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The research paradigms: Positivism

EDU 5 IMAGEI introduced the series of articles on Research Paradigms by listing all the different paradigms, also called philosophical perspectives, philosophical epochs or, sometimes also called the “isms”. This articles deals with the third paradigm, namely Positivism.

The positivist paradigm of exploring social reality is based on the idea that one can best gain an understanding of human behaviour through observation and reason. Stated differently, only objective, observable facts can be the basis for science. According to the positivist paradigm true knowledge is based on experience of senses and can be obtained by observation and experiment. Positivist thinkers lean strongly on determinism, empiricism, parsimony and generality.

‘Determinism’ means that events are caused by other circumstances; and hence, understanding such causal links is necessary for prediction and control. ‘Empiricism’ means collection of verifiable empirical evidences in support of theories or hypotheses. Knowledge stems from human experience. Furthermore, the researcher is seen as being independent from the study and follows a deductive approach. The researcher concentrates on facts rather than human interests, making this approach a deductive one. ‘Parsimony’ refers to the explanation of the phenomena in the most efficient way possible. ‘Generality’ is the process of generalising the observation of the particular phenomenon to the world at large.

With these assumptions of science, the ultimate goal is to integrate and systematise findings into a meaningful pattern or theory which is regarded as tentative and not the ultimate truth. Theory is subject to revision or modification as new evidence is found.

Positivist paradigm thus systematises the knowledge generation process with the help of quantification, which is essential to enhance precision in the description of parameters and the discernment of the relationship among them.

An interesting feature of positivism is that it accepts the supernatural and abstract as data for research purposes. However, theological (the supernatural) or metaphysical (the abstract) claims must yield to the positive – that which can be explained in terms of scientific laws.

A positivist approach to knowledge is based on a real and objective interpretation of the data at our disposal. Such knowledge can be transmitted in tangible form – knowledge is often derived from observation. Positivism is a philosophy of knowing, also called epistemology, which believes that only knowledge gained through direct observation is factual and trustworthy. Factual information gathering, for example watching people work, measuring manufactured items, measuring time in athletics, is regarded as objective and therefore also valid.

Observations should be quantifiable so that statistical analysis can be done. Researchers following a positivist approach postulate that there is one objective reality that is observable by a researcher who has little, if any, impact on the object being observed. Positivism implies that there are objective, independent laws of nature to which human life is subjected. It is the purpose of research to discover and describe these objective laws. This view describes society as being made up of structures, concepts, labels and relationships. Proving the existence and impact of such laws require discovery through scientific means.

Positivists believe that knowledge can be “revealed” or “discovered” through the use of the scientific method. The “discovered” knowledge enables us to provide possible explanations of the causes of things that happen in the world. A positivist approach emphasises experimentation, observation, control, measurement, reliability and validity in the processes of research. This implies a quantitative approach.

Positivists argue that the scientific research method produces precise, verifiable, systematic and theoretical answers to the research question or hypothesis. They also suggest that the use of the scientific method provides answers that are neutral and technical and can thus be universalised and generalised to all historical and cultural contexts.

To explain the concept of doing research independent of other people, notably your target group for the research – a researcher following a positivist approach can receive and analyse completed questionnaires from people whom he or she has never met and don’t intend meeting either. All they are interested in are the responses from which objective conclusions can be made.

The advantage of a positivist approach to research is that the researcher can cover a wide range of situations in a short period of time. However, the following disadvantages of positivism should also be borne in mind:

  • Positivism relies on experience as a valid source of knowledge. However, a wide range of basic and important concepts such as cause, time and space are not based on experience.
  • Positivism assumes that all types of processes can be perceived as a certain variation of actions of individuals or relationships between individuals.
  • Adoption of positivism can be criticised for reliance on the status quo. In other words, research findings are only descriptive, thus they lack insight into in-depth issues.

Note: Sources for all the articles on research paradigms will be acknowledged in the book that the writer is writing on Social Science Research. Posted by Dr J.P. Nel

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The research paradigms: Empiricism

EDU 8 IMAGEI introduced the series of articles on Research Paradigms by listing all the different paradigms, also called philosophical perspectives, philosophical epochs or, sometimes also called the “isms”. This articles deals with the second paradigm, namely Empiricism.

Empiricism is the doctrine that all knowledge is derived from sense experience. The philosophy behind empiricism is that all knowledge of matters of fact derives from the experience and that the mind is not furnished with a set of concepts in advance of experience. Experience can be something that people learn from events in which they participated, things that happened to them and observations that they made. Experience can also be “staged” through deliberate and pre-planned experimental arrangements. Sense experience is, therefore, the ultimate source of all our concepts and knowledge.

Empiricists present complimentary lines of thought. First, they develop accounts of how experience provides the information that rationalists cite, insofar as we have it in the first place. As the name and philosophy implies, empiricism means that all evidence of facts and phenomena must be empirical, or empirically based. Evidence should be observable by the senses or extensions of the senses.

Empiricists will at times opt for scepticism as an alternative to rationalism: if experience cannot provide the concepts or knowledge the rationalists cite, then we don’t have them. David Hume,[1] for example, argued that our beliefs are a result of accumulated habits, developed in response to accumulated sense experiences. In his book entitled “Black Brain, White Brain”, Gavin Evans claims that religion is immune to logic. This is a typical empiricist argument. Evans does not understand, or conveniently ignores the value of abstract reasoning as a foundation of deductive reasoning. One wonders if Evans would also deny the possibility that there might be life in other corners of the universe as easily as he dispels the possible existence of a creator of the universe.

Second, empiricists attack the rationalists’ accounts of how reason is the source of concepts or knowledge. Empiricists are of the opinion that knowledge must be deducted or inferred from actual events that people can experience through their senses. The idea that people can learn through reasoning independently of the senses or through intuition are rejected. Stated differently, knowledge can only be derived a posteriori, i.e. through sensory experience. Innate ideas and superiority of knowledge does not exist.

A strong distinction is made between fact (objective) and values (subjective). Sense data is the ultimate objectivity, uncontaminated by value or theory. According to empiricism a person is born with an empty brain, like a clean slate, which is then filled by what he or she learns by experiencing things. Two learning processes take place – the individual experiences a sensation after which she or he reflects on it.

[1] http://www.newworldencyclopedia.org/entry/Empiricism. Accessed on 11/07/2016.

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The research paradigms: Rationalism

EDU 11 IMAGEI introduced the series of articles on Research Paradigms by listing all the different paradigms, also called philosophical perspectives, philosophical epochs or, sometimes also called the “isms”. This articles deals with the first paradigm, namely Rationalism.

