In medical simulation training, socially shared regulation relates to subsequent emotional stabilization, with electrodermal activity modeled as a dependent variable¶

Claim · All claims
Evidence · 1 study (2 entries) · associational r? · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? An empirical study in high-fidelity medical simulation combined behavioral coding of individual and socially shared regulatory strategies with electrodermal activity data, using supervised machine learning to link regulatory behaviors to physiological arousal. → Tina Seufert 2026 q2 i? Analyzing patterns across activity phases revealed that socially shared regulation relates to subsequent emotional stabilization. → Tina Seufert 2026 (2)

Evidence¶

Tina Seufert 2026¶

Tina Seufert. (2026). Transforming Self-regulated Learning – Multimodal Insights and Future Directions. Educational Psychology Review. https://doi.org/10.1007/s10648-026-10119-6

q2 · i? · associational · r?

The discussion paper describes the Moreno et al. (2025) study drawing on data from high-fidelity medical simulation settings, combining behavioral coding of regulatory strategies with EDA and using supervised machine learning to link regulatory behaviors to physiological arousal. EDA is positioned as a dependent variable, not a predictor.

"combine behavioral coding of individual and socially shared regulatory strategies with physiological data, specifically electrodermal activity (EDA)."

Tina Seufert 2026 (2)¶

Tina Seufert. (2026). Transforming Self-regulated Learning – Multimodal Insights and Future Directions. Educational Psychology Review. https://doi.org/10.1007/s10648-026-10119-6

q2 · i? · review · r2

The discussion paper reports that Moreno et al. analyzed patterns across distinct phases of activity rather than relying solely on static markers, revealing how socially shared regulation relates to subsequent emotional stabilization. No effect sizes are printed.

"Rather than relying solely on static markers, Moreno et al. (2025) analyze patterns across distinct phases of activity, revealing how socially shared regulation relates to subsequent emotional stabilization."

Discussion¶

Learner Variables¶

• Affect Regulation — predictor: learners who differ on it differ in outcomes

Related Claims¶

• Patterns of SRL and SSRL behaviors among medical trainees predict electrodermal activity at distinct stages of high-fidelity simulation training — possibly the same claim (merge candidate)
• SRL 'Evaluation' strategy codes differ between the 'Beginning' and 'Peak' segments of medical simulations — related
• SSRL 'Facilitation' codes differ between the 'Beginning' and both the 'Escalation' and 'Peak' segments of medical simulations — related
• SRL 'Execution' strategy codes differ between the 'Beginning' and both the 'Escalation' and 'Peak' segments of medical simulations — related
• In case examples, leaders and team members showed markedly different average peaks-per-segment EDA values during the same simulation segments — related