Claims

College students who overestimate their pretest retrospective judgments engage less in preparatory metacognitive strategies before quizzes in computer-based learning environments

Claim · All claims
Evidence · 1 study · associational r? · q2
Currency · newest study 2025 · not yet checked against its sources · not reviewed by a person

Subclaims

Reading the evidence codes

q is the design tier, i the impact, n the sample, and the kind with its r the rigour judged within that kind: what each code means.

This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.

q2 i? Higher pretest calibration discrepancy (overconfidence) is associated with less engagement in preparatory metacognitive actions before quizzes. → HaeJin Lee · Nigel Bosch 2025

Evidence

HaeJin Lee · Nigel Bosch 2025

HaeJin Lee · Nigel Bosch. (2025). Calibration Discrepancy Predicts Students’ Subsequent Metacognitive Strategy Use in Computer-based Learning Environments. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-025-00514-5

q2 · i? · associational · r?

Observational regression analysis of trace data from 210 college students in a self-paced web-based statistics environment found "Students who overestimated their pretest retrospective judgments engaged less in metacognitive strategies", with overconfidence measured as estimated minus actual pretest grade.

"Students who overestimated their pretest retrospective judgments engaged less in metacognitive strategies, particularly in preparatory actions before quizzes ( b = -9.100, p < .001)."

Discussion

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