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Professional Development Workshops for Faculty on Addressing Implicit Bias in Computer Science Education

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Title: Professional Development Workshops for Faculty on Addressing Implicit Bias in Computer Science Education
Language: English
Authors: Sandie Han, Diana Samaroo, Janet Liou-Mark, Boyan Kostadinov, Johann Thiel, Suhua Zeng
Source: Mathematics Teaching Research Journal. 2025 17(4):80-97.
Availability: City University of New York. Creative Commons. 205 East 42 Street, New York, NY 10017. Web site: https://mtrj.commons.gc.cuny.edu/
Peer Reviewed: Y
Page Count: 18
Publication Date: 2025
Sponsoring Agency: Office of Postsecondary Education (OPE) (ED), Minority Science and Engineering Improvement Program (MSEIP)
Contract Number: P120A150063
Document Type: Journal Articles
Reports - Research
Tests/Questionnaires
Education Level: Higher Education
Postsecondary Education
Descriptors: STEM Education, College Faculty, Faculty Development, Teacher Workshops, Computer Science Education, Bias, Minority Serving Institutions, Undergraduate Study, Inclusion, Classroom Environment, Teacher Attitudes, Gender Bias, Sex Fairness, Equal Education, Best Practices, Problem Solving, Computation, Thinking Skills, Gender Discrimination
Geographic Terms: New York (New York)
ISSN: 2573-4377
Abstract: The "Understanding Implicit Bias" workshops were offered to Science, Technology, Engineering, and Mathematics (STEM) faculty at an urban minority-serving undergraduate institution with a focus on addressing the gender gap in computer science. The workshops aimed to raise awareness of implicit (unconscious) biases and provide practical strategies for addressing them, fostering a more inclusive classroom environment. Analysis of pre- and post-survey responses indicated an increase in participants' awareness of implicit biases in their discipline and a greater openness to taking steps to address them, suggesting the workshops' potential impact on promoting inclusive teaching practices.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1485889
Database: ERIC
FullText Text:
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  Data: Professional Development Workshops for Faculty on Addressing Implicit Bias in Computer Science Education
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  Data: <searchLink fieldCode="SO" term="%22Mathematics+Teaching+Research+Journal%22"><i>Mathematics Teaching Research Journal</i></searchLink>. 2025 17(4):80-97.
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  Data: City University of New York. Creative Commons. 205 East 42 Street, New York, NY 10017. Web site: https://mtrj.commons.gc.cuny.edu/
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  Data: 18
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  Data: 2573-4377
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  Data: The "Understanding Implicit Bias" workshops were offered to Science, Technology, Engineering, and Mathematics (STEM) faculty at an urban minority-serving undergraduate institution with a focus on addressing the gender gap in computer science. The workshops aimed to raise awareness of implicit (unconscious) biases and provide practical strategies for addressing them, fostering a more inclusive classroom environment. Analysis of pre- and post-survey responses indicated an increase in participants' awareness of implicit biases in their discipline and a greater openness to taking steps to address them, suggesting the workshops' potential impact on promoting inclusive teaching practices.
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  Data: 2025
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  Data: EJ1485889
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      – Text: English
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        PageCount: 18
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    Subjects:
      – SubjectFull: STEM Education
        Type: general
      – SubjectFull: College Faculty
        Type: general
      – SubjectFull: Faculty Development
        Type: general
      – SubjectFull: Teacher Workshops
        Type: general
      – SubjectFull: Computer Science Education
        Type: general
      – SubjectFull: Bias
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      – SubjectFull: Minority Serving Institutions
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      – SubjectFull: Undergraduate Study
        Type: general
      – SubjectFull: Inclusion
        Type: general
      – SubjectFull: Classroom Environment
        Type: general
      – SubjectFull: Teacher Attitudes
        Type: general
      – SubjectFull: Gender Bias
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      – SubjectFull: Sex Fairness
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      – SubjectFull: Equal Education
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      – SubjectFull: Best Practices
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      – SubjectFull: Problem Solving
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      – SubjectFull: Computation
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      – SubjectFull: Thinking Skills
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      – SubjectFull: Gender Discrimination
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      – SubjectFull: New York (New York)
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      – TitleFull: Professional Development Workshops for Faculty on Addressing Implicit Bias in Computer Science Education
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