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Per Anderhag; Niklas Salomonsson; Andre Bürgers; Cesar Estay Espinola; Birgit Fahrman; Dana Seifeddine Ehdwall; Maria Sundler – International Journal of Technology and Design Education, 2024
During a relatively short period of time, programming has been implemented in the national curriculum of the compulsory school in Sweden. Since 2018, programming is a new content in the technology subject and the research field has discussed some of the challenges teachers and students, who generally have little experiences of programming, face…
Descriptors: Learning Strategies, Programming, Robotics, Technology Education
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Fatima Abu Deeb; Timothy Hickey – Computer Science Education, 2024
Background and Context: Auto-graders are praised by novice students learning to program, as they provide them with automatic feedback about their problem-solving process. However, some students often make random changes when they have errors in their code, without engaging in deliberate thinking about the cause of the error. Objective: To…
Descriptors: Reflection, Automation, Grading, Novices
Abdulrahman Alshammari – ProQuest LLC, 2024
A critical component of modern software development practices, particularly continuous integration (CI), is the halt of development activities in response to test failures which requires further investigation and debugging. As software changes, regression testing becomes vital to verify that new code does not affect existing functionality.…
Descriptors: Computer Software, Programming, Coding, Test Reliability
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Abdullahi Yusuf; Amiru Yusuf Muhammad – Journal of Educational Computing Research, 2024
The study investigates the potential of anxiety clusters in predicting programming performance in two distinct coding environments. Participants comprised 83 second-year programming students who were randomly assigned to either a block-based or a text-based group. Anxiety-induced behaviors were assessed using physiological measures (Apple Watch…
Descriptors: Novices, Programming, Anxiety, Coding
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Meghan M. Parkinson; Seppe Hermans; David Gijbels; Daniel L. Dinsmore – Computer Science Education, 2024
Background and Context: More data are needed about how young learners identify and fix errors while programming in pairs. Objective: The study will identify discernible patterns in the intersection between debugging processes and the type of regulation used during debugging while children engage in coding to drive further theory and model…
Descriptors: Computer Science Education, Troubleshooting, Cooperative Learning, Coding
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Selena Steinberg; Melissa Gresalfi; Lauren Vogelstein; Corey Brady – Journal of Research on Technology in Education, 2024
This paper considers how a curricular design that integrated computer programming and creative movement shaped students' engagement with computing. We draw on data from a camp for middle schoolers, focusing on an activity in which students used the programming environment NetLogo to re-represent their physical choreography. We analyze the extent…
Descriptors: Dance, Programming, Computation, Computer Simulation
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Xiner Liu; Andres Felipe Zambrano; Ryan S. Baker; Amanda Barany; Jaclyn Ocumpaugh; Jiayi Zhang; Maciej Pankiewicz; Nidhi Nasiar; Zhanlan Wei – Journal of Learning Analytics, 2025
This study explores the potential of the large language model GPT-4 as an automated tool for qualitative data analysis by educational researchers, exploring which techniques are most successful for different types of constructs. Specifically, we assess three different prompt engineering strategies -- Zero-shot, Few-shot, and Fewshot with…
Descriptors: Coding, Artificial Intelligence, Automation, Data Analysis
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David DeLiema; Ashley Hufnagle; Miguel Ovies-Bocanegra – British Journal of Educational Psychology, 2025
Background: Moments of failure during learning present a wide range of opportunities for growth. However, experimental research and meta reviews focused on failure and learning tend to target singular valued learning processes, such as efficient fixes or transfer of conceptual understanding. These analytical decisions conflict with research…
Descriptors: Middle School Students, Nonprofit Organizations, Summer Programs, Workshops
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Jennings, Jay; Muldner, Kasia – International Journal of Artificial Intelligence in Education, 2021
When students are first learning to program, they not only have to learn to write programs, but also how to trace them. Code tracing involves stepping through a program step-by-step, which helps to predict the output of the program and identify bugs. Students routinely struggle with this activity, as evidenced by prior work and our own experiences…
Descriptors: Scaffolding (Teaching Technique), Tutors, Tutoring, Programming
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David DeLiema; Jeffrey K. Bye; Vijay Marupudi – ACM Transactions on Computing Education, 2024
Learning to respond to a computer program that is not working as intended is often characterized as finding a singular bug causing a singular problem. This framing underemphasizes the wide range of ways that students and teachers could notice discrepancies from their intention, propose causes of those discrepancies, and implement interventions.…
Descriptors: Computer Software, Troubleshooting, Intention, Intervention
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Critten, Valerie; Hagon, Hannah; Messer, David – Early Childhood Education Journal, 2022
Guided play activities were developed so that coding clubs could promote computational thinking skills in preschool children. The clubs involved fifteen children aged between 2 and 4 years, including a group of children with communication difficulties. The children took part in an action-research scoping study over three coding clubs involving six…
Descriptors: Preschool Children, Programming, Coding, Play
Samim Mirhosseini – ProQuest LLC, 2023
Computer science instructors typically have many responsibilities, such as creating material, delivering lectures, clarifying student questions, and grading student deliverables, while the demand for computer science education has been increasing. Handling all of these responsibilities is challenging in itself. However, it is made worse when…
Descriptors: Computer Science Education, Teacher Responsibility, Faculty Workload, Instructional Materials
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Zeng, Mini; Zhu, Feng – Journal of Cybersecurity Education, Research and Practice, 2021
Software vulnerabilities have become a severe cybersecurity issue. There are numerous resources of industry best practices available, but it is still challenging to effectively teach secure coding practices. The resources are not designed for classroom usage because the amount of information is overwhelming for students. There are efforts in…
Descriptors: Computer Software, Coding, Computer Security, Computer Science Education
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Dahn, Maggie; DeLiema, David; Enyedy, Noel – Teachers College Record, 2020
Background/Context: Computer science has been making its way into K-12 education for some time now. As computer science education has moved into learning spaces, research has focused on teaching computer science skills and principles but has not sufficiently explored the emotional aspects of students' experiences. This topic warrants further study…
Descriptors: Computer Science Education, Coding, Programming, Student Experience
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Hoffman, Heather J.; Elmi, Angelo F. – Journal of Statistics and Data Science Education, 2021
Teaching students statistical programming languages while simultaneously teaching them how to debug erroneous code is challenging. The traditional programming course focuses on error-free learning in class while students' experiences outside of class typically involve error-full learning. While error-free teaching consists of focused lectures…
Descriptors: Statistics Education, Programming Languages, Troubleshooting, Coding
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