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Direct linkRonit Shmallo; Adi Katz – Computer Science Education, 2024
Background and Context: Gender research shows that women are better at reading comprehension. Other studies indicate a lower tendency in women to choose STEM professions. Since data modeling requires reading skills and also belongs in the areas of information systems and computer science (STEM professions), these findings provoked our curiosity.…
Descriptors: Gender Differences, Transfer of Training, Databases, Models
Teresa M. Ober; Ying Cheng; Meghan R. Coggins; Paul Brenner; Janice Zdankus; Philip Gonsalves; Emmanuel Johnson; Tim Urdan – Computer Science Education, 2024
Background and Context: Differences in children's and adolescents' initial attitudes about computing and other STEM fields may form during middle school and shape decisions leading to career entry. Early emerging differences in career interest may propagate a lack of diversity in computer science and programming fields. Objective: Though middle…
Descriptors: Middle School Students, Student Attitudes, Computer Science Education, STEM Education
Wanzer, Dana Linnell; McKlin, Tom; Freeman, Jason; Magerko, Brian; Lee, Taneisha – Computer Science Education, 2020
Background and Context: EarSketch was developed as a program to foster persistence in computer science with diverse student populations. Objective: To test the effectiveness of EarSketch in promoting intentions to persist, particularly among female students and under-represented minority students. Method: Meta-analyses, structural equation…
Descriptors: Intention, Student Participation, Persistence, Computer Science Education
Doube, Wendy; Lang, Catherine – Computer Science Education, 2012
A multimedia university programme with relatively equal numbers of male and female students in elective programming subjects provided a rare opportunity to investigate female motivation to study and pursue computer programming in a career. The MSLQ was used to survey 85 participants. In common with research into deterrence of females from STEM…
Descriptors: Foreign Countries, Sex Stereotypes, Females, Self Efficacy
