Compare and Contrast Inductive and Deductive Research
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Jackson: Choosing a Methodology: Philosophical Underpinning
JACKSON: CHOOSING A METHODOLOGY: PHILOSOPHICAL UNDERPINNING Choosing a Methodology: Philosophical Practitioner Research Underpinning In Higher Education Copyright © 2013 University of Cumbria Vol 7 (1) pages 49-62 Elizabeth Jackson University of Cumbria [email protected] Abstract As a university lecturer, I find that a frequent question raised by Masters students concerns the methodology chosen for research and the rationale required in dissertations. This paper unpicks some of the philosophical coherence that can inform choices to be made regarding methodology and a well-thought out rationale that can add to the rigour of a research project. It considers the conceptual framework for research including the ontological and epistemological perspectives that are pertinent in choosing a methodology and subsequently the methods to be used. The discussion is exemplified using a concrete example of a research project in order to contextualise theory within practice. Key words Ontology; epistemology; positionality; relationality; methodology; method. Introduction This paper arises from work with students writing Masters dissertations who frequently express confusion and doubt about how appropriate methodology is chosen for research. It will be argued here that consideration of philosophical underpinning can be crucial for both shaping research design and for explaining approaches taken in order to support credibility of research outcomes. It is beneficial, within the unique context of the research, for the researcher to carefully -
Qualitative Research
Encyclopedia of Leadership ______________________________________________________________________________ Edited by G. Goethals, G. Sorenson, J. MacGregor Copyright © 2004 SAGE Publications London, Thousand Oaks CA, New Delhi www.sagepublications.com A R T I C L E Qualitative Research Sonia Ospina Robert F. Wagner Graduate School of Public Service New York University QUALITATIVE RESEARCH Leadership scholars seeking to answer questions about culture and meaning have found experimental and quantitative methods to be insufficient on their own in explaining the phenomenon they wish to study. As a result, qualitative research has gained momentum as a mode of inquiry. This trend has roots in the development of the New Leadership School, (Conger, 1999; Hunt, 1999), on the recent emergence of an approach to leadership that views it as a relational phenomenon (Fletcher, 2002), and on the increased recognition of the strengths of qualitative inquiry generally. Shank (2002) defines qualitative research as “a form of systematic empirical inquiry into meaning” (p. 5). By systematic he means “planned, ordered and public”, following rules agreed upon by members of the qualitative research community. By empirical, he means that this type of inquiry is grounded in the world of experience. Inquiry into meaning says researchers try to understand how others make sense of their experience. Denzin and Lincoln (2000) claim that qualitative research involves an interpretive and naturalistic approach: “This means that qualitative researchers study things in their -
Discussion Notes for Aristotle's Politics
Sean Hannan Classics of Social & Political Thought I Autumn 2014 Discussion Notes for Aristotle’s Politics BOOK I 1. Introducing Aristotle a. Aristotle was born around 384 BCE (in Stagira, far north of Athens but still a ‘Greek’ city) and died around 322 BCE, so he lived into his early sixties. b. That means he was born about fifteen years after the trial and execution of Socrates. He would have been approximately 45 years younger than Plato, under whom he was eventually sent to study at the Academy in Athens. c. Aristotle stayed at the Academy for twenty years, eventually becoming a teacher there himself. When Plato died in 347 BCE, though, the leadership of the school passed on not to Aristotle, but to Plato’s nephew Speusippus. (As in the Republic, the stubborn reality of Plato’s family connections loomed large.) d. After living in Asia Minor from 347-343 BCE, Aristotle was invited by King Philip of Macedon to serve as the tutor for Philip’s son Alexander (yes, the Great). Aristotle taught Alexander for eight years, then returned to Athens in 335 BCE. There he founded his own school, the Lyceum. i. Aside: We should remember that these schools had substantial afterlives, not simply as ideas in texts, but as living sites of intellectual energy and exchange. The Academy lasted from 387 BCE until 83 BCE, then was re-founded as a ‘Neo-Platonic’ school in 410 CE. It was finally closed by Justinian in 529 CE. (Platonic philosophy was still being taught at Athens from 83 BCE through 410 CE, though it was not disseminated through a formalized Academy.) The Lyceum lasted from 334 BCE until 86 BCE, when it was abandoned as the Romans sacked Athens. -
