Detecting excessive similarity in answers on multiple choice exams
| dc.contributor.author | Wesolowsky, George O. | en_US |
| dc.contributor.author | McMaster University, Michael G. DeGroote School of Business | en_US |
| dc.date.accessioned | 2014-06-17T20:36:59Z | |
| dc.date.available | 2014-06-17T20:36:59Z | |
| dc.date.created | 2013-12-23 | en_US |
| dc.date.issued | 1999-10 | en_US |
| dc.description | <p>23 leaves : ; Includes bibliographical references (leaves 21-22). ; "October, 1999".</p> | en_US |
| dc.description.abstract | <p>This paper provides a simple and robust method for detecting cheating. Unlike some methods, non-cheating behaviour and not cheating behaviour is modelled because this requires the fewest assumptions. The main concern is the prevention of false accusations. The model is suitable for screening large classes and the results are simple to interpret. Simulation and the Bonferroni inequaltty are used to prevent false accusation due to 'data dredging'. The model has received considerable application in practice and has been verified through the adjacent seating method.</p> | en_US |
| dc.identifier.other | dsb/30 | en_US |
| dc.identifier.other | 1029 | en_US |
| dc.identifier.other | 4944050 | en_US |
| dc.identifier.uri | http://hdl.handle.net/11375/5570 | |
| dc.relation.ispartofseries | Research and working paper series (Michael G. DeGroote School of Business) | en_US |
| dc.relation.ispartofseries | no. 442 | en_US |
| dc.subject | Business | en_US |
| dc.subject | Business | en_US |
| dc.subject.lcc | Cheating (Education) Multiple-choice examinations | en_US |
| dc.title | Detecting excessive similarity in answers on multiple choice exams | en_US |
| dc.type | article | en_US |
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