Los Angeles, CA
March 31, 2009 to April 2, 2009
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSIE.2009.710
This paper focuses on a newly developed method to detect fraud in empirical papers that are submitted by students. The proposed solution is based on the Compendium Platform and Reproducible Computing which allows the educator to build e-learning environments that are embedded in the pedagogical framework of social constructivism and which can be shown to be effective in terms of non-rote learning of statistical concepts. The paper addresses the technological aspects of the proposed fraud detection system, ways to discriminate between various types of fraud (plagiarism, free riding, data tampering, peer-review cheating), and the pedagogical issues that result from its implementation (responsibility, non-rote learning). Finally, the first experiences about the implementation of the proposed technology in an undergraduate statistics course (with a large student population) are illustrated.
fraud detection, statistics education, reproducible computing, social networks
Patrick Wessa, Bart Baesens, "Fraud Detection in Statistics Education Based on the Compendium Platform and Reproducible Computing", CSIE, 2009, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009, pp. 50-54, doi:10.1109/CSIE.2009.710