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Josh Tenenberg; Donald Chinn – Computer Science Education, 2025
Background and context: We address the question of what computer science students take the discipline to be. How students conceive the discipline can influence whether a student pursues computer science, what particular area within computer science they focus on and whether they persist in the discipline. In this paper, we examine the epistemic…
Descriptors: Computer Science Education, Epistemology, Student Attitudes, Intellectual Disciplines
Leah Bidlake; Eric Aubanel; Daniel Voyer – ACM Transactions on Computing Education, 2025
Research on mental model representations developed by programmers during parallel program comprehension is important for informing and advancing teaching methods including model-based learning and visualizations. The goals of the research presented here were to determine: how the mental models of programmers change and develop as they learn…
Descriptors: Schemata (Cognition), Programming, Computer Science Education, Coding
Brayan Díaz; Collin Lynch; Cesar Delgado; Kevin Han – International Journal of STEM Education, 2025
Background: This paper describes research into two pedagogical approaches to foster transdisciplinarity in a graduate engineering course that involves education and computer science. Leveraging the Communities of Practice framework, we examine how students majoring in computer science can integrate new knowledge from education and computer science…
Descriptors: Graduate Study, Engineering Education, Computer Science, Interdisciplinary Approach
Manuel B. Garcia – Education and Information Technologies, 2025
The global shortage of skilled programmers remains a persistent challenge. High dropout rates in introductory programming courses pose a significant obstacle to graduation. Previous studies highlighted learning difficulties in programming students, but their specific weaknesses remained unclear. This gap exists due to the predominant focus on the…
Descriptors: Programming, Introductory Courses, Computer Science Education, Mastery Learning
Atharva Naik; Jessica Ruhan Yin; Anusha Kamath; Qianou Ma; Sherry Tongshuang Wu; R. Charles Murray; Christopher Bogart; Majd Sakr; Carolyn P. Rose – British Journal of Educational Technology, 2025
The relative effectiveness of reflection either through student generation of contrasting cases or through provided contrasting cases is not well-established for adult learners. This paper presents a classroom study to investigate this comparison in a college level Computer Science (CS) course where groups of students worked collaboratively to…
Descriptors: Cooperative Learning, Reflection, College Students, Computer Science Education
Aoife Hennessy; Kieran Murphy – Irish Educational Studies, 2025
The importance of student engagement is long recognised. Students who are more engaged will be more motivated and inclined to complete their studies. The aim of this study is to understand barriers to engagement for first-year computing students, a cohort that traditionally have high non-progression rates. A qualitative descriptive design was…
Descriptors: Barriers, Learner Engagement, Computer Science Education, College Freshmen
Guanghui Qian; Fei Qiu; Jie He; Lu Zhang – Education and Information Technologies, 2025
Promoting interdisciplinary development is an inevitable requirement for the advancement of science and education, as well as an internal need for disciplinary growth and a necessary choice for building world-class universities. In this paper, high-quality academic outputs from China's first-class comprehensive universities are used as a data…
Descriptors: Foreign Countries, Universities, Interdisciplinary Approach, Natural Sciences
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
Cindy Royal – Journalism and Mass Communication Educator, 2025
Artificial intelligence (AI) has taken the forefront in discussions of the future of media and education. Although there are valid concerns, AI has the potential to be useful in learning new skills, particularly those related to computer programming. This case study depicts the ways AI was introduced to assist in teaching coding, specifically in a…
Descriptors: Artificial Intelligence, Coding, Programming, Computer Science Education
Ismaila Temitayo Sanusi; Enoch Shadrack Cudjoe; Musa Adekunle Ayanwale; Bisola Adepoju – SAGE Open, 2025
The increased trend of incorporating computer programming in the basic education system across countries requires the training of new educators. However, the current effort to increase the number of teachers teaching programming is through professional development programs for computer science (CS) teachers and from other content areas. Meanwhile,…
Descriptors: Preservice Teachers, Student Attitudes, Programming, Computer Science Education
Antoni Wilinski; Joanna Olkowicz; Sebastian Agata; Alicja Szostkiewicz; Szymon Guzik; Arkadiusz Wojtak; Pawel Tomkiewicz – Informatics in Education, 2025
This paper presents survey results involving students from three fields of study (computer science, business, and pedagogy), positing that computer science students exhibit distinct patterns in the spectrum of multiple intelligences compared to students in social sciences disciplines. The study involved over 300 students, revealing statistically…
Descriptors: Computer Science Education, Intellectual Disciplines, Majors (Students), Multiple Intelligences
Kevin Slonka; Matthew North; Neelima Bhatnagar; Anthony Serapiglia – Information Systems Education Journal, 2025
Continuing to fill the literature gap, this research replicated and expands a prior study of student performance in database normalization in an introductory database course. The data was collected from four different universities, each having different prerequisite courses for their database course. Student performance on a database normalization…
Descriptors: Required Courses, Academic Achievement, Information Systems, Databases
Shao-Heng Ko; Kristin Stephens-Martinez – ACM Transactions on Computing Education, 2025
Background: Academic help-seeking benefits students' achievement, but existing literature either studies important factors in students' selection of all help resources via self-reported surveys or studies their help-seeking behavior in one or two separate help resources via actual help-seeking records. Little is known about whether computing…
Descriptors: Computer Science Education, College Students, Help Seeking, Student Behavior
Yoana Omarchevska; Anouschka van Leeuwen; Tim Mainhard – Journal of Computing in Higher Education, 2025
In the flipped classroom, students engage in preparatory activities to study the course materials prior to attending teacher-guided sessions. Students' success in the flipped classroom is directly related to their preparation and students tend to change their preparation activity over time. Few studies have investigated why students change their…
Descriptors: Blended Learning, College Students, Metacognition, Learning Motivation
Ailsa Zayyan Salsabila; R. Yugo Kartono Isal; Harry B. Santoso – Journal of Educators Online, 2025
This study aims to provide recommendations for interaction design to enhance students' task interpretation, as one of the crucial aspects of Self-Regulated Learning (SRL) in online learning environments. Utilizing the Engineering Design Metacognitive Questionnaire (EDMQ), open-ended questions, and in-depth interviews, this study examines the…
Descriptors: Learning Processes, Electronic Learning, College Students, Computer Science Education