Rationalism took shape in modern times as an integral system of epistemological views, as a result of the development of mathematics and the natural sciences. It postulates that truth can be discovered through reason and rational thought. Rationalists assume that the world is deterministic and that cause and effect holds for all events. There are significant ways in which our concepts and knowledge are gained independently of sense experience. They also assume that these can be understood through sufficient understanding and thought. A priori (prior to experience) or rational insight is a source of much knowledge. Sense experience, on the other hand, is seen as being too confusing and tentative.

Rationalists generally develop their view in two ways. First, they argue that there are cases where the content of our concepts or knowledge outstrips the information that sense experience can provide. Second, they construct accounts of how reason in some form or other provides that additional information about the world.

Rationalism adopts at least one of three claims: the intuition/deduction thesis, the innate knowledge thesis or the innate concept thesis.

The intuition/deduction thesis claims that some propositions in a particular subject area are knowable by us by intuition only while others are knowable by being deducted from intuited propositions. Intuition is regarded as a form of rational insight. Intellectually grasping a proposition, we just “see” it to be true in such a way as to form a true, defensible belief in it. Deduction is a process in which we derive conclusions from intuited premises through valid arguments, one in which the conclusion must be true if the premises are true. Intuition and deduction thus provide us with knowledge a priori, which is to say knowledge gained independently of sense experience.

Innate knowledge means having knowledge of some truth is a particular subject area. Like the intuition/deduction thesis, the innate knowledge thesis also asserts the existence of knowledge gained a priori, independently of experience. The difference between the intuition/deduction thesis and the innate knowledge thesis rests in the accompanying understanding of how this a priori knowledge is gained. The intuition/deduction thesis cites intuition and subsequent deductive reasoning. The innate knowledge thesis offers our rational nature. Our innate knowledge is not learned through either sense experience or intuition and deduction. It is just part of our nature. Experiences may trigger a process by which we bring this knowledge to consciousness, but the experiences do not provide us with the knowledge itself. It has in some way been with us all along.

According to the innate concept thesis some of the concepts are not gained from experience – they are part of our rational nature. While sense experiences may trigger a process by which they are brought to consciousness, experience does not provide the concepts or determine the information they contain. The content and strength of the innate concept thesis varies with the concepts claimed to be innate. The more a concept seems to be removed from experience and the mental options we can perform on experience the more plausible it may be claimed to be innate.

The above three thesis are necessary for a paradigm to be rationalist. The indispensability of reason thesis and the superiority of reason thesis may also be adopted by rationalists, although they are not essential. The indispensability of reason thesis claims that the knowledge that we gain by intuition and deduction and the knowledge that are innate to us could not have been gained through sense experience. The superiority of reason thesis claims that the knowledge we gain by intuition and deduction or have innately is superior to any knowledge gained by sense experience.

Rationalism is challenged by positivism, which seeks empirical evidence rather than relying on the perceived unreliability of individual thinking. It is also opposed by empiricism on the question of the source of knowledge and the techniques for verification of knowledge.

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Social research: research paradigms

EDU 9 IMAGEResearch paradigms, also called philosophical perspectives or philosophical epochs, reflect certain assumptions with respect to the nature of the world and how we come to know about it. The philosophical stance informs the methodology and thus provides a context for the process and grounding its logic and criteria and links the choice and use of methods to the desired outcomes. Paradigms are systems of interrelated ontological, epistemological and methodological assumptions.

Epistemology is the study of knowing; essentially it is the study of what knowledge is and how it is possible. Ontology is more concerned about the natural world – how it came to be rather than an analysis of what is. Paradigms act as perspectives that provide a rationale for the research and commit the researcher to particular methods of data collection, observation and interpretation. Paradigms are thus central to research design because they impact both on the nature of the research question, i.e. what is to be studied, and on the manner in which the question is to be studied.

In designing an assignment, thesis or dissertation the principle of coherence can be preserved by ensuring that the research question and methods used fit logically within the paradigm. If a researcher planned to study the learning experience of older people (say older than 40) attending TVET College studies, the use of an objective scale to measure experiences would probably not be effective because this is not the kind of research where you can expect exact and quantifiable responses (the results will be incoherent because you will expect positivist commitments from people who probably have different motives for studying at a late stage in their lives and who will, therefore, not respond the same to questions). You can probably achieve better coherence by grouping target group members together based on certain criteria, for example gender, age brackets, geographical location, etc. By doing so, you will be adopting a positivist ontology by trying to ensure that different sections of your target group have the same origin in terms of age, gender or geography. You can also achieve more coherent results by making use of a more suitable data gathering method, for example interviews.

We can define a paradigm as an integrated cluster of substantive concepts, variables and problems attached with corresponding methodological approaches and tools. The following research paradigms are important:

  • Rationalism.
  • Empiricism.
  • Positivism.
  • Post-positivism.
  • Social constructivism.
  • Critical theory.
  • Interpretivism.
  • Functionalism.
  • Behaviourism.
  • Premodernism.
  • Modernism.
  • Postmodernism.
  • Structuralism.
  • Post-structuralism.
  • Postcolonialism.
  • Neoliberalism.

We will discuss each of the above research paradigms in articles following on this one.

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Video-lessons on Research Methodology on Master’s Degree or Doctoral Level

The videos are posted on the Mentornet Online Platform (https://mentornetonline.co.za/videoCourses.php)

Videos range between 5 and 18 minutes in duration.

