Dispositional factors add little to predicting inquiry performance except physics self-concept, and extraneous load has a significant negative effect¶

Claim · All claims
Evidence · 1 study (2 entries) · associational r2 · q3
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q3 i? A more positive physics self-concept was associated with better inquiry performance, but adding all dispositional variables did not increase overall explanatory power. → Gerdesmann 2026 q3 i? Extraneous cognitive load showed a significant negative effect on inquiry performance, adding 5% explained variance beyond cognitive and dispositional blocks. → Gerdesmann 2026 (2)

Evidence¶

Gerdesmann 2026¶

Gerdesmann, D., Schwichow, M., & Koerber, S. (2026). Factors that explain simulation-based inquiry performance in physics learning. Instructional Science. https://doi.org/10.1007/s11251-026-09806-2

q3 · i? · associational · r2

Block 2 of the hierarchical multiple regression added interest, self-concept, personality dimensions, and current motivation. Only "A more positive phys-ics self-concept was associated with better performance"; dispositional measures as a set added no explanatory power.

"A more positive phys-ics self-concept was associated with better performance, although including dispositional measures did not increase the model's overall explanatory power."

Gerdesmann 2026 (2)¶

Gerdesmann, D., Schwichow, M., & Koerber, S. (2026). Factors that explain simulation-based inquiry performance in physics learning. Instructional Science. https://doi.org/10.1007/s11251-026-09806-2

q3 · i? · associational · r2

Block 3 of the hierarchical regression added cognitive load measures, with a "significant negative effect of extraneous load on inquiry performance" and 5% additional explained variance. No effect size is printed for the extraneous load coefficient.

"The final model (block 3, orange) added intrinsic and extraneous cognitive load, revealing a significant negative effect of extraneous load on inquiry performance and producing an additional 5% increase in explained variance."

Discussion¶

Learner Variables¶

• Academic Self-Concept — predictor: learners who differ on it differ in outcomes

Related Claims¶

• Latent profile analysis identifies three learner profiles differing in cognitive factors, self-concept, and extraneous load, with significant performance differences — related
• Content knowledge does not significantly predict the number of experiments conducted; general cognitive ability shows a quadratic association and self-concept a negative linear association — related
• CVS skill is the strongest predictor of performing valid (unconfounded) experiments in simulation-based inquiry — related
• Cognitive factors explain about 49% of variance in simulation-based inquiry performance among young adults — related
• Student characteristics beyond prior knowledge bear on inquiry learning: inhibitory control predicts inquiry outcomes, and in one study a direct-instruction advantage over inquiry held only for students with low domain self-concept — related