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Alicia Garcia-Holgado; Andrea Vazquez-Ingelmo; Francisco Jose Garcia-Penalvo – IEEE Transactions on Education, 2024
Contribution: Gender mainstreaming in university teaching should be covered in all the knowledge areas. This work successfully introduces the gender perspective as part of the methodological approach to teaching and learning in Computer Science. Background: This study describes how gender mainstreaming has been introduced and matured during six…
Descriptors: Computer Science, Gender Differences, Equal Education, Inclusion
Jennifer M. Blaney; Theresa E. Hernandez; David F. Feldon; Annie M. Wofford – Community College Review, 2025
Research Questions: While community college transfer (i.e., upward transfer) represents an important mechanism for advancing equity across STEM fields, existing studies of gender and women's participation within computer science have largely excluded the perspectives of upward transfer students. We address this gap in the literature by exploring…
Descriptors: Transfer Students, STEM Education, Gender Differences, Computer Science Education
Lubna Mohammed Alshamrani – Pegem Journal of Education and Instruction, 2024
Reflective practice is an essential catalyst through which the benefits of teaching and learning can be reaped. Through it, weaknesses and strengths can be identified in a way that helps raise the level of addressing challenges that may arise as well as overcome them. This paper presents the critical reflective practices among computer science…
Descriptors: Reflective Teaching, Secondary School Teachers, Computer Science, Foreign Countries
Nontachai Samngamjan; Pakawat Phettom; Kajohnsak Sa-ngunsat; Wudhijaya Philuek – Shanlax International Journal of Education, 2024
In the realm of education, the integration of AI literacy into computer science teaching is becoming increasingly crucial (Walsh et al., 2023; Voulgari et al., 2022; Velander et al., 2023). Teachers play a pivotal role in bridging the gap between research and practical knowledge transfer of AIrelated skills, necessitating a solid foundation in…
Descriptors: Artificial Intelligence, Technological Literacy, Foreign Countries, Student Teachers
Lara Perez-Felkner; Kristen Erichsen; Yang Li; Jinjushang Chen; Shouping Hu; Ladanya Ramirez Surmeier; Chelsea Shore – Review of Educational Research, 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…
Descriptors: Computer Science Education, Gender Differences, Equal Education, Research Reports
Sonia Lorente; Mónica Arnal-Palacián; Maximiliano Paredes-Velasco – European Journal of Psychology of Education, 2024
The European Higher Education Area (EHEA) proposes to enhance active learning and student protagonism in order to improve academic performance. In this sense, different methodologies are emerging to create scenarios for self-regulation of their learning. In this study the cooperative, collaborative and interdisciplinary learning methodologies were…
Descriptors: Cooperative Learning, Interdisciplinary Approach, Computer Software, Universities
Ioannis Vourletsis – Educational Technology Research and Development, 2025
Computational thinking (CT) skills have become increasingly important in modern education, as they equip students with critical problem-solving skills applicable across various domains. Given the growing emphasis on digital literacy, it is essential to investigate grade- and gender-level differences in CT skills among students to support targeted…
Descriptors: Gender Differences, Instructional Program Divisions, Elementary School Students, Scores
Lihui Sun; Junjie Liu – Journal of Educational Computing Research, 2025
Computational Thinking (CT) has evolved as an essential competency for K-12 students, and programming practices are recognized as the key way to facilitate CT development. However, most studies of CT development in middle graders have focused on visual programming, lacking evidence to demonstrate the effectiveness of Python programming. Therefore,…
Descriptors: Computation, Thinking Skills, Skill Development, Middle School Students
Mike Karlin; Anne Ottenbreit-Leftwich; Yin-Chan Janet Liao – TechTrends: Linking Research and Practice to Improve Learning, 2024
While a growing emphasis has been placed on broadening participation in computer science (CS) education, an enduring gender gap exists. One reason for this is gender-based CS stereotypes, which serve as gatekeepers and act in exclusionary ways. However, some high schools in the U.S. have still built gender-inclusive CS programs. We conducted a…
Descriptors: High Schools, Computer Science Education, Gender Differences, Stereotypes
Yin-Rong Zhang; Zhong-Mei Han; Tao He; Chang-Qin Huang; Fan Jiang; Gang Yang; Xue-Mei Wu – Journal of Computer Assisted Learning, 2025
Background: Collaborative programming is important and challenging for K12 students. Scaffolding is a vital method to support students' collaborative programming learning. However, conventional scaffolding that does not fade may lead students to become overly dependent, resulting in unsatisfactory programming performance. Objectives: This study…
Descriptors: Middle School Students, Grade 8, Scaffolding (Teaching Technique), Programming
Fadoua Balabdaoui; Nora Dittmann-Domenichini; Henry Grosse; Claudia Schlienger; Gerd Kortemeyer – Discover Education, 2024
We report the results of a 4800-respondent survey among students at a technical university regarding their usage of artificial intelligence tools, as well as their expectations and attitudes about these tools. We find that many students have come to differentiated and thoughtful views and decisions regarding the use of artificial intelligence. The…
Descriptors: Foreign Countries, College Students, Artificial Intelligence, Student Attitudes
Yucnary-Daitiana Torres-Torres; Marcos Román-González; Juan-Carlos Perez-Gonzalez – European Journal of Education, 2024
Computational Thinking (CT) is crucial for the advancement of the STEM field, where there continues to be a lack of female representation. Teaching and learning (T/L) of CT should incorporate didactic strategies that aim to eliminate gender biases and integrate girls/women into this context. In response to the question, "What didactic…
Descriptors: Thinking Skills, Gender Differences, Females, Disproportionate Representation
Ella Christiaans; So Yeon Lee; Kristy A. Robinson – Educational Psychology, 2024
Students want to learn computer science due to its usefulness for future careers, however they often meet challenges in introductory courses. In the increasingly digital world, it is important to understand some important psychological consequences of such challenges: perceived costs of pursuing computer science. This study thus investigated…
Descriptors: Undergraduate Students, Computer Science Education, Psychological Patterns, Student Attitudes
Asiye Toker Gokce; Arzu Deveci Topal; Aynur Kolburan Geçer; Canan Dilek Eren – Education and Information Technologies, 2025
Artificial intelligence (AI) literacy is critical to shaping students' academic experiences and future opportunities inhigher education. This study examines AI literacy among university students, examining variables such as gender, frequency of use of AI applications, completion of AI-related courses, and field of study. The research involved 664…
Descriptors: Artificial Intelligence, Technological Literacy, College Students, Decision Making
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