Learning online via prompts to explain

Joseph Jay Williams, Samuel G. Maldonado, Geza Kovacs, Tania Lombrozo, Caren Walker

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Prompting learners to explain their beliefs can help them correct misconceptions upon encountering anomalies - facts and observations that conflict with learners' current understanding. We have developed a way to augment online interfaces for learning by adding prompts for users to explain a fact or observation. We conducted two experiments testing the effects of these explanation prompts, finding that they increase learners' self-correction of misconceptions, though these benefits of explaining depend on: (1) How many anomalies the prompts require people to explain, and (2) Whether anomalies are distributed so that individual observations guide learners to correct ideas by conflicting with multiple misconceptions at once.

Original languageEnglish (US)
Title of host publicationCHI EA 2014
Subtitle of host publicationOne of a ChiNd - Extended Abstracts, 32nd Annual ACM Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
Pages2269-2274
Number of pages6
ISBN (Print)9781450324748
DOIs
StatePublished - Jan 1 2014
Externally publishedYes
Event32nd Annual ACM Conference on Human Factors in Computing Systems, CHI EA 2014 - Toronto, ON, Canada
Duration: Apr 26 2014May 1 2014

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Other

Other32nd Annual ACM Conference on Human Factors in Computing Systems, CHI EA 2014
CountryCanada
CityToronto, ON
Period4/26/145/1/14

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

Keywords

  • Anomalies
  • Explanation
  • Generalization
  • Learning
  • Misconceptions
  • Self-explanation
  • Statistics

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