  1. Why Would You Embark on Ph. D. or Master’s Degree Studies?
  2. The Research Proposal.
  3. How to Structure Your Research Proposal.
  4. The Difference Between a Research Report on the Honours, the Master’s and the Doctoral Level.
  5. How to Structure a Title Page for a Master’s Degree Thesis or a Ph. D. Dissertation.
  6. The Layout and Structure of a Table of Contents for a Ph. D. Dissertation.
  7. How to Decide on the Context for Your Ph. D. or Master’s Degree Research.
  8. How to Choose a Research Approach for a Ph. D. or Master’s Degree Study.
  9. The Nature and Structure of a Ph. D. Dissertation or Master’s Degree Thesis.
  10. The Relationship Between the Ph. D. Student and the Study Leader.
  11. The Table of Contents of your Ph. D. Dissertation or Master’s Degree Thesis.
  12. How to Prepare an Abstract for a Ph. D. Dissertation.
  13. How to Write the First Chapter of Your Ph. D. Dissertation or Master’s Degree Thesis.
  14. How to Write the Second Plus Chapters of Your Ph. D. Dissertation or Master’s Degree Thesis.
  15. Creating a Draft for a Ph. D. Dissertation or Master’s Degree Thesis.
  16. The Research Problem, Question or Hypothesis for a Ph. D. Dissertation or a Master’s Degree Thesis.
  17. How to Find a Topic for Ph. D. or Master’s Degree Research.
  18. How to Establish Objectives for Ph. D. or Master’s Degree Research.
  19. The Scope for a Ph. D. Dissertation or Master’s Degree Thesis.
  20. Specifying the Limitations for Your Ph. D. or Master’s Degree Research.
  21. Consulting Sources of information for Your Ph. D. or Master’s Degree Research.
  22. Research Methods for Ph. D. and Master’s Degree Studies.
  23. The Interrelatedness of Ontology, Epistemology and Methodology.
  24. Research Methods: Action Research.
  25. Research Methods: Case Studies.
  26. Research Methods: Conceptual Studies.
  27. Research Methods: Ethnography.
  28. Research Methods: Experimental Methods.
  29. Research Methods: Field Research.
  30. Research Methods: Grounded Theory.
  31. Research Methods: Historical Research.
  32. Research Methods: Literature Study.
  33. Research Methods: Sampling Part 1 of 6.
  34. Research Methods: Sampling Part 2 of 6.
  35. Research Methods: Sampling Part 3 of 6.
  36. Research Methods: Sampling Part 4 of 6.
  37. Research Methods: Sampling Part 5 of 6.
  38. Research Methods: Sampling Part 6 of 6.
  39. Research Methods: Statistical Research Methods Part 1 of 2.
  40. Research Methods: Statistical Research Methods Part 2 of 2.
  41. Research Methods: Transformative Research.
  42. Research Methods: Paradigmatic Approaches.
  43. Research Paradigms: Behaviorism.
  44. Research Paradigms: Constructivism.
  45. Research Paradigms: Critical Race Theory.
  46. Research Paradigms: Critical Theory.
  47. Research Paradigms: Empiricism.
  48. Research Paradigms: Ethnomethodology.
  49. Research Paradigms: Feminism.
  50. Research Paradigms: Functionalism.
  51. Research Paradigms: Hermeneutics.
  52. Research Paradigms: Humanism.
  53. Research Paradigms: Interpretivism.
  54. Research Paradigms: Liberalism.
  55. Research Paradigms: Modernism.
  56. Research Paradigms: Neoliberalism.
  57. Research Paradigms: Phenomenology.
  58. Research Paradigms: Positivism.
  59. Research Paradigms: Post-colonialism.
  60. Research Paradigms: Post-modernism.
  61. Research Paradigms: Post-positivism.
  62. Research Paradigms: Post-structuralism.
  63. Research Paradigms: Pragmatism.
  64. Research Paradigms: Pre-modernism.
  65. Research Paradigms: Radicalism.
  66. Research Paradigms: Rationalism.
  67. Research Paradigms: Relativism.
  68. Research Paradigms: Romanticism.
  69. Research Paradigms: Scientism.
  70. Research Paradigms: Structuralism.
  71. Research Paradigms: Symbolic Interactionism.
  72. Research Methods for Ph. D. and Master’s Degree Studies: Data Collection.
  73. Research Methods for Ph. D. and Master’s Degree Studies: Contextualising Your Research.
  74. Research Methods for Ph. D. and Master’s Degree Studies: Using Documents to Collect Data.
  75. Research methods for Ph. D. and Master’s Degree Studies: Quantitative Data Collection Methods.
  76. Research Methods for Ph. D. and Master’s Degree Studies: Qualitative Data Collection Methods.
    1. Artefacts.
    1. Graphics and drawings.
  77. Research Methods for Ph. D. and Master’s Degree Studies: Data Collection Methods. Interviewing Part 1 of 4.
  78. Research Methods for Ph. D. and Master’s Degree Studies: Data Collection Methods. Interviewing Part 2 of 4.
  79. Research Methods for Ph. D. and Master’s Degree Studies: Data Collection Methods. Interviewing Part 3 of 4.
  80. Research Methods for Ph. D. and Master’s Degree Studies: Data Collection Methods. Interviewing Part 4 of 4.
  81. Research Methods for Ph. D. and Master’s Degree Studies: Data Collection Methods. Observation Part 1 of 2.
  82. Research Methods for Ph. D. and Master’s Degree Studies: Data Collection Methods. Observation Part 2 of 2.
  83. Research Methods for Ph. D. and Master’s Degree Studies: Data Collection Methods. Online Data Sources Part 1 of 2.
  84. Research Methods for Ph. D. and Master’s Degree Studies: Data Collection Methods. Online Data Sources Part 2 of 2.
  85. Research Methods for Ph. D. and Master’s Degree Studies: Data Collection Methods. Written Documents.
  86. Research Methods for Ph. D. and Master’s Degree Studies: Preparing for Data Collection.
  87. Research Methods for Ph. D. and Master’s Degree Studies: Data Analysis Through Coding.
  88. Research Methods for Ph. D. and Master’s Degree Studies: Data Analysis, Part 1 of 7.
    1. Analytical induction.
    1. Biographical analysis.
  89. Research Methods for Ph. D. and Master’s Degree Studies: Data Analysis, Part 2 of 7.
    1. Comparative analysis.
    1. Content analysis.
  90. Research Methods for Ph. D. and Master’s Degree Studies: Data Analysis, Part 3 of 7. Conversation and Discourse Analysis.
  91. Research Methods for Ph. D. and Master’s Degree Studies: Data Analysis, Part 4 of 7. Elementary Analysis.
  92. Research Methods for Ph. D. and Master’s Degree Studies: Data Analysis, Part 5 of 7. Ethnographic Analysis.
  93. Research Methods for Ph. D. and Master’s Degree Studies: Data Analysis, Part 6 of 7.
    1. Inductive thematic analysis.
    1. Narrative analysis.
    1. Retrospective analysis.
  94. Research Methods for Ph. D. and Master’s Degree Studies: Data Analysis, Part 7 of 7.
    1. Schema analysis.
    1. Situational analysis.
    1. Textual analysis.
    1. Thematic analysis.
  95. Research Methods for Ph. D. and Master’s Degree Studies: Data Analysis. Methods for Organizing and Analysing Data Part 1 of 2.
  • Research Methods for Ph. D. and Master’s Degree Studies: Data Analysis. Methods for Organizing and Analysing Data Part 2 of 2.
  • Research Methods for Ph. D. and Master’s Degree Studies: The Layout of the Thesis or Dissertation Part 1 of 10.
  • 10.
    • Deconstruction.
    • Empirical generalization.
  • Research Methods for Ph. D. and Master’s Degree Studies: The Layout of the Thesis or Dissertation Part 3 of 10. Ethics in research part 1 of 3.
  • Research Methods for Ph. D. and Master’s Degree Studies: The Layout of the Thesis or Dissertation Part 4 of 10. Ethics in research part 2 of 3.
  • Research Methods for Ph. D. and Master’s Degree Studies: The Layout of the Thesis or Dissertation Part 5 of 10. Ethics in research part 3 of 3.
  • Research Methods for Ph. D. and Master’s Degree Studies: The Layout of the Thesis or Dissertation Part 6 of 10. Typing format.
  • Research Methods for Ph. D. and Master’s Degree Studies: The Layout of the Thesis or Dissertation Part 7 of 10. Quotations.
  • Research Methods for Ph. D. and Master’s Degree Studies: The Layout of the Thesis or Dissertation Part 8 of 10. Referencing sources.
  • Research Methods for Ph. D. and Master’s Degree Studies: The Layout of the Thesis or Dissertation Part 9 of 10. Essential information in references. Part 1 of 2.
  • Research Methods for Ph. D. and Master’s Degree Studies: The Layout of the Thesis or Dissertation Part 10 of 10. Essential information in references. Part 2 of 2.
  • Research Methods for Ph. D. and Master’s Degree Studies: Reviewing the Thesis or Dissertation Part 1 of 3.      
    • The purpose of the review.
    • The relevance of sources.
  • Research Methods for Ph. D. and Master’s Degree Studies: Reviewing the Thesis or Dissertation Part 2 of 3.
    • The relevance of ideas in the literature.
    • Reviewing language usage.
  • Research Methods for Ph. D. and Master’s Degree Studies: Reviewing the Thesis or Dissertation Part 3 of 3.
    • The title page.
    • Proofreading.
    • Appendices.
    • A review checklist.
    • Presentation of the report.
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References Consulted for the Production of the Videos on Research Methodology for Ph. D. and Master’s Degree Studies

