Integrating Canvas Engagement Data and Student Evaluations of Teaching to Predict Academic Performance

• In Event: Virtual Poster Session
  In Virtual iPresentation Only: Division J - Section 2c: Assessing College Student Success and Impact Virtual Poster Session

Abstract

This study examines the relationship between student and faculty engagement with Canvas, students’ perceptions of instructional quality, and course performance across face-to-face, hybrid, and online instructional modes. Drawing on multiple data sources, including Canvas analytics, student evaluations of teaching (SETs), and institutional data, the study explores how specific engagement behaviors, such as login frequency, relate to students’ learning experiences and final course grades. Regression analyses reveal that student Canvas engagement and perceptions of instructional quality are positively associated with course performance across instructional modalities, while faculty Canvas engagement shows a more complex pattern. Findings underscore the value of integrating LMS data with SETs to inform instructional design, enhance student success, and guide data-driven decision-making in higher education.

Authors

• Qingmin Shi, University of Nevada - Las Vegas

• Shiloh Fling, University of Nevada - Las Vegas

• Tina Nelson, University of Nevada - Las Vegas