The Landscape of Research on Prior Knowledge and Learning: a Bibliometric Analysis

Abstract Understanding the role of prior knowledge in human learning is essential for predicting, improving, and explaining competence acquisition. However, the size and breadth of this field make it difficult for researchers to glean a comprehensive overview. Hence, we conducted a bibliometric analysis of 13,507 relevant studies published between 1980 and 2021. Abstracts, titles, and metadata were analyzed using text mining and network analysis. The studies investigated 23 topics forming five communities: Education, Learning Environments, Cognitive Processes, Nonacademic Settings, and Language. The investigated knowledge was diverse regarding its types, characteristics, and representations, covering more than 25 academic and non-academic content domains. The most frequently referenced theoretical backgrounds were the 3P Model, Cognitive Load Theory, and Conceptual Change approaches. While our results indicate that prior knowledge is a widely used cross-sectional research topic, there remains a need for more integrative theories of when and how prior knowledge causally affects learning.