Friday, November 13, 2015

The Benefits of Research are Lumpy



Edwin Mansfield, who studied the social returns on government-funded research found that the return to society on government funding in basic science was 28% to 40% a year.  A string of subsequent studies through 2014 have confirmed that basic science funding yields high returns, not just in the U.S. but also in the U.K., Europe and Japan.

A McKinsey study found that Internet-related expenditures accounted in 2013 for about 4.3% of the U.S. GDP, or about $721 billion a year. Across 13 of the largest economies, the Internet adds about $2.2 trillion dollars a year to GDP.

What is the investment to develop internet? The three most cited contributors responsible for internet are the invention of the TCP/IP protocol (funded by DARPA), the invention of the World Wide Web (at CERN), and the creation of the Mosaic Web browser (at NCSA/University of Illinois). DARPA’s budgets from its formation in 1958 through 2015 come to about $121 billion after adjusting for inflation. The expenses of CERN, whose focus is  particle physics, total roughly $50.5 billion. To estimate NCSA budget,  a gross overestimate is  the entire amount spent by the U.S. federal government on all science and research (including health, climate, energy, and all other fields except NASA) since 1962, and it comes to  comes to $372 billion.

So, even if CERN never found the Higgs boson, the National Institutes of Health never saved a child’s life, and all the knowledge we have accumulated from science in the past 50 years was utterly worthless, the discovery of scientific principles behind internet and its development would pay for the tax payers' many times over.  That is how the benefits of research are lumpy. They cannot be calculated for every research paper and every research conference and every research laboratory.


Monday, November 2, 2015

Arguments - Logic Book Style - Marianne Talbot - Oxford University Class Lectures - Videos



Deduction

Induction




The Nature of Arguments - First Lecture
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Different Types of Arguments - Marianne Talbot
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What is a Good Argument? Validity and Truth - Marianne Talbot
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Lecture 5 - Evaluating Arguments - Part 1


Lecture 6 - Evaluating Arguments - Part 2

Saturday, October 24, 2015

Sunday, October 18, 2015

Interpretive Research in Information Systems

Philosophical basis of interpretive research


The ethnographic research tradition in anthropology is a valuable starting point for a consideration of the philosophical basis of interpretive case studies.

What is called data in interpretive studies are  constructions of  people of what they and their
compatriots are up to.


Van Maanen (1979), writing in the tradition of organizational ethnography, calls the interviewee's
constructions first-order data and the constructions of the researcher second-order concepts.

Second-order concepts rely on good theory and insightful analysis, and mere collection of in-depth case study data does not provide these concepts in itself. Examples of second-order concepts
in the IS literature, derived from interpretive case studies, include the 'automate' concept from the work of Zuboff (1988), and the concept of 'technological frames' in Orlikowski & Gash (1994).

A second feature of the anthropological tradition is its concern with 'thick description'. The ethnographer is faced with a multiplicity of complex conceptual structures, many of them superimposed upon or knotted into one another and which must be first grasped and then rendered
intelligible to others.

 An IS researcher can only access the subtleties of changing interpretation by the use of approaches based on 'thick' description.

The goal is not to generate truth or social laws, and this interpretive approach can be
clearly distinguished from the positivist tradition. This should not be taken to imply that interpretive work is not generalizable, although the nature of such generalizations is different in the two traditions. This point will be considered in some detail later.


In 'nonpositivism' facts and values are intertwined and hard to disentangle, and both are involved in
scientific knowledge; and 'normativism' which takes the view that scientific knowledge is ideological and inevitably conducive to particular sets of social ends. Either of these  two positions is open for the interpretive researcher to adopt.

 'internal realism' views reality-for-us as an intersubjective construction of the shared human cognitive apparatus, and 'subjective idealism' where each person is considered to construct
his or her own reality. The usual ontological stance for an interpretive IS researcher would involve one of these  two positions, particularly with regard to the human interpretations and meanings associated with computer systems.

 Mingers (1984) identified the existence of at least four substantively
different strands of thought in nonpositivistic research: phenomenology, ethnomethodology,
the philosophy of language, and hermeneutics.

For example, Zuboff (1988) drew on phenomenology, Suchman (1987) on ethnomethodology,
and Boland & Day (1989) and Lee (1994) on hermeneutics.


