IST-Africa 2012 Conference Proceedings Paul Cunningham and Miriam Cunningham (Eds) IIMC International Information Management Corporation, 2012 ISBN: 978-1-905824-34-2 Smartphone Application Usage Amongst Students at a South African University Walter UYS 1, Aadilah MIA, Gary Jeffrey JANSEN, Haythem VAN DER SCHYFF, Michael Andre JOSIAS, Michelle KHUSU, Muzaffer GIERDIEN, Natacha Andrea LEUKES, Sulungeka FALTEIN, Tejas GIHWALA, Tracey-Lee THEUNISSEN, Yaseen SAMSODIEN 1Department of Information Systems, University of the Western Cape, Cape Town, 8000, South Africa Tel: +27 21 9593680, Fax: + 27 86 6093930, Email: [email protected] Abstract: This study assesses the usage of smartphone applications and specifically social networking applications (SNS) amongst smartphone users, due to the perceived high-level of usage amongst University Students. Questionnaires were derived from the literature, and used to assess the frequency and intensity of application usage. The data was analysed looking at key applications and frequency/intensity of usage. It was found that the students that were questioned at this university, spend an average of five hours per day on their smartphones interacting with others via SNS, and remain online for about 16 hours per day. The students that were sampled preferred to communicate using SNS. These students appear to use sms for close friends only, and phonecalls for loved ones and family; possibly due to the high cost of sms’ and phonecalls in South Africa compared to the low cost of SNS. Students use SNS predominantly for Facebook, Facebook chat and Blackberry Messenger (BB users) in order to update their profiles, chat with friends, and look at their friends’ profiles and statuses. Future studies should investigate what motivates students to spend such an inordinate amount of time with SNS apps, and which Apps are long term favourites in the race for market leading SNS App. Keywords: Smartphones, Applications, Mobile Social Networking, M-Education, Smartphone Usage. 1. Introduction The capability and performance of mobile phones have improved considerably since their first introduction, and are no longer simple voice centric devices. They now provide mobile computing power equivalent to that of personal computers of a few years ago and can be used for several purposes. Advanced mobile phones now have the capabilities of a telephone, camera (still and video), music player and voice recorder, personal digital assistant [19]. They are approaching the level of complexity of computers for mobile applications with applications such as mobile word processing, spreadsheets email and internet. These mobile phones have become so interactive that they are referred to as Smartphones [16]. A number of studies have been done on the use of mobile and smartphones. These studies typically looked at usage patterns on mobile devices [21,22], data traffic, battery life, interactions on servers [22] and interactions with mobile applications [33,34]. Reasons given in the literature for examining smartphone usage are; that little is known about how people use these devices; such as how often a user interacts with the phone, how Copyright © 2012 The authors www.IST-Africa.org/Conference2012 Page 1 of 11 long such interactions last, how users interact with such applications, and how their attention is spread amongst them [22]. Other studies claim the need for understanding smartphone usage to guide strategic research and product development around issues why users adopt applications, why they use them, HCI factors, user satisfaction and change to competing offerings [34]. Social and Psychological factors such as the blurred distinction between work and private time with mobile devices, intrusion of mobile devices in social life [27], even claiming smartphone addiction [37], dependency [24] and dysfunctional behaviour [29] have all been examined. Little is however understood about which applications end-users use when they are spending time on their smartphones. This study aims to provide a snapshot from a student’s life perspective. 2. Objectives This preliminary study examines the usage of smartphones and applications amongst students at a South African University. This research attempts to understand the perceived high-level of usage of mobile social networking applications amongst university students by looking at the intensity of usage, and which smartphones and applications they use. Of specific interest is the level of interaction with social networking applications (SNS), comparing the intensity of interactions between voice, sms, SNS, Face to Face (F2F) interactions, and its correlations with application usage. The results will be compared to two other similar studies done in Australia [37] and Europe [35]. Based on the perceived level of interactions of students with their smartphones, it is hypothesized that there should be no difference to the intensity of usage as benchmarked by these prior studies. 