Uses for Census Data in Market Research
Uses for Census Data in Market Research MRS Presentation 4 July 2011 Andrew Zelin, Director, Sampling & RMC, Ipsos MORI Why Census Data is so critical to us Use of Census Data underlies almost all of our quantitative work activities and projects Needed to ensure that: – Samples are balanced and representative – ie Sampling; – Results derived from samples reflect that of target population – ie Weighting; – Understanding how demographic and geographic factors affect the findings from surveys – ie Analysis. How would we do our jobs without the use of Census Data? Our work withoutCensusData Our work Regional Assembly What I will cover Introduction, overview and why Census Data is so critical; Census data for sampling; Census data for survey weighting; Census data for statistical analysis; Use of SARs; The future (eg use of “hypercubes”); Our work without Census Data / use of alternatives; Conclusions Census Data for Sampling For Random (pre-selected) Samples: – Need to define stratum sample sizes and sampling fractions; – Need to define cluster size, esp. if PPS – (Need to define stratum / cluster) membership; For any type of Sample: – To balance samples across demographics that cannot be included as quota controls or stratification variables – To determine number of sample points by geography – To create accurate booster samples (eg young people / ethnic groups) Census Data for Sampling For Quota (non-probability) Samples: – To set appropriate quotas (based on demographics); Data are used here at very localised level – ie Census Outputs Census Data for Sampling Census Data for Survey Weighting To ensure that the sample profile balances the population profile Census Data are needed to tell you what the population profile is ….and hence provide accurate weights ….and hence provide an accurate measure of the design effect and the true level of statistical reliability / confidence intervals on your survey measures But also pre-weighting, for interviewer field dept. -
A Feminist Epistemological Framework: Preventing Knowledge Distortions in Scientific Inquiry
Claremont Colleges Scholarship @ Claremont Scripps Senior Theses Scripps Student Scholarship 2019 A Feminist Epistemological Framework: Preventing Knowledge Distortions in Scientific Inquiry Karina Bucciarelli Follow this and additional works at: https://scholarship.claremont.edu/scripps_theses Part of the Epistemology Commons, Feminist Philosophy Commons, and the Philosophy of Science Commons Recommended Citation Bucciarelli, Karina, "A Feminist Epistemological Framework: Preventing Knowledge Distortions in Scientific Inquiry" (2019). Scripps Senior Theses. 1365. https://scholarship.claremont.edu/scripps_theses/1365 This Open Access Senior Thesis is brought to you for free and open access by the Scripps Student Scholarship at Scholarship @ Claremont. It has been accepted for inclusion in Scripps Senior Theses by an authorized administrator of Scholarship @ Claremont. For more information, please contact [email protected]. A FEMINIST EPISTEMOLOGICAL FRAMEWORK: PREVENTING KNOWLEDGE DISTORTIONS IN SCIENTIFIC INQUIRY by KARINA MARTINS BUCCIARELLI SUBMITTED TO SCRIPPS COLLEGE IN PARTIAL FULFILLMENT OF THE DEGREE OF BACHELOR OF ARTS PROFESSOR SUSAN CASTAGNETTO PROFESSOR RIMA BASU APRIL 26, 2019 Bucciarelli 2 Acknowledgements First off, I would like to thank my wonderful family for supporting me every step of the way. Mamãe e Papai, obrigada pelo amor e carinho, mil telefonemas, conversas e risadas. Obrigada por não só proporcionar essa educação incrível, mas também me dar um exemplo de como viver. Rafa, thanks for the jokes, the editing help and the spontaneous phone calls. Bela, thank you for the endless time you give to me, for your patience and for your support (even through WhatsApp audios). To my dear friends, thank you for the late study nights, the wild dance parties, the laughs and the endless support. -
