Online targeting behavior of peer-assessors under identity-revealed, nicknamed, and concealed modes

Fu Yun Yu, Shannon Sung

Research output: Contribution to journalArticlepeer-review


This study examined whether different identity revelation conditions result in different online targeting behavior among peer-assessors through a pretest and posttest quasi-experimental research design. Students from six fifth-grade classes (N = 196) participated in online learning tasks where they generated and selected peer-generated questions to review and assess in their respective identity revelation modes-real-name, nickname, and anonymity. Several findings were obtained. First, there was a high redundancy rate for both high- and low-targeted assessees under the pre-treatment (control) and treatment conditions for all three identity revelation modes. Second, the non-significant results of the chi-square tests indicated that the identity revelation modes and assessee redundancy were neither considerably related for the high- nor low-targeted assessees groups. Third, the results from the ANCOVA on the number of peer-feedback messages each student received showed no significant differences among the three identity revelation treatments. Fourth, the Wilcoxon tests confirmed that there were no significant differences in the assessee rankings in terms of the number of times their generated questions were assessed between the pre-treatment and treatment conditions for all different identity revelation modes. Finally, the results from participants' responses to the checkbox question revealed almost the same ranking pattern regarding factors dominating their targeting behavior (with the question-author ranked last among all factors), despite the various different identity revelation modes. In sum, identity revelation modes were not found to affect peer-assessors' targeting behavior in an online peer-assessment activity.

Original languageEnglish
Pages (from-to)15-27
Number of pages13
JournalEducational Technology and Society
Issue number1
Publication statusPublished - 2019

All Science Journal Classification (ASJC) codes

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

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