Abstract
Prevention is better than cure, especially for the increase in cases of cheating during online exams where concrete evidence is hard to find and detailed investigations are costly and stressful. To complement video monitoring and restricting access to forbidden resources, we developed a flexible yet scalable methodology, called E-Quiz, for programmable online examination (POE) with extensive modular randomization (EMR) of questions. E-Quiz has been successfully integrated with existing LMS via LTI, serving multiple courses at ease with 300 or more students simultaneously taking an online on/off-campus exam. In particular, we successfully applied EMR to eliminate cheating for a graduate-level Data Mining course. The question templates and package developed can be extended further to other courses. Moreover, we have simplified the system deployment process to enhance support for E-Quiz exams and shared the relevant projects. Individual educators can effortlessly establish their own customized E-Quiz system for their courses with our projects, benefitting from convenient management and optimized performance. © 2023 IEEE.
| Original language | English |
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| Title of host publication | 2023 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE) |
| Publisher | IEEE |
| Number of pages | 8 |
| ISBN (Electronic) | 978-1-6654-5331-8 |
| ISBN (Print) | 978-1-6654-5332-5 |
| DOIs | |
| Publication status | Published - Nov 2023 |
| Event | 11th IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE 2023) - Auckland, New Zealand Duration: 28 Nov 2023 → 1 Dec 2023 |
Conference
| Conference | 11th IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE 2023) |
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| Abbreviated title | IEEE TALE 2023 |
| Place | New Zealand |
| City | Auckland |
| Period | 28/11/23 → 1/12/23 |