Integrating behavioral trace data with outcomes and self-report reveals feedback effects that perception and performance measures alone miss¶

Claim · All claims
Evidence · 1 study · causal r2 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? The authors argue behavioral data captured engagement differences that would have been overlooked if only perceptions and performance had been measured. → Jae-Eun Russell 2026

Evidence¶

Jae-Eun Russell 2026¶

Jae-Eun Russell, Anna-Marie Smith, Salim George, Adam Brummett. (2026). Impact of learning analytics-based personalized feedback: an experimental study on student behavior in a large introductory STEM course. Education Tech Research Dev. https://doi.org/10.1007/s11423-026-10728-6

q2 · i? · causal · r2

Authors' interpretation from the Discussion of the randomized study: without behavioral trace data, "conclusions would have been limited to perceptions and performance outcomes, potentially overlooking important engagement differences." This is an interpretive argument, not a separately tested result.

"Behavioral data provided insights into engagement patterns that would not have been captured through perception measures alone."

Discussion¶

Related Claims¶

• Self-report measures of SRL capture perceptions of strategy use rather than implementation quality, and a combined trace-data approach may be best — possibly the same claim (merge candidate)
• Traditional self-report methods face significant limitations in capturing the dynamic nature of SRL — a broader claim this one bears on
• Questionnaire data may capture learners' perceptions rather than the strategies they actually performed — related
• Metacognition assessment is shifting from self-report questionnaires toward process-oriented multimodal methods, which face validity and data-alignment challenges — a broader claim this one bears on