Self-derivation through memory integration: clusters of precursor sub-processes.

Knowledge builds through direct experiences (e.g., teaching) and productive processes (e.g., analogy). There is variability in the specific productive process of self-derivation of new knowledge through integration of separate yet related episodes of new learning. The variability relates to each of...

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Detalles Bibliográficos
Publicado en:Memory Vol. 34; no. 3; pp. 329 - 349
Autores principales: Cronin-Golomb, Lucy M., Lee, Katherine A., Spradling, Greer E., Bauer, Patricia J.
Formato: pictorial research tables/charts Journal Article
Publicado: Taylor & Francis Ltd Mar2026
Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario:Knowledge builds through direct experiences (e.g., teaching) and productive processes (e.g., analogy). There is variability in the specific productive process of self-derivation of new knowledge through integration of separate yet related episodes of new learning. The variability relates to each of four hypothesised precursor sub-processes: encoding, reactivation, integration (all three for both children and adults), and selection (tested in children only). However, relations between each sub-process and self-derivation have been investigated in separate samples. As such, how they work together to support self-derivation is unknown. In the current research, we investigated all four sub-processes in samples of 7–11-year-olds (Study 1) and college-age adults (Study 2). In the child sample and in the combined sample of children and adults, encoding, reactivation, and integration each were found to relate to self-derivation; selection was not related to self-derivation. In the children sample and in the combined sample of children and adults, cluster analyses revealed two paths to successful self-derivation, one of which was more prompt-independent and the other seemingly was dependent on prompts. There also were two paths to unsuccessful self-derivation, both characterised by low success at encoding. The results provide new insight into sources of variability in self-derivation through memory integration.