Objectivity in the Feminist Philosophy of Science
OBJECTIVITY IN THE FEMINIST PHILOSOPHY OF SCIENCE DISSERTATION Presented in Partial Fulfillment of the Requisites for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Karen Cordrick Haely, M.A. ***** The Ohio State University 2003 Dissertation Committee: Approved by Professor Louise M. Antony, Adviser Professor Donald C. Hubin _______________________ Professor George Pappas Adviser Philosophy Graduate Program ABSTRACT According to a familiar though naïve conception, science is a rigorously neutral enterprise, free from social and cultural influence, but more sophisticated philosophical views about science have revealed that cultural and personal interests and values are ubiquitous in scientific practice, and thus ought not be ignored when attempting to understand, describe and prescribe proper behavior for the practice of science. Indeed, many theorists have argued that cultural and personal interests and values must be present in science (and knowledge gathering in general) in order to make sense of the world. The concept of objectivity has been utilized in the philosophy of science (as well as in epistemology) as a way to discuss and explore the various types of social and cultural influence that operate in science. The concept has also served as the focus of debates about just how much neutrality we can or should expect in science. This thesis examines feminist ideas regarding how to revise and enrich the concept of objectivity, and how these suggestions help achieve both feminist and scientific goals. Feminists offer us warnings about “idealized” concepts of objectivity, and suggest that power can play a crucial role in determining which research programs get labeled “objective”. -
CORRELATION COEFFICIENTS Ice Cream and Crimedistribute Difficulty Scale ☺ ☺ (Moderately Hard)Or
5 COMPUTING CORRELATION COEFFICIENTS Ice Cream and Crimedistribute Difficulty Scale ☺ ☺ (moderately hard)or WHAT YOU WILLpost, LEARN IN THIS CHAPTER • Understanding what correlations are and how they work • Computing a simple correlation coefficient • Interpretingcopy, the value of the correlation coefficient • Understanding what other types of correlations exist and when they notshould be used Do WHAT ARE CORRELATIONS ALL ABOUT? Measures of central tendency and measures of variability are not the only descrip- tive statistics that we are interested in using to get a picture of what a set of scores 76 Copyright ©2020 by SAGE Publications, Inc. This work may not be reproduced or distributed in any form or by any means without express written permission of the publisher. Chapter 5 ■ Computing Correlation Coefficients 77 looks like. You have already learned that knowing the values of the one most repre- sentative score (central tendency) and a measure of spread or dispersion (variability) is critical for describing the characteristics of a distribution. However, sometimes we are as interested in the relationship between variables—or, to be more precise, how the value of one variable changes when the value of another variable changes. The way we express this interest is through the computation of a simple correlation coefficient. For example, what’s the relationship between age and strength? Income and years of education? Memory skills and amount of drug use? Your political attitudes and the attitudes of your parents? A correlation coefficient is a numerical index that reflects the relationship or asso- ciation between two variables. The value of this descriptive statistic ranges between −1.00 and +1.00. -
A Pragmatic Stylistic Framework for Text Analysis
