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ADAPTER: A Conceptual Model of Category-Driven Analogical Retrieval
Lucas Raynal1, Emmanuel Sander1
1Université de Genève, Faculté de Psychologie et Sciences de L'education, Equipe IDEA, Genève, Switzerland.
Wiley Interdisciplinary Reviews. Cognitive Science
|May 15, 2025
Summary
Analogy-making retrieval depends on how situations are encoded, influenced by available categories. The ADAPTER model explains how encoding depth and context shape retrieval, impacting learning and transfer.
Area of Science:
- Cognitive Psychology
- Cognitive Science
- Psychology
Background:
- Analogy-making involves mapping structural similarities between situations.
- A key debate concerns whether memory retrieval relies on surface or structural similarities.
Purpose of the Study:
- To resolve the debate on determinants of analogical retrieval.
- To introduce a conceptual model (ADAPTER) explaining the influence of encoding on retrieval.
- To provide a unified account of prior findings and generate new empirical predictions.
Main Methods:
- Review of experimental evidence on analogical retrieval.
- Development of the ADAPTER (As Deep As Possible Target Encoding and Retrieval) model.
- Conceptual framework integrating encoding, categories, context, and retrieval.
Main Results:
- Analogical retrieval determinants are primarily influenced by situation encoding.
- Available categories modulate the level of abstraction during encoding.
- Encoding context and target description characteristics affect relational encoding and retrieval.
Conclusions:
- The ADAPTER model offers a unified explanation for analogical retrieval determinants.
- The model predicts future research directions and empirical outcomes.
- It provides insights into developmental changes in retrieval and suggests educational interventions for promoting spontaneous transfer.
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