SRL skills and prior knowledge predict revision performance, while SRL predicts higher and prior knowledge lower cognitive load¶

Claim · All claims
Evidence · 1 study · causal r2 · q3
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q3 i? In robust main-effects models, SRL skills and pretest CSEM score positively predicted revision performance; SRL positively and pretest CSEM negatively predicted cognitive load; GenAI experience was only marginally significant for revision performance. → Huang 2026

Evidence¶

Huang 2026¶

Huang, B., Xie, L., Liu, Y., Liu, X., Tang, H., Feng, X., Qiao, C., Guo, Q., Wu, C., & Bao, L. (2026). From answer machine to collaborative partner: impact of structured generative AI training on scientific problem solving in STEM education. International Journal of STEM Education. https://doi.org/10.1186/s40594-026-00652-9

q3 · i? · causal · r2

Robust main-effects model for revision performance (pseudo R² = 0.580) with group as covariate. For cognitive load (pseudo R² = 0.187), SRL skills positively (β = 2.067, p < 0.01) and pretest CSEM negatively (β = -2.163, p < 0.001) predicted load; GenAI experience did not (p = 0.752).

"SRL skills had a significant positive effect ( β = 2.556, 95% CI [0.791, 4.516], p < 0.01). The pretest CSEM score had a significant positive effect (β = 7.513, 95% CI [5.718, 9.514], p < 0.001). GenAI experience had a marginally significant positive effect (β = 1.349, 95% CI [-0.234, 2.935], p = 0.100)"

Discussion¶

Learner Variables¶

• Prior Knowledge — predictor: learners who differ on it differ in outcomes

Related Claims¶

• Structured GenAI scaffolding training raises sophomore STEM students' posttest CSEM electromagnetism scores over problem-solving training (d = 0.81) — related
• GenAI training leaves total cognitive load comparable while marginally raising intrinsic cognitive load — related
• GenAI training attenuates the predictive effect of prior GenAI experience on revision performance — related
• GenAI effects on externally assessed learning are highly heterogeneous and conditional on prior knowledge, scaffolding, verification, and task design, with pooled effects unstable under publication-bias correction — related
• ADA use shows a modest non-significant tendency toward increased intrinsic and extrinsic cognitive load, contrary to prior chatbot research — related
• Sequence of worked examples and problems had no significant effect on self-reported cognitive load, but higher prior knowledge was associated with lower load in experimental design — related
• Higher extraneous cognitive load predicted lower post-test scores after controlling for prior knowledge — related
• Revisions to visuals had no effect on post-lesson test scores, though prior knowledge predicted performance — related
• Intrinsic cognitive load during the scenario negatively predicted problem-solving performance (ANCOVA, p = .01) — related