International Journal of Education ISSN 1948-5476 2015, Vol. 7, No. 1 A Pragmatic Stylistic Framework for Text Analysis Ibrahim Abushihab1,* 1English Department, Alzaytoonah University of Jordan, Jordan *Correspondence: English Department, Alzaytoonah University of Jordan, Jordan. E-mail: [email protected] Received: September 16, 2014 Accepted: January 16, 2015 Published: January 27, 2015 doi:10.5296/ije.v7i1.7015 URL: http://dx.doi.org/10.5296/ije.v7i1.7015 Abstract The paper focuses on the identification and analysis of a short story according to the principles of pragmatic stylistics and discourse analysis. The focus on text analysis and pragmatic stylistics is essential to text studies, comprehension of the message of a text and conveying the intention of the producer of the text. The paper also presents a set of standards of textuality and criteria from pragmatic stylistics to text analysis. Analyzing a text according to principles of pragmatic stylistics means approaching the text’s meaning and the intention of the producer. Keywords: Discourse analysis, Pragmatic stylistics Textuality, Fictional story and Stylistics 110 www.macrothink.org/ije International Journal of Education ISSN 1948-5476 2015, Vol. 7, No. 1 1. Introduction Discourse Analysis is concerned with the study of the relation between language and its use in context. Harris (1952) was interested in studying the text and its social situation. His paper “Discourse Analysis” was a far cry from the discourse analysis we are studying nowadays. The need for analyzing a text with more comprehensive understanding has given the focus on the emergence of pragmatics. Pragmatics focuses on the communicative use of language conceived as intentional human action. -
Mathematics: Analysis and Approaches First Assessments for SL and HL—2021
International Baccalaureate Diploma Programme Subject Brief Mathematics: analysis and approaches First assessments for SL and HL—2021 The Diploma Programme (DP) is a rigorous pre-university course of study designed for students in the 16 to 19 age range. It is a broad-based two-year course that aims to encourage students to be knowledgeable and inquiring, but also caring and compassionate. There is a strong emphasis on encouraging students to develop intercultural understanding, open-mindedness, and the attitudes necessary for them LOMA PROGRA IP MM to respect and evaluate a range of points of view. B D E I DIES IN LANGUA STU GE ND LITERATURE The course is presented as six academic areas enclosing a central core. Students study A A IN E E N D N DG two modern languages (or a modern language and a classical language), a humanities G E D IV A O L E I W X S ID U IT O T O G E U or social science subject, an experimental science, mathematics and one of the creative IS N N C N K ES TO T I A U CH E D E A A A L F C T L Q O H E S O R I I C P N D arts. Instead of an arts subject, students can choose two subjects from another area. P G E A Y S A E R S It is this comprehensive range of subjects that makes the Diploma Programme a O S E A Y H T demanding course of study designed to prepare students effectively for university entrance. -
Notes for Our Seminar: Objectivity and Subjectivity
Notes for our seminar: Objectivity and Subjectivity B.M. December 14, 2019 Contents I A preview and overview of the topics we may cover 2 1 The nature of our seminar-course 3 II Readings and Notes for the sessions of Sept 11, Oct 2, Oct 30, and part of Dec 4 13 2 Readings for the September 11 session 13 2.1 Excerpt from [9] . 14 3 Some notes for Sep 11: Subjectivity, Universal Subjectivity, Objectivity 15 3.1 Objective . 16 4 Readings for October 2: 25 5 Notes for Oct 21 session: Objectivity and Subjectivity in Mathematics 36 5.1 What is the number `A thousand and one'?....................... 37 5.2 Plato ............................................ 38 5.3 `Tower Pound' definition ................................ 39 1 5.4 J.S. Mill .......................................... 39 5.5 Georg Cantor: ...................................... 40 5.6 Gottlob Frege (∼ 1900) ................................ 41 5.7 Foundations::: or Constitutions ............................. 43 5.8 David Hilbert ....................................... 43 5.9 L.E.J. Brouwer ...................................... 46 5.10 The simple phrase \and so on::: "............................ 48 6 Readings for October 30, 2019: (Shades of Objectivity and Subjectivity in Epistemology, Probability, and Physics) 50 7 Notes for October 30, 2019:(Shades of Objectivity and Subjectivity in Epistemology, Probability, and Physics) 51 8 Subjectivity and Objectivity in Statistics: `Educating your beliefs' versus `Test- ing your Hypotheses' 55 8.1 Predesignation versus the self-corrective nature of inductive reasoning . 57 8.2 Priors as `Meta-probabilities' . 59 8.3 Back to our three steps . 61 8.4 A numerical example and a question . 62 9 Issues of Subjectivity and Objectivity in Physics 63 10 Consequentialism of Meaning|notes for part of session of December 4 65 11 Dealing with nonexistent objects 69 2 Part I A preview and overview of the topics we may cover 1 The nature of our seminar-course Phil273O (Objectivity and Subjectivity) will be the fourth seminar- course I've taught with Amartya Sen and Eric Maskin. -
