Utilizing an LMS-based feedback repository to encourage continuous student action and feedback uptake

Lovemore Chirubvu; Fanuel Muzerengi

doi:10.51574/hamka.v4i1.115

Authors

Lovemore Chirubvu
lchirubvu@sociol.uz.ac.zw
Department of Community and Social Development, Faculty of Social and Behavioural Sciences, University of Zimbabwe, Harare, Zimbabwe
Fanuel Muzerengi d

Keywords:

Feedback literacy, Formative assessment, Feedback uptake, Learning Management System (LMS), Higher education

Abstract

Purpose: This study addresses persistent student non-engagement and mark-centric behaviors by evaluating how a centralized Learning Management System (LMS) feedback repository promotes continuous feedback uptake, dialogic feed-forward processes, and learner agency.

Method: Employing a sequential explanatory mixed-methods design, data were gathered from undergraduate and postgraduate students alongside academic staff across several faculties. Automated LMS interaction analytics, DEFT-adapted survey instruments, revision logs, student focus groups, and staff reflections were analyzed using repeated-measures ANOVA, linear regression, and thematic analysis.

Findings: Repository implementation significantly increased feedback read duration, revisitation frequency, and action plan submissions. Low-performing students exhibited a substantial surge in feedback revisitation after completing required action prompts. Student feedback literacy scores improved markedly across all dimensions, with repository engagement serving as a significant positive predictor of subsequent academic achievement.

Practical implications: The study offers higher education educators and curriculum designers a scalable, technology-mediated framework to disentangle numeric grades from feedback commentary, fostering self-regulated learning and actionable feedback literacy within blended learning environments.

Originality/value: This research provides novel empirical evidence on how centralizing multi-source feedback—integrating peer, teacher, and AI-generated insights within LMS architecture—converts episodic commentary into longitudinal feedback spirals.

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