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The Landscape of Research on Prior Knowledge and Learning: a Bibliometric Analysis
Educational Psychology Review ( IF 10.1 ) Pub Date : 2023-05-19 , DOI: 10.1007/s10648-023-09775-9
André Bittermann, Danielle McNamara, Bianca A. Simonsmeier, Michael Schneider

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.



中文翻译:

先验知识和学习的研究概况:文献计量分析

了解先验知识在人类学习中的作用对于预测、改进和解释能力习得至关重要。然而,该领域的规模和广度使研究人员难以全面了解。因此,我们对 1980 年至 2021 年间发表的 13,507 篇相关研究进行了文献计量分析。使用文本挖掘和网络分析对摘要、标题和元数据进行了分析。这些研究调查了构成五个社区的 23 个主题:教育、学习环境、认知过程、非学术环境和语言。调查的知识在类型、特征和表示方面是多种多样的,涵盖超过 25 个学术和非学术内容领域。最常被引用的理论背景是 3P 模型、认知负荷理论、和概念变革方法。虽然我们的结果表明先验知识是一个广泛使用的横断面研究主题,但仍然需要更多的综合理论来说明先验知识何时以及如何因果影响学习。

更新日期:2023-05-19
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