Explanation and Fractions: How Preferences for Types of Explanations Affect Learning

Abstract

Explanation is often cited as an effective learning tool, but much work remains to determine the influence of explanations on different types of material to be learned. Evidence from category learning suggests that explanation may drive the learner to identify underlying regularities that fit a general pattern (Williams & Lombrozo, 2010). In a pilot study, we examined whether explanation could be used to improve understanding of fraction magnitudes and whether explanations of specific inequalities are more or less effective than explanations of sets of inequalities. Results revealed that generating single or set explanations did not affect test or transfer accuracy, but individuals indicated strong and consistent preferences for particular types of explanations (i.e. conceptual, procedural, or rule-based). Further studies are being conducted to identify individual differences that may predict preferences for different kinds of explanations and their effect on subsequent learning and understanding.


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