Preservice teachers' recognition of source and content bias in educational application (app) reviews. (September 2022)
- Record Type:
- Journal Article
- Title:
- Preservice teachers' recognition of source and content bias in educational application (app) reviews. (September 2022)
- Main Title:
- Preservice teachers' recognition of source and content bias in educational application (app) reviews
- Authors:
- List, Alexandra
Lee, Hye Yeon
Du, Hongcui
Campos Oaxaca, Gala S.
Lyu, Bailing
Falcon, A. Lilyan
Lin, Chang-Jen - Abstract:
- 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. Highlights: We examine the role of source and content bias in pre-service teachers' (PSTs') evaluations of educational app reviews. PSTs discounted reviews published as a sponsored post or on a commercial website. PSTs similarly rated a third-party review and a commercial review with a "real" testimonial. PSTs trusted two-sidedAbstract: 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. Highlights: We examine the role of source and content bias in pre-service teachers' (PSTs') evaluations of educational app reviews. PSTs discounted reviews published as a sponsored post or on a commercial website. PSTs similarly rated a third-party review and a commercial review with a "real" testimonial. PSTs trusted two-sided reviews more-so than one-sided reviews. We document PSTs' difficulties distinguishing between commercially biased reviews. … (more)
- Is Part Of:
- Computers in human behavior. Volume 134(2022)
- Journal:
- Computers in human behavior
- Issue:
- Volume 134(2022)
- Issue Display:
- Volume 134, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 134
- Issue:
- 2022
- Issue Sort Value:
- 2022-0134-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-09
- Subjects:
- Source evaluation -- Trustworthiness ratings -- Sourcing -- Bias -- Source bias -- Content bias
Interactive computer systems -- Periodicals
Man-machine systems -- Periodicals
004.019 - Journal URLs:
- http://www.sciencedirect.com/science/journal/07475632 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.chb.2022.107297 ↗
- Languages:
- English
- ISSNs:
- 0747-5632
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.921600
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21872.xml