Paper Info
Title
Fraud Detection in Statistics Education Based on the Compendium Platform and Reproducible Computing
Abstract
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.
Year
DOI
Venue
2009
10.1109/CSIE.2009.710
Computer Science and Information Engineering, 2009 WRI World Congress
Keywords
Field
DocType
computer aided instruction,fraud,mathematics computing,statistics,Compendium platform,e-learning environment,fraud detection system,nonrote learning,pedagogical framework,pedagogical issues,reproducible computing,social constructivism,statistical concepts,statistics education,undergraduate statistics course,fraud detection,reproducible computing,social networks,statistics education
Data science,Population,Computer aided instruction,Social network,Statistics education,Compendium,Computer science,Social constructivism,Artificial intelligence,Free riding,Cheating,Machine learning
Conference
Volume
ISBN
Citations 
3
978-0-7695-3507-4
0
PageRank 
References 
Authors
0.34
5
2
Name
Order
Citations
PageRank
Patrick Wessa111.07
Bart Baesens22511145.52