Adding Self-Efficacy Features to an Online Statistics Lesson

Xiaoxia Huang, Richard E. Mayer

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

This study investigated the effectiveness of adding four self-efficacy features to an online statistics lesson, based on Bandura’s four sources of self-efficacy information. In a randomized between-subjects experiment, participants learned statistical rules in an example-based online environment with four self-efficacy features added (treatment group) or not (control group). Results of analyses of variance showed that the treatment group performed better on practice (d = 0.36), retention (d = 0.39), and transfer (d = 0.42) tests as well as reporting higher self-efficacy (d = 0.44) and lower task anxiety (d = −0.45). Further, mediation analyses revealed that the effect of treatment group on performance was fully mediated by task anxiety and self-efficacy. The results support the inclusion of self-efficacy features in online mathematics lessons, when the goal is to improve learning outcomes by reducing anxiety and increasing self-efficacy. The results show the utility of applying Bandura’s model of self-efficacy to technology-based learning environments.

Original languageEnglish (US)
Pages (from-to)1003-1037
Number of pages35
JournalJournal of Educational Computing Research
Volume57
Issue number4
DOIs
StatePublished - Jul 1 2019
Externally publishedYes

Keywords

  • blended learning
  • multimedia learning
  • online intervention
  • self-efficacy
  • statistics learning
  • task anxiety
  • worked example

ASJC Scopus subject areas

  • Education
  • Computer Science Applications

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