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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
Yuhan Lin – ProQuest LLC, 2024
Block-based programming environments have become increasingly commonplace in computer science education. Despite a rapidly expanding ecosystem of block-based programming environments, text-based languages remain the dominant programming paradigm outside of educational contexts, motivating the transition from block-based to text-based programming.…
Descriptors: Computer Science Education, Programming, Coding, Scaffolding (Teaching Technique)
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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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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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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
Arawjo, Ian Anders – ProQuest LLC, 2023
I situate computer programming as a cultural practice. I develop this perspective in two ways: exploring how programming practices can support intercultural learning, and examining how programming tools themselves embed cultural assumptions and values. For the former, I study how relationships across difference are formed over computing activities…
Descriptors: Computer Science Education, Programming, Cultural Influences, Elementary Secondary Education
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Gao, Zhikai; Erickson, Bradley; Xu, Yiqiao; Lynch, Collin; Heckman, Sarah; Barnes, Tiffany – International Educational Data Mining Society, 2022
In computer science education timely help seeking during large programming projects is essential for student success. Help-seeking in typical courses happens in office hours and through online forums. In this research, we analyze students coding activities and help requests to understand the interaction between these activities. We collected…
Descriptors: Computer Science Education, College Students, Programming, Coding
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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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Renske Weeda; Sjaak Smetsers; Erik Barendsen – Computer Science Education, 2024
Background and Context: Multiple studies report that experienced instructors lack consensus on the difficulty of programming tasks for novices. However, adequately gauging task difficulty is needed for alignment: to select and structure tasks in order to assess what students can and cannot do. Objective: The aim of this study was to examine…
Descriptors: Novices, Coding, Programming, Computer Science Education
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Peter J. Rich; Scott Bartholomew; David Daniel; Kenzie Dinsmoor; Meagan Nielsen; Connor Reynolds; Meg Swanson; Ellyse Winward; Jessica Yauney – Journal of Research on Technology in Education, 2024
In this study, we attempted to curate a list of tools whose primary intent is to enable and teach children to code. From this list, we developed a framework for the classification of coding tools and reviewed current research to determine how tools are used to teach coding in elementary education. The catalog grew to over 300 specific tools…
Descriptors: Educational Trends, Teaching Methods, Coding, Thinking Skills
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Yong-Woon Choi; In-gyu Go; Yeong-Jae Gil – International Journal of Technology and Design Education, 2024
The purpose of this study is to derive a correlation between the technological thinking disposition and the computational thinking ability of gifted students in Korea. The correlation between each element was analyzed by looking at the sub-elements of computational thinking according to the components of technological thinking disposition. The…
Descriptors: Thinking Skills, Mental Computation, Gifted, Correlation
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Jiangyue Liu; Siran Li – Journal of Educational Computing Research, 2024
Pair Programming is considered an effective approach to programming education, but the synchronous collaboration of two programmers involves complex coordination, making this method difficult to be widely adopted in educational settings. Artificial Intelligence (AI) code-generation tools have outstanding capabilities in program generation and…
Descriptors: Artificial Intelligence, Programming, Technology Uses in Education, Coding
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