Prepared by Dr. Hannes Nel

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Babbie, E., 2011. Introduction to Social Research. International Edition. Cengage Learning. Wadsworth, Australia.

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Bak, N. 2013. Completing your thesis. A practical guide. Van Schaik Publishers, Pretoria.

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Samuels, H. Basic Steps in the Research Process. Cambridge Rindge and Latin Research Guide.

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Selecting Participants and Conducting Research.

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Shuttleworth, M. The Parts of a Research Paper.

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Stanford Encyclopedia of Philosophy. Critical Theory.

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Stanford Encyclopedia of Philosophy. Relativism.

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Steiner, C.J. 2002. The Technicist Paradigm and Scientism in Qualitative Research. The Qualitative Report, Volume 7, Number 2, Article 4.

Accessed on 05/04/2017.

Statpac.Inc. Statistical Significance.

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Summary of Survey Analysis Software.

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The Guardian. Neoliberalism – the ideology at the root of all our problems.

Accessed on 24/04/2018.

Thorsen, D.E. and Lie, A. What is Neoliberalism? Department of Political Science, University of Ohio.

https://folk.uio.no/daget/neoliberalism.pdf. Alternatively: https://

pdfs.semanticscholar.org/089/731ee9a3257a0baa9a4e302b578f1bbc59d2.pdf.

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Trevors, J.T. Transformative research: definitions, approaches and consequences.

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Wright, J. What are the limitations of phenomenology?

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Other

Anderson, T. Date unknown. Research Paradigms: Ontologies, Epistemologies & Methods. PhD Seminar slide show, Universitat Oberta de Catalunya.

Asiko, A.B. December 2016. Beyond a Qualitative Enquiry: A Neoliberal Society and Power Relations in Action. International Journal of Scientific Research and Innovative Technology. Vol 3 No. 12.

Crews, K.D. 2013. Copyright and Your Research report: Ownership, Fair Use, and Your Rights and Responsibilities. ProQuest Article.

Mackenzie, N. and Knipe, S. 2006. Research delimmas: Paradigms, methods and methodology. Issues In Educational Research, Vol 16.

Nel, J.P. 2007. A Strategic Approach to Quality Assurance in Occupationally-directed Education, Training and Development in South Africa. D. Phil Dissertation. University of Johannesburg.

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ARTICLE 100: Research Methods for Ph. D. and Master’s Degree Studies: The Layout of the Thesis or Dissertation Part 4 of 9 Parts: Ethics Part 2 of 3 Parts

Written by Dr. Hannes Nel

What does ethics in research entail?

Some post-graduate students will think that not committing plagiarism is what it is all about.

And they will not be entirely wrong.

Not committing plagiarism is an element of ethics.

However, there are many other facets to the concept.

Ethics are not only important for writing your thesis or dissertation, but also for the safety and integrity of the participants.

Especially the target group for your research.

I discuss the following issues on ethics in this article:

  1. Axiology.
  2. Codes of consent.
  3. No harm to participants.

Axiology. The quality of our research will be judged according to the criteria of validity and authenticity. This brings us to the concept “axiology”. Axiology addresses the nature of ethical behaviour. In research axiology refers to what you belief to be ethical. Basic beliefs about what is ethical are embedded in research paradigms and guide the researcher’s decision making. The purpose of the research needs to be balanced with what you value as well as other ethical considerations in the conduct of research, notably validity and authenticity.

Validity and authenticity are prerequisites for understanding. It is in this that epistemology and ethics are brought together. It is also a meeting point between epistemology and ontology because what we know (ontology) is tied up with what we understand (epistemology).

Ontological and educative authenticity, on the other hand, were designated as criteria for determining a raised level of awareness; in the first instance, by individual research participants and, in the second, by individuals who share a particular value system and, therefore, maintain contact for some social or organisational purpose. That is why the validity of your epistemological approach starts with ontology. It is rather difficult and mostly unnecessary, to separate epistemology from ontology, because they form a unified system and are highly interdependent. Epistemology is the declarative extension of ontology and often includes additional ontological statements.

It is, however, important that you do not confuse ontology and epistemology. As a matter of routine, it helps to mention ontology first, and then epistemology, since it enables you to base your study on a statement of “fact” (which can include your target group, world or society) before you do any explaining and theorising.

It is, sometimes, necessary and useful to develop models of real-life situations or artefacts for research purposes. Choice of representation (i.e., the way in which models must be articulable) does, in fact, have real implications for what aspects of the research target receive the most attention – what the model handles well, and what gets minimised or left out. On the other hand, models of what there is (ontology) need to be explained by what can be known and how it can be known (epistemology). We know that the shortest distance between two points is a straight line – this is what we know, or the ontology. How we know this, that is. the evidence that the shortest route between two points is a straight line, is the epistemology.

Epistemology is not just a way of knowing. It is also a system of knowing through cognitive reasoning based on internal logic (contextualising information gathered to your research purpose) and the wider applicability of the knowledge, that is external validity (ensuring that findings are in line with the general environment and that they will be acceptable to other stakeholders).

