Abstract
This design research was focused on developing standards covering the entire process of examination to limit the chances of security risks (e.g., the prevention of exam fraud as much as possible, and detection by means of data forensics), together these standards form the Educational Data Forensics Protocol. Two research questions guided this study. The first question was, which standards regarding preventing and detecting fraud in the process of examination need to be included into the EDF protocol? In addition, practitioners must be able to act on indications of exam fraud based on these standards. Therefore, a second research question was formulated, namely which conditions must be considered during development of the EDF protocol to support practitioners in detecting possible gaps in the security of their examination process?
The EDF protocol was developed and validated in five consecutive steps. This study analyses on the theoretical base of developing the EDF protocol (Step 1) and the considerations for developing a prototype (Step 2). The prototype was being validated (e.g., establishing correctness of the content) through seven semi-structured interviews with content experts in the field of either test security or data forensics (Step 3). Statements from these interviews were used to adjust the prototype into a final version of the EDF protocol (Step 4). Finally, to determine the practical value, the final version of the EDF protocol was used to flag gaps in the security of the exam process and determine possible security risks for one of eX:plain’ s exam programs (Step 5).
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References
McCabe, D.L., Butterfield, K.D., Trevino, L.K.: Academic dishonesty in graduate business programs: prevalence, causes, and proposed action. Acad. Manag. Learn. Educ. 5(3), 294–305 (2006)
McCabe, D.L.: CAI Research. Center for Academic Integrity (2005). http://www.academicintegrity.org/cai_research.asp
Murdock, T.B., Hale, N.M., Weber, M.J.: Predictors of cheating among early adolescents: academic and social motivations. Contemp. Educ. Psychol. 26, 96–115 (2001)
Novotney, A.: Beat the cheat. Am. Psychol. Assoc. 42(6), 54 (2011)
Witherspoon, M., Maldonado, N., Lacey, C.H.: Undergraduates and academic dishonesty. Int. J. Bus. Soc. Sci. 3(1) (2012)
Yee, K., MacKown, P.: Detecting and preventing cheating during exams. Center for Academic Integrity, Rutland Institute for Ethics, Clemson University (2010). http://www.academicintegrity.org
Marianti, S., Fox, J.P., Avetisyan, M., Veldkamp, B.P., Tijmstra, J.: Testing for aberrant behavior in response time modeling. J. Educ. Behav. Stat. 39(6), 426–451 (2014). https://doi.org/10.3102/1076998614559412
Impara, J.C., Kingbury, G., Maynes, D., Fitzgerald, C.: Detecting cheating in computer adaptive test using data forensics. In: National Council on Measurement in Education and the National Association of Test Directors, Montreal, Canada (2005)
Plackner, C., Primoli, V.: Data forensics: a compare and contrast analysis of multiple methods. Presented at the 2012 Conference on Statistical Detection of Potential Exam Fraud in Lawrence, KS (2012)
Van Noord, S.: Detecting cheating in computer based multiple-choice testing. Master thesis, University of Twente, The Netherlands (2018)
Fremer, J.: Data Forensics, [Blogpost] (2011). https://www.fsbpt.org/FreeResources/NPTEArticles/articleType/ArticleView/articleId/40/Data-Forensics.aspx
Howell, S.L., Sorensen, D., Tippets, H.R.: The New (and Old) News about Cheating for Distance Educators (2016). https://www.researchgate.net/publication/268359500
Xquiry: XQUIRY Whitepaper 1.0. Xquiry, Amersfoort (2017)
Moher, D., Liberati, A., Tetzlaff, J., Altman, D.G.: Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 6(6), e1000097 (2009). https://doi.org/10.1371/journal.pmed1000097
Cassell, C., Denyer, D., Tranfield, D.: Using qualitative research synthesis to build an actionable knowledge base. Manag. Descision 44(2), 213–227 (2006)
McKenney, S., Reeves, T.C.: Conducting Educational Design Research. Routledge Education, New York (2012)
Piercy, K.W.: Analysis of semi-structured interview data (2004). https://www.scribd.com/document/249952429/Piercy-Analysis-of-Semi-structured-Interview-Data
Wools, S., Sanders, P.F., Eggen, T.J.H.M., Baartman, L.K.J., Roelofs, E.C.: Evaluatie van een beoordelingssysteem voor de kwaliteit van competentie-assessments [Testing an evaluation system for performance tests]. Pedagog. Stud. 88, 23–40 (2011)
Wohlin, C.: Guidelines for snowballing in systematic literature studies and a replication in software engineering (2014). http://dx.doi.org/10.1145/2601248.2601268
Wollack, J.A., Fremer, J.J.: Handbook of Test Security. Routledge, New York (2013)
Cizek, G.J., Wollack, J.A.: Handbook of Quantitative Methods for Detecting Cheating on Tests. Routledge, London (2017)
Kingston, N.M., Clark, A.K.: Test Fraud: Statistical Detection and Methodology. Routledge, New York (2014)
American Educational Research Association, American Psychological Association, and National Council for Measurement in Education: Standards for educational and psychological testing. American Educational Research Association, Washington DC (2014)
Oleck, J.: Most high school students admit to cheating. Sch. Libr. J. (2008). http://www.schoollibraryjournal.com/article/CA6539855.html
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van Ommering, C.J., de Klerk, S., Veldkamp, B.P. (2019). Getting to Grips with Exam Fraud: A Qualitative Study Towards Developing an Evidence Based Educational Data Forensics Protocol. In: Draaijer, S., Joosten-ten Brinke, D., Ras, E. (eds) Technology Enhanced Assessment. TEA 2018. Communications in Computer and Information Science, vol 1014. Springer, Cham. https://doi.org/10.1007/978-3-030-25264-9_13
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