By the same authors

From the same journal

From the same journal

Self-explanation in the domain of statistics: An expertise reversal effect

Research output: Contribution to journalArticle

Published copy (DOI)

Author(s)

  • Jimmie Leppink
  • Nick J. Broers
  • Tjaart Imbos
  • Cees P.M. van der Vleuten
  • Martijn P.F. Berger

Department/unit(s)

Publication details

JournalHigher Education
DatePublished - 1 Jun 2012
Issue number6
Volume63
Number of pages15
Pages (from-to)771-785
Original languageEnglish

Abstract

This study investigated the effects of four instructional methods on cognitive load, propositional knowledge, and conceptual understanding of statistics, for low prior knowledge students and for high prior knowledge students. The instructional methods were (1) a reading-only control condition, (2) answering open-ended questions, (3) answering open-ended questions and formulating arguments, and (4) studying worked-out examples of the type of arguments students in the third group had to formulate themselves. The results indicate that high prior knowledge students develop more propositional knowledge of statistics than low prior knowledge students. With regard to conceptual understanding, the results indicate an expertise reversal effect: low prior knowledge students learn most from studying worked-out examples, whereas high prior knowledge students profit most from formulating arguments. Thus, novice students should be guided into the subject matter by means of worked-out examples. As soon as students have developed more knowledge of the subject matter, they should be provided with learning tasks that stimulate students to solve problems by formulating arguments.

    Research areas

  • Cognitive load, Conceptual understanding, Expertise reversal effect, Propositional knowledge

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