Feedback
Adaptive digital feedback and self-regulated learning
Open access · cc by · source: Europe PMC
A semester-long mixed-methods study found task enjoyment and personalized adaptive feedback central to how university students plan and regulate learning with a digital tool.
How this study connects
Role on claims
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Task enjoyment and personalized adaptive feedback appear central to how university students plan and regulate learning with a digital tool.
Evidence for the claim as stated.
Personalized adaptive feedback through a digital tool shapes how university students integrate guidance into planning and learning actions.
Evidence for the claim as stated.
Study at a glance
- Design
- Other — Concurrent mixed-methods: quantitative adaptive-feedback trial plus qualitative data
- N
- N=33 · Mean age 26.3 (SD 3.89) university students
- Population
- University students using a digital tool with adaptive feedback
- Outcome
- Learning outcomes under adaptive digital feedback
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Inspect source passages
Adaptive digital feedback and self-regulated learning
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What SRL phases structure the study’s view of learning?
pre-actional, actional, and post-actional phase
What did the study aim to understand about feedback?
adaptive feedback on students’ SRL
Key findings
Quantitative and qualitative strands converged on task-related enjoyment as an important prerequisite for pre-actional planning, with personalized feedback shaping how students integrated guidance into learning actions. The study maps SRL across pre-actional, actional, and post-actional phases in a digital setting.
Methodology
Researchers embedded an adaptive learning tool (“studybuddy”) in a Swiss university methods course and followed students over a semester using a convergent parallel mixed-methods design. Quantitative SRL measures (n=33) were integrated with qualitative evidence on how learners perceived and used adaptive feedback across SRL phases.
Limitations
Authors note the lack of a control group, so effects cannot be definitively attributed to the tool. The small single-course sample limits generalizability beyond this higher-education context.
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