joint family 10 37 8 55 4 14 2 20 (9.71) (37.53) (7.76) (64.71) (2.86) (15.00) (2.14) (71.43) Total 15 58 12 85 4 21 3 28 (17.65) (68.23) (14.12) (100.00) (14.29) (75.00) (10.71) (100.00) X2 = 0.96 NS X2 = 0.49 NS
X2 –tab value at 5 per cent level of significance = 5.991 d.f. = 2 NS = Non significant Figures in parenthesis indicate percentage
Table 5.4.10 Association of size of family of internet utilizing male and female agricultural students with their internet utilization N=113
S. Category Male students (N=85) Female students (N=28) No. Low Medium High Total Low Medium High Total (i) Small family (up 7 25 3 35 1 11 1 13 to five members) (6.18) (23.88) (4.94) (41.18) (1.86) (9.75) (1.39) (46.43) (ii) Big family (above 8 33 9 50 3 10 2 15 five members) (8.82) (34.12) (7.06) (58.82) (2.14) (11.25) (1.61) (53.57) Total 15 58 12 85 4 21 3 28 (17.65) (68.23) (14.12) (100.00) (14.29) (75.00) (10.71) (100.00) X2 = 1.57 NS X2 = 1.24 NS
X2 –tab value at 5 per cent level of significance = 5.991 d.f. = 2 NS = Non significant Figures in parenthesis indicate percentage
Table 5.4.11 Association of family income of internet utilizing male and female agricultural students with their internet utilization N=113
S. Category Male students (N=85) Female students (N=28) No. Low Medium High Total Low Medium High Total (i) Up to 10000 8 15 8 31 1 6 3 10 (5.47) (21.15) (4.38) (36.47) (1.43) (7.50) (1.07) (35.71) (ii) 10000 to 4 32 2 38 0 9 0 9 25000 (6.71) (25.93) (5.36) (44.71) (1.29) (6.75) (0.96) (32.14) (iii) > 25000 3 11 2 16 3 6 0 9 (2.82) (10.92) (2.26) (18.82) (1.29) (6.75) (0.96) (32.14) Total 15 58 12 85 4 21 3 28 (17.65) (68.23) (14.12) (100.00) (14.29) (75.00) (10.71) (100.00) X2 = 10.62* X2 = 10.23* C value = 0.3333 C value = 0.5173 X2 –tab value at 5 per cent level of significance = 9.488 d.f. = 4 * significant at 5 per cent level of significance Figures in parenthesis indicate percentage
Table 5.4.12 Association of medium of instruction during school days of internet utilizing male and female agricultural students with their internet utilization N=113
S. Category Male students (N=85) Female students (N=28) No. Low Medium High Total Low Medium High Total (i) Hindi 11 48 10 69 3 17 1 21 (12.18) (47.08) (9.74) (81.18) (3.00) (15.75) (2.25) (75.00) (ii) English 4 10 2 16 1 4 2 7 (2.82) (10.92) (2.26) (18.82) (1.00) (5.25) (0.75) (25.00) (iii) Others 0 0 0 0 0 0 0 0 0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) Total 15 58 12 85 4 21 3 28 (17.65) (68.23) (14.12) (100.00) (14.29) (75.00) (10.71) (100.00) X2 = 0.73 NS X2 = 3.17 NS
X2 –tab value at 5 per cent level of significance = 9.488 d.f. = 4 NS = Non significant Figures in parenthesis indicate percentage
Table 5.4.13 Association of training being extended by the college library of internet utilizing male and female agricultural students with their internet utilization N=113
S. Category Male students (N=85) Female students (N=28) No. Low Medium High Total Low Medium High Total (i) Yes 5 6 4 15 2 2 2 6 (2.65) (10.24) (2.12) (17.65) (0.86) (4.50) (0.64) (21.43) (ii) No (10 52 8 70 2 19 1 22 12.35) (47.76) (9.88) (82.35) (3.14) (16.50) (2.36) (78.57) Total 15 58 12 85 4 21 3 28 (17.65) (68.23) (14.12) (100.00) (14.29) (75.00) (10.71) (100.00) X2 = 6.70* X2 = 7.35* C value = 0.2702 C value = 0.4560
X2 –tab value at 5 per cent level of significance = 5.991 d.f. = 2 * significant at 5 per cent level of significance Figures in parenthesis indicate percentage
Table 5.4.14 Association of computer course studied to know use of internet by internet utilizing male and female agricultural students with their internet utilization N=113 S. Category Male students (N=85) Female students (N=28) No. Low Medium High Total Low Medium High Total (i) Yes 3 32 4 39 0 12 3 15 (6.88) (26.61) (5.51) (45.88) (2.14) (11.25) (1.61) (53.57) (ii) No 12 26 8 46 4 9 0 13 (8.12) (31.39) (6.49) (54.12) (1.86) (9.75) (1.39) (46.43) Total 15 58 12 85 4 21 3 28 (17.65) (68.23) (14.12) (100.00) (14.29) (75.00) (10.71) (100.00) X2 = 6.82* X2 = 7.32* C value = 0.2726 C value = 0.4553
X2 –tab value at 5 per cent level of significance = 5.991 d.f. = 2 * significant at 5 per cent level of significance Figures in parenthesis indicate percentage
Table 5.4.15 Association of type of computer course studied to know use of internet by internet utilizing male and female agricultural students with their internet utilization N=113
