Please use this identifier to cite or link to this item:
http://hdl.handle.net/11375/5570| Title: | Detecting excessive similarity in answers on multiple choice exams |
| Authors: | Wesolowsky, George O. McMaster University, Michael G. DeGroote School of Business |
| Keywords: | Business;Business |
| Publication Date: | Oct-1999 |
| Series/Report no.: | Research and working paper series (Michael G. DeGroote School of Business) no. 442 |
| 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> |
| Description: | <p>23 leaves : ; Includes bibliographical references (leaves 21-22). ; "October, 1999".</p> |
| URI: | http://hdl.handle.net/11375/5570 |
| Identifier: | dsb/30 1029 4944050 |
| Appears in Collections: | DeGroote School of Business Working Paper Series |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| fulltext.pdf | 574.64 kB | Adobe PDF | View/Open |
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