Example-Generation Tasks for Computer-Aided Assessment in University Mathematics Education: Insights From A Study Conducted in Two Educational Contexts

Abstract

In recent decades, there has been rapid development in digital technologies for automated assessment. Through enhanced possibilities in terms of algorithms, grading codes, adaptivity, and feedback, they are suitable for formative assessment. There is a need to develop computer-aided assessment (CAA) tasks that target higher-order mathematical skills to ensure a balanced assessment approach beyond basic procedural skills. To address this issue, research suggests the approach of asking students to generate examples. This study focuses on an example-generation task on polynomial function understanding, proposed to 205 first-year engineering students in Sweden and 111 first-year biotechnology students in Italy. Students were encouraged to collaborate in small groups, but individual elements within the tasks required each group member to provide individual answers. Students' responses kept in the CAA system were qualitatively analyzed to understand the effectiveness of the task in extending the students’ example space in diverse educational contexts. The findings indicate a difference in students’ example spaces when performing the task between the two educational contexts. The results suggest key strengths and possible improvements to the task design.