S. Category Male students (N=85) Female students (N=28) No. Low Medium High Total Low Medium High Total (i) Basic + Tally 3 14 2 19 1 8 0 9 (3.35) (12.96) (2.68) (22.35) (1.29) (6.75) (0.96) (32.14) (ii) DCA 3 3 3 9 1 1 1 3 (1.59) (6.14) (1.27) (10.59) (0.43) (2.25) (0.32) (10.71) (iii) C ++ 1 3 0 4 0 1 0 1 (0.71) (2.73) (0.56) (4.71) (0.14) (0.75) (0.11) (3.57) (iv) O level 0 3 4 7 2 0 0 2 (1.24) (4.78) (0.99) (8.24) (0.29) (1.50) (0.21) (7.14) (v) No course 8 35 3 46 0 11 2 13 (8.12) (31.39) (6.49) (54.12) (1.86) (9.75) (1.39) (46.43) Total 15 58 12 85 4 21 3 28 (17.65) (68.23) (14.12) (100.00) (14.29) (75.00) (10.71) (100.00) X2 = 17.30* X2 = 16.48* C value = 0.4112 C value = 0.6087
X2 –tab value at 5 per cent level of significance = 15.507 d.f. = 8 * significant at 5 per cent level of significance Figures in parenthesis indicate percentage Table 5.4.16 Association of Expertise in navigating web of internet utilizing male and female agricultural students with their internet utilization N=113
S. Category Male students (N=85) Female students (N=28) No. Low Medium High Total Low Medium High Total (i) Beginner 1 12 2 15 1 3 2 6 (2.65) (10.24) (2.12) (17.65) (0.86) (4.50) (0.64) (21.43) (ii) Intermediate 14 28 6 48 0 13 0 13 (8.47) (32.75) (6.78) (56.47) (1.86) (9.75) (1.39) (46.43) (iii) Advanced 0 18 4 22 3 5 1 9 (3.88) (15.01) (3.11) (25.88) (1.29) (6.75) (0.96) (32.14) Total 15 58 12 85 4 21 3 28 (17.65) (68.23) (14.12) (100.00) (14.29) (75.00) (10.71) (100.00) 2 X = 10.46* X2 = 10.46* C value = 0.3309 C value = 0.5215
X2 –tab value at 5 per cent level of significance = 9.488 d.f. = 4 * significant at 5 per cent level of significance Figures in parenthesis indicate percentage
Table 5.4.17 Association of Place of living at the time of education of internet utilizing male and female agricultural students with their internet utilization N=113 S. Category Male students (N=85) Female students (N=28) No. Low Medium High Total Low Medium High Total (i) Non 2 4 4 10 1 2 2 5 hosteller (1.76) (6.82) (1.41) (11.76) (0.71) (3.75) (0.54) (17.86) (ii) Hosteller 13 54 8 75 3 19 1 23 (13.24) (51.18) (10.59) (88.24) (3.29) (17.25) (2.46) (82.14) Total 15 58 12 85 4 21 3 28 (17.65) (68.23) (14.12) (100.00) (14.29) (75.00) (10.71) (100.00) 2 X = 6.74* X2 = 6.00* C value = 0.2710 C value = 0.4202
X2 –tab value at 5 per cent level of significance = 5.991 d.f. = 2 * significant at 5 per cent level of significance Figures in parenthesis indicate percentage
Table 5.4.18 : Association of wish to migrate abroad of education of internet utilizing male and female agricultural students with their internet utilization N =113
S. No. Category Male students (N=85) Female students (N=28) Low Medium High Total Low Medium High Total (i) No wish to go abroad 9 9 4 22 1 12 0 13 (3.88) (15.01) (3.11) (25.88) (1.86) (9.75) (1.39) (46.43) (ii) Wish to go abroad for study 2 6 2 10 1 8 1 10 (1.76) (6.82) (1.41) (11.76) (1.43) (7.50) (1.07) (35.71) (iii) Wish to go abroad for settling 4 43 6 53 2 1 2 5 (9.35) (36.16) (7.48) (62.35) (0.71) (3.75) (0.54) (17.86) Total 15 58 12 85 4 21 3 28 (17.65) (68.23) (14.12) (100.00) (14.29) (75.00) (10.71) (100.00) X2 = 14.44** X2 = 10.81* C value = 0.3810 C value = 0.5277
X2 –tab value at 1 per cent level of significance = 13.277 d.f. = 4 X2 –tab value at 5 per cent level of significance = 9.488 ** significant at 1 per cent level of significance * significant at 5 per cent level of significance Figures in parenthesis indicate percentage
Table 5.4.19 : Association of wish to get higher academic degree of internet utilizing male and female agricultural students with their internet utilization N=113
S. No. Category Male students (N=85) Female students (N=28) Low Medium High Total Low Medium High Total (i) Willing to have next degree 12 43 6 61 3 14 1 18 (10.76) (41.62) (8.61) (71.76) (2.57) (13.50) (1.93) (64.29) (ii) Not willing to have next degree 3 15 6 24 1 7 2 10 (4.24) (16.38) (3.39) (28.24) (1.43) (7.50) (1.07) (35.71) Total 15 58 12 85 4 21 3 28 (17.65) (68.23) (14.12) (100.00) (14.29) (75.00) (10.71) (100.00) X2 = 3.46 NS X2 = 1.50 NS
X2 –tab value at 5 per cent level of significance = 5.991 d.f. = 2 NS = Non significant Figures in parenthesis indicate percentage