What question did this study set out to answer?

This study investigates how self-regulated learning processes interact within game-based learning environments and their effects on learning outcomes.

July 5, 2026British Journal of Educational TechnologyOpen Access

A balance between stability and flexibility: Adaptive patterns of self‐regulated learning processes shape game‐based learning

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Authors

ECElizabeth B. Cloude SHS Huber JWJingwei Wei

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Overview

Randomized trial shows the impact of self-regulated learning processes on learning outcomes in adults, suggesting optimal regulation strategies for game-based learning.

Key Points

This study investigates how self-regulated learning processes interact within game-based learning environments and their effects on learning outcomes.
Analyzed interactions among cognitive, affective, metacognitive, and motivational processes during game-based learning.
Employed think-aloud and emote-aloud techniques to assess CAMM states alongside physiological measures.
Utilized sequence analysis and transfer entropy to evaluate regulatory patterns and their impact on learning.
Found a quadratic relationship between turbulence of cognitive and affective state transitions and learning variability (31% explained).
Demonstrated that adaptive regulation of CAM processes enhanced learning gains.
Physiological measures of motivation were not predictive of learning performance.

Cite This Study

Cloude et al. (2026) studied this question.

synapsesocial.com/papers/6a49f754f5d1d45b288014a3 https://doi.org/10.1111/bjet.70077

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July 5, 2026British Journal of Educational TechnologyOpen Access

A balance between stability and flexibility: Adaptive patterns of self‐regulated learning processes shape game‐based learning

View Full Paper

Ask AI

Bookmark

Authors

ECElizabeth B. Cloude SHS Huber JWJingwei Wei

Discussion

Member takes

Overview

Randomized trial shows the impact of self-regulated learning processes on learning outcomes in adults, suggesting optimal regulation strategies for game-based learning.

Key Points

This study investigates how self-regulated learning processes interact within game-based learning environments and their effects on learning outcomes.
Analyzed interactions among cognitive, affective, metacognitive, and motivational processes during game-based learning.
Employed think-aloud and emote-aloud techniques to assess CAMM states alongside physiological measures.
Utilized sequence analysis and transfer entropy to evaluate regulatory patterns and their impact on learning.
Found a quadratic relationship between turbulence of cognitive and affective state transitions and learning variability (31% explained).
Demonstrated that adaptive regulation of CAM processes enhanced learning gains.
Physiological measures of motivation were not predictive of learning performance.

Cite This Study

Cloude et al. (2026) studied this question.

synapsesocial.com/papers/6a49f754f5d1d45b288014a3 https://doi.org/10.1111/bjet.70077

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