Scientific Discovery in the Era of Big Data: More Than the Scientific Method
Scientific Discovery in the Era of Big Data: More than the Scientific Method A RENCI WHITE PAPER Vol. 3, No. 6, November 2015 Scientific Discovery in the Era of Big Data: More than the Scientific Method Authors Charles P. Schmitt, Director of Informatics and Chief Technical Officer Steven Cox, Cyberinfrastructure Engagement Lead Karamarie Fecho, Medical and Scientific Writer Ray Idaszak, Director of Collaborative Environments Howard Lander, Senior Research Software Developer Arcot Rajasekar, Chief Domain Scientist for Data Grid Technologies Sidharth Thakur, Senior Research Data Software Developer Renaissance Computing Institute University of North Carolina at Chapel Hill Chapel Hill, NC, USA 919-445-9640 RENCI White Paper Series, Vol. 3, No. 6 1 AT A GLANCE • Scientific discovery has long been guided by the scientific method, which is considered to be the “gold standard” in science. • The era of “big data” is increasingly driving the adoption of approaches to scientific discovery that either do not conform to or radically differ from the scientific method. Examples include the exploratory analysis of unstructured data sets, data mining, computer modeling, interactive simulation and virtual reality, scientific workflows, and widespread digital dissemination and adjudication of findings through means that are not restricted to traditional scientific publication and presentation. • While the scientific method remains an important approach to knowledge discovery in science, a holistic approach that encompasses new data-driven approaches is needed, and this will necessitate greater attention to the development of methods and infrastructure to integrate approaches. • New approaches to knowledge discovery will bring new challenges, however, including the risk of data deluge, loss of historical information, propagation of “false” knowledge, reliance on automation and analysis over inquiry and inference, and outdated scientific training models. -
Mixed Methods Research Approaches:Warrant Consideration Phenomena in Themethodological Thirdmovementon the Humanities Sciences
IOSR Journal Of Humanities And Social Science (IOSR-JHSS) Volume 20, Issue 11, Ver. II (Nov. 2015) PP 21-28 e-ISSN: 2279-0837, p-ISSN: 2279-0845. www.iosrjournals.org Mixed Methods Research Approaches:Warrant Consideration Phenomena in theMethodological ThirdMovementon the Humanities Sciences Kamal koohi Assistant Professor of Institute ofSocial Research, University of Tabriz Abstract:Today, Dramatic changes and transformations has happened in theories sociology similar to other areas.We have seen in recent sociological theories emerging paradigms of integrated. Social research methods are not exempt from this rule. Simplification of complex social problems cannot be easily by a deterministic selection approach to both qualitative and quantitative methods. Therefore, since the condition of today's postmodern discourse of diversity technique, Selection mixed research approach is a methodological necessity in the social sciences. Today, the simultaneous use of both quantitative and qualitative methods is justified.As mentioned, the mixed researchapproach qualitative and quantitative methods are combined by each other.The main objective of this paper is to introduce integrated research approach and review of advantage and disadvantage mentioned method. It is expected that using this approach contribute to overcome the shortcomings of positivistic hard and soft humanistic Blumer. Because the main idea of mixed researchapproach is to combine of qualitative and quantitative approaches,more appropriate and comprehensive understanding is obtained of topic. Keywords:Mixed ResearchApproach, Third Movement ofMethodological, Qualitative Method and Quantitative Method. I. Introduction In the present age, significant changes has occurred in sociological theory and paradigm as a researcher thought and action guidance ( the entire process of research ).