Predictive effects of online peer feedback types on performance quality

Fu Yun Yu, Chun Ping Wu

Research output: Contribution to journalArticlepeer-review

33 Citations (Scopus)

Abstract

This study examined the individual and combined predictive effects of two types of feedback (i.e., quantitative ratings and descriptive comments) in online peer-assessment learning systems on the quality of produced work. A total of 233 students participated in the study for six weeks. An online learning system that allows students to contribute to and benefit from the process of question-generation and peer-assessment was adopted. The regression results indicated that quantitative ratings and descriptive comments significantly predicted the quality of produced work (i.e., question-generation performance) both individually and collectively, and descriptive feedback explained more variance in quality of produced work than did quantitative ratings. The empirical significance of this study and suggestions for online learning system development, instructional implementation and future studies are discussed.

Original languageEnglish
Pages (from-to)332-341
Number of pages10
JournalEducational Technology and Society
Volume16
Issue number1
Publication statusPublished - 2013

All Science Journal Classification (ASJC) codes

  • Education
  • Sociology and Political Science
  • Engineering(all)

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