Epistemology is intimately linked to a world-view. People from different continents, countries and even regions will often not have the same outlook or frame of reference towards the world around them. Thus, the conditions under which people live and learn, shape both their knowledge and their world-views.

Codes of consent. Codes of consent deal with if the target group for the research participates voluntarily or not. Qualitative research can be an intrusion into people’s lives, especially if it is social research. The interviewer’s knock on the door or the arrival of a questionnaire in the post or by email signals the beginning of an activity that the respondent has not requested, and one that may require a significant portion of his or her time and energy. Participation in a social experiment disrupts the subject’s personal and work schedule.

What is needed is informed consent, meaning that the research subjects need to know that they are being researched and what the nature and purpose of the research are. Participants in research should base their voluntary participation on a full understanding of the nature of the research and possible risks involved. When obtaining their consent, you need to appreciate that the participants may be under subtle pressure to co-operate, and you should take this possibility into account.

Consent is considered ‘informed’ when, in a language that the participants understand, you explain to them the nature of the research, their right to refuse to participate or withdraw from participation at any time, factors that may influence their willingness to participate, and the data collection methods to be used. The participants must have a complete understanding of the nature, aims and processes of the research, its intended outcomes, as well as any consequences that may follow from participation and publication.

Participants in research are often required to provide personal information about themselves, such as their age, weight, eating habits, drinking habits, smoking habits, etc. Such information may be unknown to their friends and associates and they might not want people close to them to know. Furthermore, research on human activities often requires that such information be revealed to strangers. Other professionals, such as physicians, and lawyers, also require such information. Their requests, however, may be justified because the information is required for them to serve the personal interests of the respondent. Social researchers can seldom make this claim. Like medical scientists, they can only argue that the research effort may ultimately help all of humanity.

No one should be forced to participate in research. This norm, however, is far easier to accept in theory than it is to apply in practice. It is unlikely that people will participate voluntarily if they do not believe that they will, somehow, benefit from participating. That is probably the most important reason why the response rate to questionnaires is often low, and you should plan on receiving only a fraction of the questionnaires back that you send out. Any response rate higher than 10% is good, unless you take special steps, like delivering and collecting the questionnaires personally.

No harm to the participants. Research should never physically, psychologically or financially injure the people involved, regardless of whether they volunteer for the study. Questions that would embarrass people or endanger their home life, friendship, career, etc. should not be asked or, if asked, be done with the consent of the participants. Sometimes subjects are asked to reveal deviant behaviour, attitudes they feel are unpopular, or demeaning personal characteristics, such as low income, the receipt of welfare payments, etc. You, as the researcher, should agree not to reveal such information and you must keep your undertaking. You must look for the subtlest dangers that information might end up in the wrong hands and guard against them.

The ethical norms of voluntary participation and no harm to participants have become formalised in the concept of informed consent, which we touched on under the sub-heading “codes of consent”. 

To avoid harm to respondents, you as the researcher should have the firmest of scientific grounds for asking questions that may cause injury to others. The objective of informed consent may be rather difficult to achieve and maintain in the case of internet or other electronic research contexts. You might not even have physical contact with the participants in the research. The challenge is exacerbated if the maintenance of anonymity is also needed. With this as background, informed consent can sometimes cause harm, be counterproductive or simply impossible to achieve.

Qualitative research projects may also force participants to face aspects of themselves that they do not normally consider. The project can be a source of continuing, personal agony for the subject. If the study concerns codes of ethical conduct, for example, the subject may begin questioning his or her own morality, and that personal concern may last long after the research has been completed and reported.

Subjects can also be harmed by the analysis and reporting of data. If the respondent reads the research report it might happen that he or she may find themselves characterised in an index, table or description. Having done so, they may find themselves portrayed – though not identified by name – as bigoted, unpatriotic, irregular, etc. 

An obvious and generally applicable concern in the protection of the participants’ interests and well-being is the protection of their identity, especially in survey research. Two techniques – anonymity and confidentiality – can be used in this regard.

Anonymity. A respondent may be considered anonymous when you cannot link a given response with a given respondent. This means an interview survey respondent can never be considered anonymous, since an interviewer collects the information from an identifiable respondent. Assuring anonymity makes it difficult to keep track of who has or has not returned the questionnaires.

Anonymity relates to the issue of privacy and is especially difficult to maintain on the internet. Privacy is regarded as the right to withhold information from public consumption. People often use publicly accessible information spaces, like Facebook, but maintain strong expectations of privacy. Because of this, privacy often refers to the way information is used rather than how easy or difficult it is for people to gain access to such information.

Confidentiality. Confidentiality means that you, as the researcher, should protect your participant’s identity, places of work and stay, and the location of the research. In a confidential survey, the researcher can identify a given person’s responses but essentially promises not to do so publicly.

You can use several techniques to ensure the maintenance of confidentiality. All stakeholders in the research team who might need to maintain confidentiality and who will have access to data and findings should be trained in their ethical responsibilities. All names and addresses should be removed from the questionnaires as soon as they are no longer needed and replaced by special identification numbers, not their national identification numbers. A file should be prepared linking special identification numbers or codes with real identification numbers. This file should be kept in a safe or lockable filing cabinet to which only people who need to know have access.  

It is your responsibility to inform the respondent if a survey is confidential rather than anonymous. Do not use the term anonymous if you mean confidential.  

Summary

Axiology addresses the nature of ethical behaviour.

Basic beliefs about what is ethical are embedded in research paradigms.

You need to achieve a balance in your research between ethics, your values, validity and authenticity.

Validity and authenticity are prerequisites for understanding.

Ethics is based on the ontology and epistemology of your research topic.

Codes of consent deal with if the target group for your research participates voluntarily or not.

Participants in research need to be informed about the purpose and nature of the research, how they will be involved and possible risks.

Participants are sometimes asked to share personal information with the researcher.

No one should be forced to participate in research.

You should keep in mind that the response rate to especially questionnaires is often low.

Research should never physically, psychologically or financially injure participants in the research.

Participants must not be harmed by the collection, analysis or reporting of data.

Questions asked to participants must be relevant and necessary for the research.

Anonymity and confidentiality should be maintained if necessary.

Anonymity is difficult to maintain.

Confidentiality means that the participant’s identity, places of work and stay and where the research took place must only be revealed on a need-to-know basis.

Close

Maintaining sound ethical standards is important for the protection of the interests of others who participate in your research.

However, most importantly, you should protect your own interests.

It is in your interest not to cause damage to other people.

And it is in your interest to submit good quality work.

Because gaining higher qualifications is supposed to prepare you for a career and quality life.

Enjoy your studies.

Thank you.   

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ARTICLE 99: Research Methods for Ph. D. and Master’s Degree Studies: The Layout of the Thesis or Dissertation, Part 3 of 9: Ethics in Research Part 1 of 3

Written by Dr. Hannes Nel

Do people still care about the truth?

