Mini Track on Data Collection and Analysis in Case Study Research
Mini Track Chair: Prof Noel Pearse, Rhodes Business School, Rhodes University, South Africa
According to Yin (2014 p. 44 and 45) a case study inquiry is one which “investigates a contemporary phenomenon in depth and within its real-life context, especially when the boundaries between phenomenon and context are not clearly evident.”, and which “copes with the technically distinctive situation in which there will be many more variables of interest than data points, and as one result relies on multiple sources of evidence, with data needing to converge in a triangulating fashion, and as another result benefits from the prior development of theoretical propositions to guide data collection and analysis”.
Some of the main characteristics of case studies include:
- Addressing research questions that are asking “How?” and “Why?” in relation to contemporary events.
- The use and combination of multiple data collection techniques (such as interviews, questionnaires, documents and observation), and often from multiple sources.
- An array of analytical procedures that can be used such as Pattern Matching, Explanation Building, Time-Series Analysis, Logic Models and Cross-Case Synthesis.
These, and other characteristics display the flexibility of the case study method, which can be applied to researching one or more individual, group, organisation, process, event, or related phenomena. There is also flexibility of approach, with Riege (2003) suggesting that a case study can be followed in any one of four paradigms, namely positivism, realism, critical theory and constructivism. While it is this level of flexibility that makes the case study a useful and appealing research method, it can also create confusion for the researcher and endorse poor quality research, lacking rigour. This is not only a challenge for the researcher, but also for the teaching of the case study as a research method.
This mini-track therefore seeks to explore the variety of data collection and analysis techniques in case study research. In particular, papers are encouraged that:
- Illustrate how to enhance the quality of case study research
- Provide structured approaches and examples of designing and/or conducting case study research
- Illustrate good or novel teaching practises in relation to teaching researchers how to use the case study method.
Riege, AM 2003, ‘Validity and reliability tests in case study research: a literature review with “hands‐on” applications for each research phase’, Qualitative Market Research: An International Journal, vol. 6, no. 2, pp. 75–86
Yin, RK 2014, Case Study Research, Design and Methods, 5th edn, SAGE Publications, Thousand Oaks
Mini Track on Fake Knowledge – Academic Misconduct
Mini Track Chair: Shawren Singh, School of Computing, UNISA, South Africa
Academic achievement is being assaulted by sophisticated cybercriminals who generate fake knowledge through what has become known as academic mills that sell counterfeit academic research papers, term reports, and even complete dissertations. In addition, predatory journals are exploiting naïve academics by publishing work which is not recognised by any serious university. To add to this there is even the sale of counterfeit degree certificates which can deceive the public into believing that the holder of such a qualification is an expert in their field.
Both Counterfeit degrees and fake knowledge production is a serious concern for a knowledge-driven society. Purchasing a degree is a crude example of academic misconduct, where candidates use sophisticated internet-based systems to cheat the academic systems. Some examples of such systems include Ghostwriting, Contract cheating and Plagiarism.
Fake knowledge is a term used to describe a claim that rigorous research has led to some new substantial understanding, i.e. new knowledge of the topic being studied, while in fact this is not true. Fake knowledge could be the result of research misconduct i.e. lying or cheating, or it could come about because of the researcher’s lack of competence. Fake knowledge involves violating established scientific practices by, for example, fabricating raw data, analysing the fabricating raw data using sophisticated scientific techniques or mis-analysing raw data and then deceiving science guardians into publishing these fabricated results as a contribution to the scientific body of knowledge. Fake knowledge is on the academic radar, but it needs further attention if it is to be adequately dealt with. Fake knowledge production within the scientific community has been highlighted by the numerous retractions that academic journals have made recently (Moylan & Kowalczuk, 2016).
The purpose of this mini-track is to seek a better understanding of the issues related to fake knowledge production. In particular:
- How are universities and research leaders dealing with sophisticated fake knowledge production systems that are attacking the ethics and integrity of the academic system?
- How extensive is fake knowledge production and how can fake knowledge production be stopped?
- What are the repercussions for those persons who engage in fake knowledge production?
- How extensive is cheating during the degree process and how can it be stopped?
- What can be done about predatory journals?