3. Methodology In order to better understand what students are using their smartphones for, a questionnaire was developed to assess their demographics, smartphone details, relative ranking of apps, and intensity of usage. 3.1 Data Collected Demographics, including information such as year of study, age, course major, language and marital status was collected. Questions were formulated to determine the make and model of smartphone as well as the network providers. Operating systems were established from the make and model of the phone. Users were asked to rank the level of usage of SNS applications on a scale of 1 to 11, as well as which other apps they use on a regular basis, ranked from 1 to 10. These rankings were then inverted to establish intensity. To determine the general usage of the phone, the number of incoming/outgoing calls were queried, as well as the number of incoming/outgoing sms’. The average time spent on a phonecall was also asked for. To determine the intensity of SNS usage, the number of SNS interactions per day were requested, the average time spent on SNS interactions, as well as how many people were interacted with together with the number of SNS friends/contacts. As a comparison, the users were also asked how many Face to Face (F2F) interactions they have on a daily basis, and the average time spent on these interactions. In order to determine the average monthly cellphone expenditure, the average monthly income as well as monthly cellphone costs was requested, as well as the source of income to pay these bills. Copyright © 2012 The authors www.IST-Africa.org/Conference2012 Page 2 of 11 3.2 Questionnaire Administration The questionnaire was piloted in a class situation by all the students of a 3rd year course on research methods, where one student was the interviewer, and another the interviewee. The questionnaire was then expanded based on the class feedback to include other Apps and questions that were identified in the class. For the final study, students who use or own a smartphones on campus were randomly surveyed. A prize was offered for their participation, and this was found to be a useful incentive to encourage participation. Sixty questionnaires were administered, and three were discarded due to incomplete information. Results were captured, additional data re-requested, prizes drawn and handed over, data analysed, and further research performed by the listed authors, who voluntarily participated in the process. 3.3 Study Limitations The sample population for this study was specifically students on campus using smartphones. Only a small number of students were surveyed (60 out of a possible 7000 on campus), therefore the following limitations should be considered. Due to the low number of responses (n=60 with 57 valid responses), non-parametric statistics was used to analyse the results. Also, a number of the variables are based on self- reported figures, and may be skewed due to the users not being clear on the question, on their actual usage, or may be in denial about their level of usage or wish to conceal what they perceive to be sensitive or personal information such as income or cell expenditure. Although the sample is not statistically representative of the student population, a good representation of students from different departments, as well as gender, race and language were targeted in the study. Users were asked to provide a self-report on their usage and ranking of Apps, which may not be as accurate as using metric software, but should provide sufficient causal data for examination. As only smartphones were surveyed, the operating systems identified in this survey are only indicative of smartphones used on this campus, and should not be considered representative of all phone operating systems. It should also be noted that smartphone apps are under continuous development, and a number of new apps such as Viber etc. have entered the market since this study was done. 3.4 Limitations i.t.o. Examples For illustrative purposes and in order to compare the findings to usage norms, this study is compared with that of Verkasalo [35] and Walsh, White & Young [37]. The population for the Verkasalo study [35] were users from North-America, Europe and selected Asian countries and was conducted between 2008-2009. Fifty-six percent (56%) of the users were under the age of 30 and 86% paid their own phone bills. The Australian study [37] sampled 946 participants aged between 15 to 24 years from private and public schools, university campuses, youth organisations, and snowballing methods between 2005-2006. These populations are significantly different to this study to readily make comparisons, however it is hoped to illustrate some of the differences on usage from a Southern African students perspective. Because of the disparities amongst measures for usage and differences in samples, it is difficult to compare the frequency and intensity of usage of apps with those of [35,37], however attempts were made to standardise the times for illustrative purposes only. Copyright © 2012 The authors www.IST-Africa.org/Conference2012 Page 3 of 11 4.