Nudging student learning strategies using formative feedback in automatically graded assessments

Abstract

Automated assessment tools are widely used as a means for providing formative feedback to undergraduate students in computer science courses while helping those courses simultaneously scale to meet student demand. While formative feedback is a laudable goal, we have observed many students trying to debug their solutions into existence using only the feedback given, while losing context of the learning goals intended by the course staff. In this paper, we detail two case studies from second and third-year undergraduate software engineering courses indicating that using only nudges about where students should focus their efforts can improve how they act on generated feedback. By carefully reasoning about errors uncovered by our automated assessment approaches, we have been able to create feedback for students that helps them to revisit the learning outcomes for the assignment or course. This approach has been applied to both multiplechoice quizzes and automated programming assessment. We have found that student performance has not suffered and that students reflect positively about how they investigate automated assessment failures.

Does personality matter: examining the value of personality insights for personalized nudges that encourage the selection of learning resources

“…This resonates with our selection, as our Opinion Leader nudges utilize the behavior of well-known healthcare organizations as role models to motivate learners, acknowledging the positive impact that such influencers can have on behavior without undermining autonomy. In addition to the insights from Van Roekel ( 2023 ), Zamprogno et al ( 2020 ) examined the use of nudges in computer science courses to improve student learning strategies, which supports our approach to utilizing Feedback and Self-commitment nudges. Zamprogno et al ( 2020 ) demonstrated that carefully designed nudges about where students should focus their efforts can enhance how students act on generated feedback, effectively preserving their autonomy while aligning their actions with the learning goals intended by the course staff.…”

“…In addition to the insights from Van Roekel ( 2023 ), Zamprogno et al ( 2020 ) examined the use of nudges in computer science courses to improve student learning strategies, which supports our approach to utilizing Feedback and Self-commitment nudges. Zamprogno et al ( 2020 ) demonstrated that carefully designed nudges about where students should focus their efforts can enhance how students act on generated feedback, effectively preserving their autonomy while aligning their actions with the learning goals intended by the course staff. By considering these findings alongside the autonomy-preserving framework of Van Roekel ( 2023 ), our study aimed to contribute to the evolving understanding of how autonomy-respecting nudging can positively impact students' engagement with educational resources.…”

Two-sided Long Tails on Blockchain-Based Crowdsourcing Platforms

“…In other words, the feedback nudges place targets in a favorable context, encouraging them to make a right decision (Purohit & Helme-Guizon, 2020). For example, employing feedback intervention to increase password strength (Zimmermann & Renaud, 2021) and improve learning (Zamprogno et al, 2020). In the context of digital well-being, recently, Purohit and Holzer (2021) employed the feedback nudges that nudged users after 1 minute of using the app, followed by feedback every minute thereafter.…”

Automated Grading and Feedback Tools for Programming Education: A Systematic Review

“…While some AATs focus on the three major language paradigms, other AATs focus on grading more specific areas, such as web-based languages [158,171,194], graphics development [77,78,151,191], kernel development and assembly languages [103,150,162], or query languages [186].…”