Both cognitive and educational psychology literature strive to investigate human category and concept learning. However, both literatures focus on different phenomena and often use different methodologies. We identify and discuss commonalities and differences between the literatures. This literature comparison reveals that research on relational category learning offers a promising avenue to integration. We suggest that this integration would be especially beneficial to advance our understanding of conceptual change essentially, how complex scientific concepts and categories are acquired and developed in educational contexts elaborating or correcting students' prior conceptions. Furthermore, the focus on relational categories allows us to provide an integrative discussion on how recent lines of research on analogy, memory and category learning, and knowledge restructuring relate to and can inform education. In general, this article advocates the complementary nature of cognitive and educational psychology and identifies viable, and potentially synergistic paths for future research. (PsycINFO Database Record
We investigated the understanding of causal systems categories-categories defined by common causal structure rather than by common domain content-among college students. We asked students who were either novices or experts in the physical sciences to sort descriptions of real-world phenomena that varied in their causal structure (e.g., negative feedback vs. causal chain) and in their content domain (e.g., economics vs. biology). Our hypothesis was that there would be a shift from domain-based sorting to causal sorting with increasing expertise in the relevant domains. This prediction was borne out: The novice groups sorted primarily by domain and the expert group sorted by causal category. These results suggest that science training facilitates insight about causal structures.
The ability to form relational categories for objects that share few features in common is a hallmark of human cognition. For example, anything that can play a preventative role, from a boulder to poverty, can be a "barrier." However, neurobiological research has focused solely on how people acquire categories defined by features. The present functional magnetic resonance imaging study examines how relational and feature-based category learning compare in well-matched learning tasks. Using a computational model-based approach, we observed a cluster in left rostrolateral prefrontal cortex (rlPFC) that tracked quantitative predictions for the representational distance between test and training examples during relational categorization. Contrastingly, medial and dorsal PFC exhibited graded activation that tracked decision evidence during both feature-based and relational categorization. The results suggest that rlPFC computes an alignment signal that is critical for integrating novel examples during relational categorization whereas other PFC regions support more general decision functions.
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