Designing Formative Assessment Through Multimodal Learning Analytics: Integrating Knowledge Tracing, Dashboards, and Epistemic Feedback in Higher Education
Keywords:
Epistemic Feedback Formative Assessment Higher Education Knowledge Tracing Learning Analytics Dashboards Multimodal Learning AnalyticsAbstract
Formative assessment remains central to higher education quality, yet many digital implementations still privilege summative grades over actionable knowledge representations that support teaching and learning. This narrative review synthesises research on multimodal learning analytics, knowledge tracing, learning analytics dashboards, and epistemic feedback as design resources for formative assessment in blended and online higher education. Drawing on learning sciences, educational data science, and assessment theory, the review maps how latent knowledge models, multimodal behavioural traces, and dialogic feedback processes can be aligned with Black and Wiliam's formative strategies. Evidence indicates that knowledge tracing and related learner models can externalise evolving mastery, that multimodal analytics can capture process evidence beyond clickstreams, and that dashboards and feedback analytics tools are most effective when they prompt reflection rather than merely display metrics. Persistent risks include opaque algorithms, equity harms, over-reliance on prediction, and weak pedagogical integration. The review proposes an integrative design framework linking evidence collection, knowledge representation, interpretive mediation, and instructional action, and identifies research priorities for transparent models, teacher and student feedback literacy, and culturally situated evaluation, especially in under-represented higher education systems.
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