ERIC Number: EJ1471302
Record Type: Journal
Publication Date: 2025-Jun
Pages: 45
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0034-6543
EISSN: EISSN-1935-1046
Available Date: 0000-00-00
Computing Education Interventions to Increase Gender Equity from 2000 to 2020: A Systematic Literature Review
Lara Perez-Felkner1; Kristen Erichsen2; Yang Li1; Jinjushang Chen3; Shouping Hu1; Ladanya Ramirez Surmeier1; Chelsea Shore4
Review of Educational Research, v95 n3 p536-580 2025
Although gender parity has been achieved in some STEM fields, gender disparities persist in computing, one of the fastest-growing and highest-earning career fields. In this systematic literature review, we expand upon academic momentum theory to categorize computing interventions intended to make computing environments more inclusive to girls and women and consider how those characteristics vary by the success of the intervention. Particular attention is given to the efficacy of broadening participation and success for women in computer science, information technology, and related fields. After scrutinizing 168 relevant studies, 48 met the inclusion criteria and were included. We introduce a framework for gender equity in computing, expanding on existing research on academic and STEM momentum to encompass new domains representing social and structural momentum. Our analysis reveals the complex roles of intervention domains, strategies, goals, levels, and duration in shaping their efficacy. Implications for theory, research, and practice are discussed.
Descriptors: Computer Science Education, Gender Differences, Equal Education, Research Reports, Intervention, Females, Social Influences, Inclusion, Womens Education, Salaries, Career Choice, Guidelines
SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Publication Type: Journal Articles; Information Analyses; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: National Science Foundation (NSF)
Authoring Institution: N/A
Grant or Contract Numbers: 1920670; 2030070; 2305516
Author Affiliations: 1Florida State University; 2Knowli Data Science; 3Beijing Normal University; 4Independent Researcher, SAFE Project