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Differential-associative processing or example elaboration: Which strategy is best for learning the definitions of related and unrelated concepts?

机译:差异关联处理或示例阐述:哪种策略最适合学习相关和无关概念的定义?

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摘要

Definitions of related concepts (e.g., genotype–phenotype) are prevalent in introductory classes. Consequently, it is important that educators and students know which strategy(s) work best for learning them. This study showed that a new comparative elaboration strategy, called differential-associative processing, was better for learning definitions of related concepts than was an integrative elaborative strategy, called example elaboration. This outcome occurred even though example elaboration was administered in a naturalistic way (Experiment 1) and students spent more time in the example elaboration condition learning (Experiments 1, 2, 3), and generating pieces of information about the concepts (Experiments 2 and 3). Further, with unrelated concepts (morpheme-fluid intelligence), performance was similar regardless if students used differential-associative processing or example elaboration (Experiment 3). Taken as a whole, these results suggest that differential-associative processing is better than example elaboration for learning definitions of related concepts and is as good as example elaboration for learning definitions of unrelated concepts.
机译:相关概念的定义(例如,基因型–表型)在入门类中很普遍。因此,重要的是教育者和学生必须知道哪种策略最适合学习它们。这项研究表明,一种新的比较细化策略,称为微分关联处理,比学习示例性细化的集成细化策略更好地学习了相关概念的定义。即使以自然主义的方式进行示例阐述(实验1),并且学生在示例阐述条件学习(实验1、2、3)中花费了更多的时间,并生成了有关概念的信息(实验2和3),也出现了这种结果。 )。此外,对于不相关的概念(语素-流体智能),无论学生使用微分关联处理还是示例阐述,其表现都相似(实验3)。总的来说,这些结果表明,微分联想处理优于学习相关概念定义的示例性阐述,也优于学习无关概念定义的示例性阐述。

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