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- Vol 5 RE: Chapters 12, App C
formative assessmentlearning analyticsfeedback processeslearning intentionsevidence elicitationself-assessmentinstructional decision-makingJournal article Evidence summaryAt a glance
Banihashem and colleagues systematically review 93 studies published from 2011 to 2023 to examine how learning analytics supports formative assessment.
Key ideas
Their coding framework combines three actors—teachers, peers, and learners as self-assessors—with three questions: where learning is going, where it is now, and how to move forward. The review finds that analytics can clarify goals, diagnose current understanding, and support feedback or instructional action, but coverage across the framework is uneven. A central concern is alignment: dashboards or predictions are useful only when their outputs connect to a defensible model of formative assessment and can be interpreted and acted upon.
Why it matters
For educators and designers, the study recommends building analytics around learning intentions, evidence elicitation, feedback processes, and concrete decisions rather than treating data visualisation as formative assessment by itself.
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Edition abbreviations
- TE
- Teacher Edition
- PE
- Practice Edition
- RE
- Research Edition
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