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  • 2018
  • Article
  • Service Science

Insight into Gender Differences in STEM: Evidence from Peer Reviews in an Engineering Class

By: Jacqueline N. Lane, Bruce Ankenman and Seyed Iravani
  • Format:Electronic
  • | Pages:15
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Abstract

As the service industry moves toward self-service, peer feedback serves a critical role in this shift for educational services. Peer feedback is a process by which students provide feedback to each other. One of its major benefits is that it enables students to become actively involved in the learning and assessment process and play an integral role in the delivery and quality of their education. However, a primary concern is that students do not consistently provide each other with quality feedback, especially in science, technology, engineering, and mathematics (STEM) disciplines in which gender stereotypes may hinder the ability of women to provide critical peer feedback. A potential way to improve peer feedback is to create anonymous review settings. This study examines how anonymity alters the nature of peer feedback in a large introductory undergraduate statistics class for computer science and engineering majors. In this class, peers review a series of team video projects as either anonymous or nonanonymous reviewers. Our results show that female peer reviewers were more affected by the anonymity setting than the male peer reviewers. We discuss the implications of these findings for promoting greater participation and retention of women in underrepresented STEM disciplines and the design of effective peer-review processes for improved student achievement and satisfaction.

Keywords

Peer Review; Peer Feedback; STEM Education; Anonymity; Education; Gender; Education Industry

Citation

Lane, Jacqueline N., Bruce Ankenman, and Seyed Iravani. "Insight into Gender Differences in STEM: Evidence from Peer Reviews in an Engineering Class." Service Science 10, no. 4 (2018): 442–456.
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About The Author

Jacqueline Ng Lane

Technology and Operations Management
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    • September–October 2024
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    The Crowdless Future? Generative AI and Creative Problem-Solving

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    Setting Gendered Expectations? Recruiter Outreach Bias in Online Tech Training Programs

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More from the Authors
  • The Crowdless Future? Generative AI and Creative Problem-Solving By: Léonard Boussioux, Jacqueline N. Lane, Miaomiao Zhang, Vladimir Jacimovic and Karim R. Lakhani
  • Narrative AI and the Human-AI Oversight Paradox in Evaluating Early-Stage Innovations By: Jacqueline N. Lane, Léonard Boussioux, Charles Ayoubi, Ying Hao Chen, Camila Lin, Rebecca Spens, Pooja Wagh and Pei-Hsin Wang
  • Setting Gendered Expectations? Recruiter Outreach Bias in Online Tech Training Programs By: Jacqueline N. Lane, Karim R. Lakhani and Roberto Fernandez
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