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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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Xue Zhang; Chao Qin; Yanjia Liu; Haipeng Wan – ACM Transactions on Computing Education, 2024
Pair programming is an effective instructional format in programming education for adolescents. Within pair programming, three potential gender combinations may arise: Boy-Boy (BB), Girl-Girl (GG), and Boy-Girl (BG). This study explores the impact of different gender pairings on the programming self-efficacy and collaborative attitudes of…
Descriptors: Programming, Gender Differences, Cooperative Learning, Self Efficacy
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Saqr, Mohammed; Ng, Kwok; Oyelere, Solomon Sunday; Tedre, Matti – ACM Transactions on Computing Education, 2021
The momentum around computational thinking (CT) has kindled a rising wave of research initiatives and scholarly contributions seeking to capitalize on the opportunities that CT could bring. A number of literature reviews have showed a vibrant community of practitioners and a growing number of publications. However, the history and evolution of the…
Descriptors: Computation, Thinking Skills, Bibliometrics, Educational Research
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Lishinski, Alex; Yadav, Aman – ACM Transactions on Computing Education, 2021
Research has repeatedly shown self-efficacy to be associated with course outcomes in CS and across other fields. CS education research has documented this and has developed CS-specific self-efficacy measurement instruments, but to date there have been only a few studies examining interventions intended to improve students' self-efficacy in CS, and…
Descriptors: Self Evaluation (Individuals), Intervention, Self Efficacy, Computer Science Education
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Lyon, Louise Ann; Green, Emily – ACM Transactions on Computing Education, 2021
College-educated women in the workforce are discovering a latent interest in and aptitude for computing motivated by the prevalence of computing as an integral part of jobs in many fields as well as continued headlines about the number of unfilled, highly paid computing jobs. One of these women's choices for retraining are the so-called coding…
Descriptors: Computer Science Education, Coding, Programming, Females
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Umar Shehzad; Jody Clarke-Midura; Mimi Recker – ACM Transactions on Computing Education, 2024
Objectives: The increasing demand for computing skills has led to a rapid rise in the development of new computer science (CS) curricula, many with the goal of equitably broadening the participation of underrepresented students in CS. While such initiatives are vital, factors outside of the school environment also play a role in influencing…
Descriptors: Parent Child Relationship, Computer Science Education, Programming, Equal Education
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Loksa, Dastyni; Margulieux, Lauren; Becker, Brett A.; Craig, Michelle; Denny, Paul; Pettit, Raymond; Prather, James – ACM Transactions on Computing Education, 2022
Metacognition and self-regulation are important skills for successful learning and have been discussed and researched extensively in the general education literature for several decades. More recently, there has been growing interest in understanding how metacognitive and self-regulatory skills contribute to student success in the context of…
Descriptors: Metacognition, Programming, Computer Science Education, Learning Processes
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Hamouda, Sally; Edwards, Stephen H.; Elmongui, Hicham G.; Ernst, Jeremy V.; Shaffer, Clifford A. – ACM Transactions on Computing Education, 2019
Recursion is one of the most important and hardest topics in lower division computer science courses. As it is an advanced programming skill, the best way to learn it is through targeted practice exercises. But the best practice problems are time consuming to manually grade by an instructor. As a consequence, students historically have completed…
Descriptors: Computer Science Education, Programming, Instructional Effectiveness, Difficulty Level
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Weston, Timothy J.; Dubow, Wendy M.; Kaminsky, Alexis – ACM Transactions on Computing Education, 2020
While demand for computer science and information technology skills grows, the proportion of women entering computer science (CS) fields has declined. One critical juncture is the transition from high school to college. In our study, we examined factors predicting college persistence in computer science- and technology-related majors from data…
Descriptors: Females, Academic Persistence, High School Students, Computer Science Education
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Clarke-Midura, Jody; Sun, Chongning; Pantic, Katarina; Poole, Frederick J.; Allan, Vicki – ACM Transactions on Computing Education, 2019
Our work is situated in research on Computer Science (CS) learning in informal learning environments and literature on the factors that influence girls to enter CS. In this article, we outline design choices around the creation of a summer programming camp for middle school youth. In addition, we describe a near-peer mentoring model we used that…
Descriptors: Computer Science Education, Educational Environment, Females, Middle School Students
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Hundhausen, C. D.; Olivares, D. M.; Carter, A. S. – ACM Transactions on Computing Education, 2017
In recent years, learning process data have become increasingly easy to collect through computer-based learning environments. This has led to increased interest in the field of "learning analytics," which is concerned with leveraging learning process data in order to better understand, and ultimately to improve, teaching and learning. In…
Descriptors: Learning Analytics, Computer Science Education, Programming, Learning Processes
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Enstrom, Emma; Kann, Viggo – ACM Transactions on Computing Education, 2017
When compared to earlier programming and data structure experiences that our students might have, the perspective changes on computers and programming when introducing theoretical computer science into the picture. Underlying computational models need to be addressed, and mathematical tools employed, to understand the quality criteria of…
Descriptors: Difficulty Level, Computer Science Education, Undergraduate Students, Programming
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Merkouris, Alexandros; Chorianopoulos, Konstantinos; Kameas, Achilles – ACM Transactions on Computing Education, 2017
Pedagogy has emphasized that physical representations and tangible interactive objects benefit learning especially for young students. There are many tangible hardware platforms for introducing computer programming to children, but there is limited comparative evaluation of them in the context of a formal classroom. In this work, we explore the…
Descriptors: Computer Science Education, Programming, Robotics, Computers
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Magerko, Brian; Freeman, Jason; McKlin, Tom; Reilly, Mike; Livingston, Elise; McCoid, Scott; Crews-Brown, Andrea – ACM Transactions on Computing Education, 2016
This article presents EarSketch, a learning environment that combines computer programming with sample-based music production to create a computational remixing environment for learning introductory computing concepts. EarSketch has been employed in both formal and informal settings, yielding significant positive results in student content…
Descriptors: Art Education, STEM Education, Computer Science Education, Disproportionate Representation