Did people ever care about the truth?

Are opinions more important than facts?

And what will the implications be if the truth is no longer important, and opinions are more important than facts?

I discuss the principles of ethics in research in this article.

Ethics are typically associated with morality, that is matters of right and wrong. You need to know, understand and accept the general consensus amongst academic researchers about what is acceptable and not acceptable in the conduct of scientific inquiry. The following principles are fundamental to an ethical approach to research:

  1. Research should always respect and protect the dignity of participants in research. This requires sensitivity, empathy, and accountability towards the target group for your research. The greater the vulnerability of the participants in the research (community, author, expert, etc.), the greater the obligation of the researcher to protect the participant. To this end, you as the researcher should:
    1. Ensure that you know and understand the values, cultures and protocols of your target group. It might be necessary to be academically or culturally qualified to work with some communities.
    1. Consult experts on communities if you lack the qualifications, knowledge and cultural background to work with them.
    1. Share your findings honestly, clearly, comprehensively and accountably with only those who are entitled to have access to the findings.
    1. Report your findings, and the limitations thereof, openly and honestly so that peers and the public in general may scrutinise and evaluate them, keeping in mind that your findings may probably only be shared with certain people.
    1. Acknowledge and point out the possibility of alternative interpretations.
    1. Respect the right of fellow researchers to work with different paradigms and research methods and accept it if they disagree with your finding and interpretation.
    1. Agree to disagree rather than to defend your point of view fanatically in an effort to sway others.
    1. Honour the authority of professional codes in specific disciplines.
    1. Refrain from using your position for undeserved, corrupt or otherwise dishonest personal gain.
  2. Because ‘harm’ is defined contextually, ethical principles are more likely to be understood inductively rather than applied universally. That is, rather than a one-size-fits-all approach, ethical decision-making is best approached through the application of practical judgement related to the specific context.
  3. When making ethical decisions, you should balance the rights of participants with the social benefits of the research and your right to conduct the research. In different contexts the rights of subjects may outweigh the benefits of research.
  4. The importance of adhering to ethical requirements is equally important regardless of which stage of the research process is involved.
  5. Ethical decision-making is a deliberate process, and you should consult as many people and resources as possible in the process, including fellow researchers, people participating in or familiar with the contexts or sites being studied, research review boards, ethic guidelines, published scholarships and where applicable, legal precedent.

With the above principles in mind, the ethical issues that impact the most on research are:

  1. The notion of truth.
  2. Axiology.
  3. Codes of consent.
  4. No harm to the participants.
  5. Trust.
  6. Deception.
  7. Analysis and reporting.
  8. Plagiarism.
  9. Legality.
  10. Professionalism.
  11. Research ethics and society.
  12. Copyright and intellectual property right.
  13. The originality of your research.
  14. Promulgation of results.

The notion of truth. Truth is largely governed by critical epistemology. Critical epistemology is an understanding of the relationship between power, cognitive reasoning and truth. This implies that the way we think about concepts, theory, philosophy and phenomena determines what we would regard as truth. You should uphold the epistemological principles that apply to all researchers, meaning that truth should be a product of logical reasoning and evidence. In terms of critical epistemology, however, we need to be careful – it is easy to twist your arguments to fit your preferences by describing them in terms of an unfounded epistemology. The need for and availability of power can erode logical truth. Sometimes writers and researchers work with a predetermined political agenda in mind, for example to gain support from a particular group or to promote a political objective, rather than to strive for scientific validity. You will only truly develop new knowledge or add to existing knowledge, that is, make a positive epistemological contribution to science, if you are objective and honest in your interpretation and analysis of information. This brings us to the epistemic imperative.

In the world of science our aim is to generate truthful (valid/plausible) descriptions and explanations of the world. This is called the epistemic intent of science. “Epistemic” is derived from episteme, the Greek word for “truthful knowledge”. We use “truthful” as a synonym for “valid” or “close approximation of the truth”. We accept knowledge to be accurate and true when we have sufficient reason to believe that it is a logical and motivated representation or explanation of a phenomenon, event or process. There needs to be enough evidence to support such claims. It mostly takes time to accumulate evidence and claims of truth must withstand repeated testing under various conditions in order to be accepted as valid or, at least, plausible.

“Instant verification” of a hypothesis or theory is largely impossible to achieve. Research takes place all the time, and scientific communities accept certain points of view, hypotheses or theories as valid and plausible, based on the best available evidence at a given point in time. However, new empirical evidence contradicting current “truth” can be revealed by new research at any time in the future. The obvious thing to do when this happens would be for scientists to revise their opinions and change their theories.

Commitment to “truth” is not the same as the search for certainty or infallible knowledge. Neither does it imply holding truth as absolute without any concern for time and space. The notions of “certainty” and “infallibility” would suggest that we can never be wrong. If we are to accept a particular point of view as “certain” or “infallible” we are in fact saying that no amount of new evidence can ever lead us to change our beliefs. This would obviously be a false stance, making a mockery of scientific enterprise. Life and the environment are dynamic concepts – not only do they change because of internal and external forces impacting on them, but we also discover flaws in our beliefs and perceptions. None of the paradigms that we discussed already go so far as to claim that truth is exact and perfectly final. Pre-modernism might be regarded as an exception by some. The commitment to true and valid knowledge is, therefore, not a search for infallible and absolute knowledge.

Even though we know that “truth” is a rather volatile concept, the “epistemic imperative” demands that researchers commit themselves to the pursuit of the most truthful claims about the world and the phenomena and events that have an impact on human beings. This has at least three implications:

  • The idea of an imperative implies that a type of “moral contract” has been entered into. It is neither optional nor negotiable. This “contract” is intrinsic to scientific inquiry. Every researcher and scientist should commit themselves to this contract. When you embark on a scientific project, or undertake any scientific enquiry, you tacitly agree to the epistemic imperative – to the search for truth. But the epistemic imperative is not merely an ideal or regulative principle. It has real consequences. This is evident in the way that the scientific community deals with any attempt to circumvent or violate the imperative.
  • The “epistemic imperative” is a commitment to an ideal. Its goal is to generate results and findings which are as valid or truthful as possible. The fact that it is first and foremost an ideal means that it might not always be attained in practice. All research, however, should represent steps closer to accuracy and truth. It seems to be unlikely, if not impossible, to achieve perfect accuracy and truth, amongst other things because of methodological problems, practical constraints (such as lack of resources) and a dynamic environment. We are often required to settle for results that are, at best, approximations to the truth.
  • The meaning that we attach to the concept “truth” presupposes a loose, somewhat metaphorical relationship between our scientific proposition and the world. Contrary to the classical notion that “truth” means that what we regard as reality, and what reality actually is, as being the same, we accept that this relationship is not that simple. The notion of “fit”, “articulation” or “modelling” is a more appropriate term for two reasons: Firstly, it suggests that a point of view can be relatively true. Articulation is not an absolute notion but allows for degrees of accuracy. Secondly, the term “articulation” can refer to the relationship between our points of view and the world (the traditional notions of “representation” or “correspondence”), or to the relationships between our points of view. In the latter’s case, we would use the term “coherence”. This means that “articulation”, “fit” or “modelling” is used to refer to both empirical and conceptual correspondence. When our conceptual system exhibits a high degree of internal coherence, we could also speak of the concepts as “fitting”, “being articulated” or “being modelled” well.

