Expectations for supporting student engagement with learning analytics: An academic path perspective

https://doi.org/10.1016/j.compedu.2021.104192Get rights and content
Under a Creative Commons license
open access

Highlights

  • Qualitative user needs analysis on supporting student engagement.

  • Academic path perspective to examine continuums and prolonged student engagement.

  • Four different roles for LA to support behavioral, cognitive, emotional and agentic engagement.

  • Holistic understanding of student suppor with LA.

  • Aligning ethical issues of LA with the construct of student engagement.

Abstract

There has been a growing interest in higher education to explore how learning analytics (LA) could be used to support student engagement. Providing actionable feedback with LA for students is an emerging area of research. Previous studies have commonly focused on course-level aspects of supporting engagement with LA, but students' perspectives have received limited attention. This study analyzed pre-service teachers’ needs and expectations for LA to support student engagement on the academic path level, which means observing the continuum of study periods and academic years. Qualitative content analysis was conducted for video-recorded student small-group conversations to analyze in-depth how pre-service teachers (N = 40) described their needs for support student engagement and expectations and ethical concerns for using LA tools. Students suggested that LA tools could support their engagement by mediating information between the student and institution, facilitating effective studying, increasing awareness about themselves as learners, providing help and support in different challenging situations, and working as a feedback channel to adapt the learning conditions according to their individual needs. The results of this study demonstrate how student needs are sometimes contradictory, for example when students suggest more possibilities for agentic choices on their studies, but similarly more institutional monitoring or their study progression. This offers insights to clarify specific objectives for supporting student engagement with LA.

Keywords

Data science applications in education
Human-computer interface
Pedagogical issues

Cited by (0)