Explicitly teach search-based heuristics and metacognitive skills using cognitive load techniques¶

Strategy · All strategies
Evidence · 2 claims (2 for) · 3 studies (2 quant-synthesis, 1 theoretical), q1–q4 · 2 of 3 report an effect size · 1 claim rests on one study

Description¶

The article recommends teaching general problem-solving heuristics and metacognitive skills as biologically secondary knowledge, using cognitive load theory techniques to reduce unnecessary working memory load. It suggests "explicit instruction that models the application of means-ends analyses in solving selected domain-specific problems that are genuinely new to learners," worked examples for novices, and metacognitive prompts for more experienced learners.

Design Implications¶

Context¶

Requirements¶

• Problems used for modeling the heuristic must be genuinely new to the learners; explicit examples suit novices while metacognitive prompts suit more experienced learners.

Constraints¶

• The article states these are hypothetical approaches that should be tested experimentally against traditional approaches with delayed post-tests of genuinely novel problem solving.

Target Learners¶

• novices and more experienced learners in domain-specific secondary-knowledge subjects

Target Learning Goals¶

• general problem-solving heuristics, metacognitive skills, novel problem-solving performance

Affordances¶

• Intelligent Natural Information Processing System

Claims¶

• General problem-solving heuristics used in controlled conscious problem solving are biologically secondary skills requiring explicit learning [+W]
• Strategy Instruction Improves Learning [+S]

Related Strategies¶

• Evaluate proposed instructional approaches with controlled experiments measuring far-transfer problem solving

Examples¶

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Key Sources¶

• Kalyuga, S. (2026). Instructional Implications of Evolutionary Perspective on Human Cognitive Architecture as an Intelligent Natural Information Processing System. Educational Psychology Review, 38, 33. https://doi.org/10.1007/s10648-026-10135-6