Summary

Ethics deal with matters of right and wrong.

The principles of an ethical approach to research are:

  1. Respect and protect the dignity of participants in research.
    1. Base ethical decision-making on the application of practical judgement in a specific context.
    1. Balance the rights of participants with the social benefits of the research and your right to conduct the research.
    1. Maintain and apply sound ethics throughout the research process.
    1. Treat all participants and stakeholders in your research ethically.

Truth is largely governed by critical epistemology.

It should be the product of logical reasoning and evidence.

The need for and availability of power can erode logical truth.

Always keep the epistemic imperative in mind when conducting research.

The implications of the epistemic imperative are:

  1. A moral contract is intrinsic to scientific inquiry.
  2. All research should represent steps closer to accuracy and truth.
  3. Truth is not always absolute or timeless.

Close

On the questions that I posed in my introduction –

All people do not care about the truth.

But, as you know, this is nothing new.

Not all people seem to have the ability to foresee the consequences of dishonesty for individuals, families, communities, cities, countries, the world.

Ironically lack of visionary thinking has this nasty way of causing great damage to the myopic in the end.

Enjoy your studies.

Thank you.

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ARTICLE 93: Research Methods for Ph. D. and Master’s Degree Studies: Data Analysis: Part 6 of 7 Parts

Written by Dr. Hannes Nel

In academic research we need to think inductively and deductively.

Inductive thinking is used to develop a new theory.

Therefore, it is what you would mostly use when writing a dissertation for a doctoral degree.

And you should use inductive thematic analysis to analyse the data that you collect.

Deductive thinking is used to test existing theory.

Therefore, it is what you would mostly use when writing a thesis for a master’s degree.

And you should use retrospective analysis to analyse the data that you collect.

Narrative analysis uses both inductive and deductive thinking more or less equally.

That is why both a dissertation and a thesis can be written in a narrative format.

I will discuss the nature of inductive thematic analysis, narrative analysis and retrospective analysis in this article.

Inductive thematic analysis (ITA)

Inductive thematic analysis draws on inductive analytic methods. It involves reading through textual data and identifying and coding emergent themes within the data.

ITA requires the generation of free-flow data. The most common data collection techniques associated with ITA are in-depth interviews and focus groups. You can also analyse notes from participant observation activities with ITA, but interview and focus group data are better. ITA is often used in qualitative inquiry, and non-numerical computer software, specifically designed for qualitative research, is often used to code and group data.

Paradigmatic approaches that fit well with ITA include post-structuralism, rationalism, symbolic interactionism, and transformative research.

Narrative analysis

The word “narrative” is generally associated with terms such as “tale”, or “story”. Such stories are mostly told in the first person, although somebody else might also tell the story about a different character, that is in the second or third person. First person will apply if an interview is held. Every person has his or her own story, and you can design your research project to collect and analyse the stories of participants, for example when you study the lived experiences of somebody who is a member of a gang on the Cape Flats.

There are different kinds of narrative research studies ranging from personal experiences to oral historical narratives. Therefore, narrative analysis refers to a variety of procedures for interpreting the narratives obtained through interviews, questionnaires by email or post, perhaps even focus groups. Narrative analysis includes formal and structural means of analysis. One can, for example, relate the information obtained from a gang member in terms of circumstances and reasons why he or she became a gang member, growth into gang activities, the consequences of criminal activities for his or her personal life, career, etc. One can also do a functional analysis looking at gang activities and customs (crime, gang fights, recruiting new members, punishment for transgression of gang rules, etc.)

In the analysis of narrative, you will track sequences, chronology, stories or processes in the data, keeping in mind that most narratives have a backwards and forwards nature that needs to be unravelled in the process of analysing the data.

Like many other data collection approaches, narrative analysis, also sometimes called ‘narrative inquiry’, is based on the study and textual representation of discourse, or the analysis of words. The type of discourse or text used in narrative analysis is, as the name indicates, narratives.

The sequence of events can be generated and recorded during the data collection process, such as through in-depth interviews or focus groups; they can be incidentally captured during participant observation; or, they can be embedded in written forms, including diaries, letters, the internet, or literary works. Narratives are analysed in numerous ways and narrative analysis can be used in research within a substantial variety of social sciences and academic fields, such as sociology, management, labour relations, literature, psychology, etc.

Narrative analysis can be used for a wide range of purposes. Some of the more common usages include formative research for a subsequent study, comparative analysis between groups, understanding social or historical phenomena, or diagnosing psychological or medical conditions. The underlying principle of a narrative inquiry is that narratives are the source of data used, and their analysis opens a gateway to better understanding of a given research topic.

In most narratives meaning is conveyed at different levels, for example informational content level that is suitable for content analysis; textual level that is suitable for hermeneutic or discourse analysis, etc.

Narrative analysis has its own methodology. In narrative analysis you will analyse data in search of narrative strings (present commonalities running through and across texts), narrative threads (major emerging themes) and temporal/spatial themes (past, present and future contexts).

Retrospective analysis

Retrospective analysis is sometimes also called ‘retrospective studies’ or ‘trend analysis’ or ‘trend studies’. Retrospective analysis usually looks back in time to determine what kind of changes have taken place. For example, if you were to trace the development of computers over the past three decades, you would see some remarkable changes and improvements.

Retrospective analysis focuses on changes in the environment rather than in people, although changes in the fashions, cultures, habits, values, jobs, etc. are also often analysed. Each stage in a chronological development is represented by a sample and each sample is compared with the others against certain criteria.

Retrospective analysis examines recorded data to establish patterns of change that have already occurred in the hope of predicting what will probably happen in the future. Predicting the future, however, is not simple and often not accurate. The reason for this is that, as the environment changes, so do the variables that determine or govern the change. It, therefore, stands to reason that, the longer ahead one tries to predict the future, the more inaccurate will your predictions probably be.

Retrospective analysis does not include the same respondents over time, so the possibility exists for variation in data due to the different respondents rather than the change in trends.

