Preservice teachers’ recognition of source and content bias in educational application (app) reviews

Alexandra List, Hye Yeon Lee, Hongcui Du, Gala S. Campos Oaxaca, Bailing Lyu, A. Lilyan Falcon, Chang Jen Lin

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Across two studies we examine the role of bias in preservice teachers' (PSTs) selection of educational applications for classroom use. In Study 1, participants were asked to rate and form recommendations based on four app reviews, varying in their source bias or commercial motivations (e.g., a sponsored post on a third-party review site; a commercial site with a real teacher testimonial) and in their introduction of one-sided or two-sided content (i.e., content bias). In Study 2, participants were asked to rate eight differentially attributed app reviews and complete two bias discrimination tasks, purposefully constructed to capture PSTs’ reasoning about source bias and content bias. Results from Study 1 showed that PSTs were somewhat effective at discounting reviews demonstrating source bias but were less effective at considering content bias. Study 2 showed that while PSTs considered two-sided information to be more trustworthy than one-sided information, they did not seem to differentiate between commercially biased reviews, of different types. Implications for supporting PSTs and all students to reason about forms of bias are discussed.

Original languageEnglish (US)
Article number107297
JournalComputers in Human Behavior
Volume134
DOIs
StatePublished - Sep 2022

All Science Journal Classification (ASJC) codes

  • Arts and Humanities (miscellaneous)
  • Human-Computer Interaction
  • General Psychology

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