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Ronit 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
Steve Balady; Cynthia Taylor – Computer Science Education, 2024
Background and Context: Computer Science has traditionally had poor student retention, especially among women. Prior work has found that student attitudes are a key factor to retention, especially with "weedout" courses such as Calculus. Objective: To determine how student attitudes towards CS 1 and Calculus change over active-learning…
Descriptors: Student Attitudes, Calculus, Computer Science Education, Academic Persistence
Dandan Yang; Zhanxia Yang; Marina Umaschi Bers – Computer Science Education, 2025
Background and context: Despite the growing importance of computer science (CS) education, high-quality CS curricula for students in kindergarten to lower elementary grades are lacking. It is also unclear how students from underrepresented groups such as female students, students from low socioeconomic status, and students with disability respond…
Descriptors: Computer Science Education, Early Childhood Education, Program Effectiveness, Programming
Lijun Shen; Zitsi Mirakhur; Sarah LaCour – Computer Science Education, 2025
Background and Context: Educators and researchers are interested in building the computational thinking (CT) skills of K-12 students. However, the availability of language-agnostic assessments for lower elementary graders remains limited. Objective: We present preliminary insights into the reliability and validity of the Computational Thinking…
Descriptors: Thinking Skills, Gender Differences, Computer Science Education, Elementary School Students
Chen Chen; Jonathan Rothwell; Pedrito Maynard-Zhang – Computer Science Education, 2024
Background and Context: Both in- and out-of-school computer science (CS) learning opportunities are expanding, but their influences on CS career interests are unclear. Method: To investigate, we applied multinomial propensity score weighting analysis on a 2021 U.S. nationally representative sample of 4,116 5th-to-12th-grade students. Findings: The…
Descriptors: Informal Education, Computer Science Education, Influences, Vocational Interests
Amanda A. Barrett; Colin T. Smith; Courtni H. Hafen; Emilee Severe; Elizabeth G. Bailey – Computer Science Education, 2024
Background and Context: While biology has strong female representation, computer science is the least gender equitable of the STEM fields. A better understanding of the barriers that keep women out of computational fields will help overcome those barriers to create a more diverse workforce. Objective: We investigated the complexities that…
Descriptors: Sex Role, Majors (Students), Prior Learning, Computer Science Education
Leiny Garcia; Miranda Parker; Mark Warschauer – Computer Science Education, 2024
Background and Context: Despite the growing initiatives in K-12 computer science (CS), there is a continued disparity in the participation of Latinx and multilingual students, a historically underrepresented group in computing. The inequitable participation may be understood by examining students' early development of CS attitudes. Objective: This…
Descriptors: Coding, Student Attitudes, Grade 4, Elementary School Students
Zhanxia Yang; Marina Bers – Computer Science Education, 2024
Background and Context: Historically, women have been underrepresented in computer science. To address this gender gap, researchers advocate for high-quality computer science programs for early childhood. Objectives: This study examines gender differences in coding performance before and after implementing a 24-lesson visual programming curriculum…
Descriptors: Gender Differences, Grade 1, Elementary School Students, Programming
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