Summary

Inductive thematic analysis, or ITA:

  1. Draws on inductive analytical methods.
  2. Involves reading textual data.
  3. Identifies and codes emergent themes within the data.
  4. Requires the generation of free-flow data.
  5. Favours in-depth interviews and focus groups.
  6. Can also use participant observation.
  7. Fits well with qualitative research and critical or interpretive paradigms.

Narrative analysis:

  1. Tells stories related by people.
  2. Ranges from personal experiences to historical narratives.
  3. Can use a wide range of data collection methods.
  4. Includes formal, structural and functional analysis.
  5. Tracks sequences, chronology, stories or processes in data.
  6. Is based on the textual representation of discourse, or the analysis of words.
  7. Is used by a substantial variety of social sciences.
  8. Can be used for a wide range of purposes.
  9. Conveys meaning on different levels.
  10. Has its own methodology.

Retrospective analysis:

  1. Looks back in time to identify change.
  2. Focuses on change in the environment.
  3. Represents and compares change in samples.
  4. Sometimes tries to predict the future.
  5. Does not include the same respondents over time.

Close 

It is a good idea to mention and explain how you analysed the data that you collected in your thesis or dissertation.

Ph. D. students will already do so in their research proposal.

That is why you need to know which data analysis methods are available and what they mean.

It will also help to ensure that you use the data that you collect efficiently and effectively to achieve the purpose of your research.

Enjoy your studies.

Thank you.

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ARTICLE 88: Research Methods for Ph. D. and Master’s Degree Studies: Data Analysis Methods Part 1 of 7 Parts

Written by Dr. Hannes Nel

Isn’t life strange?

There are so many ways in which we can learn.

And the interrelatedness of events, phenomena and behaviour can be researched in so many ways.  

And we can discover truths and learn lesson by linking data, paradigms, research methods, dada collection and analysis methods.

And by changing the combination of research concepts, we can discover new lessons, knowledge and truths.

Research often deals with the analysis of data to discriminate between right and wrong, true and false.

Furthermore, people and life form a system with a multitude of links and correlations.

Consequently, we can learn by conducting research on even just an individual. 

I discuss the following two data analysis methods in this article:

  1. Analytical induction.
  2. Biographical analysis.

Analytical induction

Induction, in contrast to deduction, involves inferring general conclusions from particular instances. It is a way of gaining understanding of concepts and procedures by identifying and testing causal links between them. Analytical induction is, therefore, a procedure for analysing data which requires systematic analysis.

It aims to ensure that the analyst’s theoretical conclusions cover the entire range of the available data.

Analytical induction is a data analysis method that is often regarded as a research method. It uses inductive, as opposed to deductive reasoning. Qualitative data can be analysed without making use of statistical methods. The process to be explained and the factors that explain the phenomenon are progressively redefined in an iterative process to maintain a perfect relationship between them.

The procedure of analytical induction means that you, as the researcher, form an initial hypothesis or a series of hypotheses or a problem statement or question and then search for false evidence in the data at your disposal and formulate or modify your conclusions based on the available evidence. This is especially important if you work on a hypothesis, seeing that evidence can prove or refute a hypothesis.

Data are studied and analysed to generate or identify categories of phenomena; relationships between these categories are sought and working typologies and summaries are written based on the data that you examined. These are then refined by subsequent cases and through analysis. You should not only look for evidence that corroborates your premise but also for evidence that refutes it or calls for modification. Your original explanation or theory may be modified, accepted, enlarged or restricted, based on the conclusions to which the data leads you. Analytical induction will typically follow the following procedure:     

  1. A rough definition of the phenomenon to be explained is formulated.
  2. A hypothetical explanation of the phenomenon is formulated.
  3. A real-life case is studied in the light of the hypothesis, with the object of determining whether the hypothesis fits the facts in the case.
  4. If the hypothesis does not fit the facts, either the hypothesis is reformulated or the phenomenon to be explained is redefined, so that the case is excluded.
  5. Practical certainty may be attained after a small number of cases have been examined, but the discovery of negative evidence disproves the explanation and requires a reformulation.
  6. The procedure of examining cases, redefining the phenomenon, and reformulating the hypothesis is continued until a universal relationship is established, each negative case calling for a redefinition or a reformulation.
  7. Theories generated by logical deduction from a priori assumptions.

Paradigmatic approaches that can be used with analytical induction include all paradigms where real-life case studies are conducted, for example transformative research, romanticism, relativism, rationalism, post-structuralism, neoliberalism and many more.

Biographical analysis

Biographical analysis focuses on an individual. It would mostly focus on a certain period in a person’s life when she or he did something or was somebody of note. Biographical analysis can include research on individual biographies, autobiographies, life histories and the history of somebody told by those who know it. Data for a biographical analysis will mostly be archived documents or at least documents that belong in an archive. Interviews can also be used if the person is still alive or by interviewing people who knew the individual well when still alive.

Although biographical analysis mostly deals with prominent individuals, it can also deal with humble people, people with tragic life experiences, people from whose life experiences lessons can be learned, etc. Regardless of whether the individual is or was a prominent person or not, you as the researcher will need to collect extensive information on the individual, develop a clear understanding of the historical and contextual background, and have the ability to write in a good narrative format.

You can approach an autobiographical analysis as a classical biography or as an interpretive biography. A classical biography is one in which you, as the researcher, would be concerned about the validity and criticism of primary sources so that you will develop a factual base for explanations. An interpretive biography is a study in which your presence and your point of view are acknowledged in the narrative. Interpretive biographies recognise that in a sense, the writer ‘creates’ the person in the narrative.  

Summary

Analytical induction:

  1. Is a procedure for analysing data.
  2. Requires systematic analysis.
  3. Identifies and tests causal links between phenomena.
  4. Ensures complete coverage of data through theoretical conclusions.
  5. Is regarded as a research method by some.
  6. Progressively refines the explanation of phenomena.
  7. Searches for false information through hypothesis testing.
  8. Searches for relationships between phenomena.
  9. Modifies wrong conclusions.
  10. Identifies categories of phenomena.
  11. Enables the researcher to write and summarise working typologies.

Biographical analysis:

  1. Focuses on the individual.
  2. Can include research on individual biographies, autobiographies and life histories.
  3. Mostly fall back on archival documents.
  4. Can deal with anybody’s experiences from which others can gain value and learn lessons.
  5. Can be a classical or interpretive biography.

Close

In this video, we saw how we can gain knowledge by testing the validity, authenticity and accuracy of data.

We also saw that we can learn from the experiences of others.

There are many other ways in which we can discover knowledge by analysing existing data.

We will discuss them in the six articles following on this one.

Enjoy your studies.

Thank you.

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