Kalyuga's Self-Regulation of Cognitive Load
Updated 2026-08-10
INTRODUCTION
English translation pending.
CORE DEFINITION
Slava Kalyuga proposed a framework in which learners self-regulate cognitive load. The central claims are that learners can perceive their own load through metacognitive monitoring, that they adjust strategy according to the load they perceive, and that the level of load supporting learning depends on prior knowledge. The expertise reversal effect is the key consequence: instructional methods that work well for novices, such as fully worked examples and detailed guidance, can hinder experts, because the guidance is redundant with knowledge they already hold and consumes working memory the task needs. The framework requires instruction to adapt to expertise.
SCAFFOLDING EFFECT
Reduce cognitive load
- Use load check: rate your mental effort mid-task and treat a high rating as a signal to change approach. - Use guidance fading: withdraw worked steps as competence grows rather than keeping support constant. - Use level matching: choose support intensity from measured prior knowledge, not from a default design.
Anchor fast decisions
Working memory is limited, and instructional support occupies part of it. For a novice, that support carries information the learner does not have, so the trade is worthwhile. For an expert, the same support restates knowledge already stored in long-term memory, so it adds load without adding information and interferes with the processing the task requires. Because the cost of guidance depends on what the learner already knows, the same design can help one group and hinder another.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
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Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/Cognitive_loadverified
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