In an Era of Online Learning, New Testing Approach Intends to Minimize Cheating

The era of widespread long-distance learning caused by the COVID-19 pandemic needs online testing methods that efficiently avert cheating, specifically in the form of cooperation amongst pupils. With worry about cheating rising across the United States, a solution that preserves students’ privacy is particularly beneficial.

In research published on March 1st in npj Science of Discovering, engineers from Rensselaer Polytechnic Institute show how a testing strategy they call “distanced online testing” can successfully reduce students’ capacity to obtain assistance from each other to score higher on a test taken at home throughout social distancing.

“Frequently in remote online examinations, students can talk over the phone or net to discuss responses,” said Ge Wang, an endowed chair professor of biomedical engineering at Rensselaer and the corresponding author on this paper. “The focal idea of our method is to lessen this possibility through discrete optimization helped by knowledge of a student’s expertise.”

Students will obtain the same questions during the distanced online test, but at differing times depending on their ability degree. For example, students of the highest mastery degrees get each question after other trainees have answered those questions. This method, Wang claimed, lowers the incentive for students to get help from those with a lot more proficiency in the subject. In order to figure out the order of each student’s questions, their skills levels are approximated utilizing their grade point averages, SAT scores, or midterm scores, relying on what is readily available at a particular point in the semester.

This method lowered the points obtained through collusion by orders of magnitude compared to standard test methods according to analytical tests and post-exam surveys. As an extra benefit, Wang said, when students knew collusion would not be possible, they were more inspired to study class material. Wang and also his collaborators hope to share this pedagogical advancement beyond the Rensselaer campus.

“We plan to create a good platform so that others can conveniently use this method,” stated Wang, a participant of the Facility for Biotechnology and Interdisciplinary Studies at Rensselaer.

Originally published by Rensselaer Polytechnic Institute. Read the original article.

Reference: Mengzhou Li, Lei Luo, Sujoy Sikdar, Navid Ibtehaj Nizam, Shan Gao, Hongming Shan, Melanie Kruger, Uwe Kruger, Hisham Mohamed, Lirong Xia, Ge Wang. Optimized collusion prevention for online exams during social distancing. npj Science of Learning, 2021; 6 (1) DOI: 10.1038/s41539-020-00083-3