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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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Ishaya Gambo; Faith-Jane Abegunde; Omobola Gambo; Roseline Oluwaseun Ogundokun; Akinbowale Natheniel Babatunde; Cheng-Chi Lee – Education and Information Technologies, 2025
The current educational system relies heavily on manual grading, posing challenges such as delayed feedback and grading inaccuracies. Automated grading tools (AGTs) offer solutions but come with limitations. To address this, "GRAD-AI" is introduced, an advanced AGT that combines automation with teacher involvement for precise grading,…
Descriptors: Automation, Grading, Artificial Intelligence, Computer Assisted Testing
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Davi Bernardo Silva; Deborah Ribeiro Carvalho; Carlos N. Silla – IEEE Transactions on Learning Technologies, 2024
Throughout a programming course, students develop various source code tasks. Using these tasks to track students' progress can provide clues to the strengths and weaknesses found in each learning topic. This practice allows the teacher to intervene in learning in the first few weeks of class and maximize student gains. However, the biggest…
Descriptors: Computation, Models, Ability Grouping, Programming
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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
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Pavlos Toukiloglou; Stelios Xinogalos – Education and Information Technologies, 2024
Hour of Code is a widely recognized global event that aims to introduce programming to novice users and integrate computer science into education. This paper presents an analysis of the effectiveness of the support system and user interface of Minecraft Adventurer, a serious game designed for the Hour of Code global event. Although previous…
Descriptors: Novices, Programming, Coding, Computer Science 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
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Andrew Millam; Christine Bakke – Journal of Information Technology Education: Innovations in Practice, 2024
Aim/Purpose: This paper is part of a multi-case study that aims to test whether generative AI makes an effective coding assistant. Particularly, this work evaluates the ability of two AI chatbots (ChatGPT and Bing Chat) to generate concise computer code, considers ethical issues related to generative AI, and offers suggestions for how to improve…
Descriptors: Coding, Artificial Intelligence, Natural Language Processing, Computer Software
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Tuba Ketenci; Brendan Calandra; Jonathan Cohen; Maggie Renken; Nurjamal Chonoeva – Journal of Research on Technology in Education, 2023
The goal of this study was to examine how two groups of middle school students' self-efficacy, interest, goal orientation, and prior experience related to evidence of their building upon existing ideas and code in digital artifacts they created using MIT's App Inventor, a computational practice that Brennan and Resnick (2012) identified as…
Descriptors: Middle School Students, Coding, Computer Science Education, Self Efficacy
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Dan Sun; Fan Xu – Journal of Educational Computing Research, 2025
Real-time collaborative programming (RCP), which allows multiple programmers to work concurrently on the same codebase with changes instantly visible to all participants, has garnered considerable popularity in higher education. Despite this trend, little work has rigorously examined how undergraduates engage in collaborative programming when…
Descriptors: Cooperative Learning, Programming, Computer Science Education, Undergraduate Students
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David P. Bunde; John F. Dooley – PRIMUS, 2024
We present a detailed description of a Cryptography and Computer Security course that has been offered at Knox College for the last 15 years. While the course is roughly divided into two sections, Cryptology and Computer Security, our emphasis here is on the Cryptology section. The course puts the cryptologic material into its historical context…
Descriptors: Technology, Coding, Computer Security, Mathematics Education
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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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Mehmet Ceylan; Durmus Aslan – Education and Information Technologies, 2024
This study was conducted to investigate the effects of learning trajectories-based coding (LTs) and LTs-based program on preschoolers' length, area, volume, and angle measurement skills. A quasi-experimental research design was utilized with a quantitative approach. The study's participants were 47 children between the ages of 55-71 months who…
Descriptors: Learning Trajectories, Coding, Mathematics Skills, Measurement Techniques
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Mark Frydenberg; Anqi Xu; Jennifer Xu – Information Systems Education Journal, 2025
This study explores student perceptions of learning to code by evaluating AI-generated Python code. In an experimental exercise given to students in an introductory Python course at a business university, students wrote their own solutions to a Python program and then compared their solutions with AI-generated code. They evaluated both solutions…
Descriptors: Student Attitudes, Programming, Computer Software, Quality Assurance
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Stella Xin Yin; Dion Hoe-Lian Goh; Choon Lang Quek; Zhengyuan Liu – Educational Technology & Society, 2025
With the growing popularity of computational thinking (CT) classes in K-12 schools, it is important to investigate public perceptions of these initiatives. Analyzing public discussions and opinions provides valuable insights that can inform future educational policies and reforms. In this paper, we collected questions and answers related to CT…
Descriptors: Computation, Thinking Skills, Elementary Secondary Education, Public Opinion
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Mayowa Oyedoyin; Ismaila Temitayo Sanusi; Musa Adekunle Ayanwale – Computer Science Education, 2025
Background and Context: Recognizing that digital technologies can enable economic transformation in Africa, computing education has been considered a subject relevant for all within the compulsory level of education. The implementation of the subject in many schools is, however, characterized by a myriad of challenges, including pedagogical…
Descriptors: Elementary School Students, Student Attitudes, Internet, Coding
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