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Showing 1 to 15 of 46 results Save | Export
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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
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Aadarsh Padiyath – ACM Transactions on Computing Education, 2024
As computing educators begin to recognize that their students need strong ethical foundations, there is a growing interest to integrate meaningful ethics education into undergraduate computing curricula. To achieve this, it is crucial to understand how students respond to ethical interventions in the classroom. This review examines the acceptance…
Descriptors: Undergraduate Students, Student Attitudes, Ethics, Intervention
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Noelle Brown; Sara Nurollahian; Eliane S. Wiese – ACM Transactions on Computing Education, 2025
While there have been many calls for teaching ethics and responsible computing, it is unclear how responsible computing instruction and technical learning interact. Some instructors even hesitate to include ethics in their courses, fearing it might distract students from learning technical computing content. An approach called…
Descriptors: Teaching Methods, Computer Science Education, Intervention, Ethics
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Marcus Messer; Neil C. C. Brown; Michael Kölling; Miaojing Shi – ACM Transactions on Computing Education, 2024
We conducted a systematic literature review on automated grading and feedback tools for programming education. We analysed 121 research papers from 2017 to 2021 inclusive and categorised them based on skills assessed, approach, language paradigm, degree of automation, and evaluation techniques. Most papers assess the correctness of assignments in…
Descriptors: Automation, Grading, Feedback (Response), Programming
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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
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Niloofar Mansoor; Cole S. Peterson; Michael D. Dodd; Bonita Sharif – ACM Transactions on Computing Education, 2024
Background and Context: Understanding how a student programmer solves different task types in different programming languages is essential to understanding how we can further improve teaching tools to support students to be industry-ready when they graduate. It also provides insight into students' thought processes in different task types and…
Descriptors: Biofeedback, Eye Movements, Computer Science Education, Programming Languages
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Gabriela de Carvalho Barros Bezerra; Wilk Oliveira; Ana Cláudia Guimarães Santos; Juho Hamari – ACM Transactions on Computing Education, 2024
Despite recent high interest among researchers and practitioners in learning programming, even the most dedicated learners can struggle to find motivation for studying and practicing programming. Therefore, in recent years, several strategies (e.g., educational games, flipped classrooms, and visual programming languages) have been employed to…
Descriptors: Gamification, Programming, Computer Science Education, Workshops
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Stephanie Yang; Miles Baird; Eleanor O’Rourke; Karen Brennan; Bertrand Schneider – ACM Transactions on Computing Education, 2024
Students learning computer science frequently struggle with debugging errors in their code. These struggles can have significant downstream effects--negatively influencing how students assess their programming ability and contributing to their decision to drop out of CS courses. However, debugging instruction is often an overlooked topic, and…
Descriptors: Computer Science Education, Troubleshooting, Programming, Teaching Methods
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Catalina Cortázar; Iñaki Goñi; Andrea Ortiz; Miguel Nussbaum – ACM Transactions on Computing Education, 2024
Integrating graduate education with professional skills development is still a challenge. People's beliefs about learning impact their learning processes. Therefore, we need to understand the mindset of graduates to determine best practices for promoting professional skills development. In this study, we explore the perspective of computing…
Descriptors: Computer Science Education, Graduate Students, Computer Literacy, Job Skills
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Khalia Braswell; Simone Smarr; Jamie Payton – ACM Transactions on Computing Education, 2024
Several studies have reported the positive benefits of informal Computer Science learning programs for Black girls, which include staff, mentors, and peers reflective of the girls in the program; however, we do not know enough about what motivates Black women to sign up to teach in such programs, or how representation in mentoring affects future…
Descriptors: Mentors, African American Students, Females, Computer Science Education
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Randy Connolly – ACM Transactions on Computing Education, 2024
The belief that AI technology is on the cusp of causing a generalized social crisis became a popular one in 2023. While there was no doubt an element of hype and exaggeration to some of these accounts, they do reflect the fact that there are troubling ramifications to this technology stack. This conjunction of shared concerns about social,…
Descriptors: Artificial Intelligence, Computers, Technology Uses in Education, Public Opinion
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Diana Kirk; Andrew Luxton-Reilly; Ewan Tempero – ACM Transactions on Computing Education, 2025
Objectives: Code style is an important aspect of text-based programming because programs written with good style are considered easier to understand and change and so improve the maintainability of the delivered software product. However teaching code style is complicated by the existence of many style guides and standards that contain…
Descriptors: Computer Science Education, Programming, Computer Software, Teaching Methods
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Noelle Brown; Benjamin Xie; Ella Sarder; Casey Fiesler; Eliane S. Wiese – ACM Transactions on Computing Education, 2024
The computing education research community now has at least 40 years of published research on teaching ethics in higher education. To examine the state of our field, we present a systematic literature review of papers in the "Association for Computing Machinery" computing education venues that describe teaching ethics in higher-education…
Descriptors: Ethics, Computer Science Education, Higher Education, Teaching Methods
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Susan R. Fisk; Brittany Watts; Courtney Dress; Charlotte Lee; Audrey Rorrer; Tom McKlin; Tiffany Barnes; Jamie Payton – ACM Transactions on Computing Education, 2024
Black women remain severely underrepresented in computing despite ongoing efforts to diversify the field. Given that Black women exist at the intersection of both racial and gendered identities, tailored approaches are necessary to address the unique barriers Black women face in computing. However, it is difficult to quantitatively evaluate the…
Descriptors: Females, Disproportionate Representation, Intervention, African American Students
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Rafi Santo; Aman Yadav; David Phelps – ACM Transactions on Computing Education, 2024
Those working toward equitable K-12 computing education in the United States have always had their work cut out for them: understanding how best to teach, developing robust curricula, designing novel tools, building teacher capacity, and supporting systemic change in schools to bring equitable computing education to young people. Collectively,…
Descriptors: Computer Science Education, Elementary Secondary Education, Public Education, Teaching Methods
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