From Data Generators to Beneficiaries: Impacts of Learning Analytics on Student Learning

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Authors: Rosa Junghwa Hong, Sara N. Pagliaro, Ivan Chow
Cited by: 0

Abstract

This paper examines the transformative potential of Learning Analytics (LA) in higher education, with a focus on how student-generated data can enhance student learning experiences. Using the University of Toronto’s implementation of the Canvas Learning Management System (LMS), we investigated an opt-in tool called the Student Learning Mastery Gradebook (SLMG), which can align a course’s learning outcomes with online assessments. We explored the affordance of LA on student performance and attitudes towards learning and learner autonomy using SLMG. Our mixed-method study, conducted in a second-year online English Grammar course, examined the potential for effective use of LA in university settings, especially for students. The results of this preliminary experimentation reveal insights into the benefits and challenges of LA use at the instructional level and in curricular design, emphasizing the need for further research into more ethical and student-centered approaches in institutional uses of LA.

Fields of Study & Subjects

Online Learning and Analytics Intelligent Tutoring Systems and Adaptive Learning Educational Technology and E-Learning

Publication details

Journal / source
Nouvelle Revue Synergies Canada
Volume
2025
Issue
19
Pages
1–17
Publication date
16 January 2026
Language
EN