More factors, better understanding: model verification and construct validity study on the community of inquiry in MOOC

Xuemei Bai, Xiaoqing Gu, Rifa Guo

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

This study aimed to verify the applicability of the community of inquiry (CoI) survey instrument in MOOC involving 1,186 college students from 11 different disciplines in China. Exploratory factor analysis was used to explore potential factor structure models, and confirmatory factor analysis was utilized to verify the four-factor structure obtained from exploratory factor analysis. The original three- and new six-factor structure models were also included in the study. Confirmatory factor analysis results indicating that all three models fit very well with the data. Then Chi-square difference test was used to select the optimal model. Results indicate that the six-factor structure model with teaching presence, social presence, cognitive presence, design and organization, affective expression, and resolution is the optimal one, with good convergent and discriminant validity. Especially, the chi-square difference results indicate that design and organization can be significantly distinguished from teaching presence, whereas affective expression can be significantly distinguished from social presence, and resolution can be significantly distinguished from cognitive presence. Based on these findings, the present study argues that the six-factor structure model can provide a better understanding for the fine design and implementation of MOOC.

Original languageEnglish
Pages (from-to)10483-10506
Number of pages24
JournalEducation and Information Technologies
Volume28
Issue number8
DOIs
StatePublished - Aug 2023

Keywords

  • CoI survey instrument
  • Factor analysis
  • MOOC
  • Optimal model structure

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