Reference

Interpretive case studies in IS research: nature and method
G WALSHAM
Department of Management Science, The Management School, Lancaster University, Lancaster LAI 4YX, UK
Eur. J. Inf. Systs. (199S) 4,74-81



Sunday, September 6, 2015

Ethics in Research




Research Ethics - Preview Google Book

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Misconduct in Research
Dr, Regina Smith,
University of Georgia Uploaded Video

Updated  6 Sep 2015
First published 22 June 2013

Thursday, April 2, 2015

What is a Research Thesis?




What is a thesis?


A thesis is 'a proposition to be discussed and proved or to be maintained against objections' (Oxford dictionary 2004). The whole thesis needs to be focused around one major idea for which you provide evidence and can defend in discussion with other scholars.

http://resource.unisa.edu.au/mod/book/view.php?id=10112&chapterid=4106

Actual entry in the Concise Oxford Dictionary, 1982

Proposition to be maintained or proved;   Dissertation  esp. by candidate for degree

Sunday, January 4, 2015

Writing a Successful Thesis or Dissertation - Lunenburg - Irby - Book Information


Google Book Preview facility
https://books.google.co.in/books?id=CkpOAwAAQBAJ&printsec=frontcover#v=onepage&q&f=false



Writing a Successful Thesis or Dissertation: Tips and Strategies for Students in the Social and Behavioral Sciences



Fred C. Lunenburg, Beverly J. Irby
Corwin Press, Dec 10, 2007 - 352 pages


The book is a comprehensive manual and offers direction for every step of the thesis or dissertation process, from choosing an appropriate topic to adapting the finished work for publication.


Table of Contents

Preface
About the Authors


Part I. Getting Started
1. Selecting a Suitable Topic
Sources of Topics
Criteria for Topic Selection
Summary

2. Selecting a Chair and Committee
Criteria to Consider in Selecting a Chair
Composition and Role of the Committee
Research Prospective Committee Members
The Desirable Student
Summary


Part II. What You Need to Know

3. Quantitative Research Designs
Descriptive Research
Correlational Research
Causal-Comparative Research
Quasi-Experimental Research
Experimental Research
Theory Development
Summary

4. Basic Statistics
Descriptive Statistics
Inferential Statistics
Summary

5. Qualitative Research Designs
Phenomenological Research
Case Study Research
Ethnographic Research
Grounded Theory Research
Mixed Method Research
Summary


Part III. The Dissertation Chapters
6. Writing the Introduction Chapter
Background of the Study
Statement of the Problem
Purpose of the Study
Significance of the Study
Definition of Terms
Theoretical Framework
Models
Research Questions (or Hypotheses)
Limitations
Delimitations
Assumptions
Organization of the Study
Summary

7. Writing the Literature Review Chapter
Searching the Literature
Writing the Literature Review
Synthesizing the Literature
Summary

8. Writing the Methodology Chapter
Introduction
Selection of Participants
Instrumentation
Data Collection
Data Analysis
Summary
Conclusion

9. Writing the Results Chapter
Introduction
Descriptive Statistics
Testing the Research Questions (Hypotheses)
Additional Analyses
Summary
Conclusion
10. Writing the Discussion Chapter
Summary
Discussion
Implications for Practice
Recommendations for Further Research
Conclusions
Summary

Part IV. The Defense and Afterward
11. The Proposal and Final Defense
Prepare a Well-Written Document
Know the Format
Prepare Your Presentation
Practice Your Presentation
Anticipate Questions
Final Oral Defense
Tips on How to Avoid Common Mistakes
Summary

12. Publishing Your Dissertation
Presentations
Job Interview
Academic Journals
Books
Chapters in Books
Popular Press
Internet Publishing
Desktop Publishing
Planning the Writing Process
Summary


Appendix A: Initial Letter to Participants
Appendix B: First Follow-up Letter to Participants
Appendix C: Second Follow-up Letter to Participants
Appendix D: Dissertation Proposal Outline (Correlational)
Appendix E: Dissertation Proposal Outline (Analysis of Variance)
Appendix F: Dissertation Proposal Outline (Multivariate Analysis of Variance)
Appendix G: Dissertation Proposal Outline (Qualitative)
Appendix H: The Qualitative Research Critique
Appendix I: Agreement: Guidelines for Chairing a Dissertation
Appendix J: Checklist for Dissertation Quality
References
Index