An Immediate And Retrospective Analysis Of Stability And Change: Examining Students' Emotion And Motivation Profiles In Response To Outcome-Presenting Learning Analytics Dashboards

Read full text
Authors: Zhiqing Zheng, Marek Hatala, Arash Ahrar
Cited by: 1
References: 26

Abstract

Learning Analytics Dashboards (LADs) have been studied to support student learning and motivation, yet how their effects evolve or endure over time remains in question. This study examines students’ immediate and retrospective emotional and motivational responses to two types of outcome-presenting dashboards: a class-performance comparison dashboard (CP-D) and an individual-comparison dashboard (IC-D). Using a mixed-methods approach with survey data, clustering of Achievement Goal Orientations (AGOs), and qualitative analysis of student reflections, the study explores how emotions persisted or diminished across the semester. Results showed that emotions more strongly associated with perceived control (e.g., pride, hope) tended to persist, whereas those less tied to control (e.g., assurance, hopelessness) were less stable. Reductions in anxiety and disappointment emerged most clearly among Mastery-Oriented students, with other clusters showing little differences between dashboard conditions. Interestingly, IC-D supported hope even among some lower-performing Non-Competitive students, while CP-D anchored students more strongly to the class average. These findings underscore that dashboard design interacts with performance and motivational profiles, suggesting the need for adaptive and hybrid designs that balance comparative feedback with individualized progress indicators.

Fields of Study & Subjects

Online Learning and Analytics Intelligent Tutoring Systems and Adaptive Learning Student Assessment and Feedback

Publication details

Journal / source
Proceedings of the LAK26: 16th International Learning Analytics and Knowledge Conference
Publisher
ACM
Pages
480–490
Publication date
25 April 2026