Develop online measures of students' strategy use, linking learning analytics with retrospective task reports¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The commentary recommends that researchers continue developing new kinds of measure, including online measures of both self-regulated learning and approaches to learning, because questionnaire responses about how students normally study are based on inferences and reconstructions derived from subjective implicit theories. It proposes that learning analytics can monitor students' strategic decisions in online environments in minute detail and in real time, and that linking this technology to retrospective reports of just-completed tasks could cross-fertilize the learning pattern approach with accounts of strategic processing.

Design Implications¶

Context¶

Requirements¶

• Requires linking learning analytics technology to the collection of students' retrospective reports regarding how they have just carried out specific learning tasks

Constraints¶

• Retrospective reports are informative only about recently completed specific tasks, per Ericsson and Simon's conclusion that such reports are accurate because based on representations in recent memory

Target Learners¶

• higher education students
• distance-learning students

Target Learning Goals¶

• measuring and understanding students' use of learning strategies and approaches to learning

Related Strategies¶

• Test whether student learning concepts and findings hold in online environments, and relate higher education curricula to secondary curricula
• Embed SRL supports in digital and AI-enhanced learning environments, grounded in solid SRL theory
• Use multi-method, multi-timing measurement and subscale-level correlational analysis when evaluating metacognition

Examples¶

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Key Sources¶

• John T. E. Richardson. (2017). Student Learning in Higher Education: a Commentary. Educational Psychology Review, 29, 353–362. https://doi.org/10.1007/s10648-017-9410-x