Using Data Analytics to Detect Possible Collusion in a Multiple Choice Quiz Test
Abstract
This paper reports on the experiences of using an on-line MCQ test to assess students’ knowledge for a postgraduate module. Because of the COVID-19 pandemic, the test was taken in a remote non-proctored environment. Although it was executed under timed conditions with students seeing questions in a randomised order, algorithmic analysis of the response patterns suggests that collusion occurred during the test. Practical implications for assessment design and administration are discussed.
Origin | Files produced by the author(s) |
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