Research Projects

This paper explores the combination of multiple attempts on assessments with immediate feedback through the LMS. The data reveals that students who do not earn an A are likely to use additional attempts and they tend to do better on future attempts.

Feedback best practices suggest that timely, specific, and actionable feedback is provided, with the option to apply the feedback. We used a learning management system to deliver assessments with automatic feedback provided at the conclusion of the assessment, allowing for multiple attempts in order to apply the knowledge gained. Questions were pooled so each attempt was unique, the highest score earned was awarded, and there was no penalty for failure to take advantage of multiple attempts. We found that students who did not earn an A on their first attempt were more likely to opt to try again. Those that did so tended to score better on their second attempt. This leads us to conclude that assessment design with multiple attempts that incorporates feedforward influences student behaviour. Understandably, students who used multiple attempts invested more time on the assessment; this time investment did not correlate to better performance, but time on task on the first attempt was also not a predictor of mastery, either. Future work will include additional STEM general education courses in a broader study and a survey of student opinions regarding the utility of the feedback and the option for multiple attempts.