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Showing 1 to 15 of 95 results Save | Export
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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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Rong, Wenge; Xu, Tianfan; Sun, Zhiwei; Sun, Zian; Ouyang, Yuanxin; Xiong, Zhang – IEEE Transactions on Education, 2023
Contribution: In this study, an object tuple model has been proposed, and a quasi-experimental study on its usage in an introductory programming language course has been reported. This work can be adopted by all C language teachers and students in learning pointer and array-related concepts. Background: C language has been extensively employed in…
Descriptors: Models, Introductory Courses, Programming, Computer Science Education
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Multazam, Muhammad; Syahrial, Zulfiati; Rusmono – Turkish Online Journal of Distance Education, 2023
Web programming courses are practical courses that can only run with the help of computer devices. The content or learning content in web programming courses is in program code directly created with a computer. The models developed include conceptual models, procedural models, and physical models. The research method used is Research and…
Descriptors: Computer Science Education, Programming, Models, Practicums
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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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Hatice Yildiz Durak – Education and Information Technologies, 2024
Examining middle school students' computational identity development, personal, situational variables and programming experiences through the lens of identity may offer an opportunity to explore the dynamic relationship between individual, academic and social influences in computer science and CI. The aim of this study is to examine the variables…
Descriptors: Middle School Students, Computation, Thinking Skills, Self Concept
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Xin Gong; Shufan Yu; Jie Xu; Ailing Qiao; Han Han – Education and Information Technologies, 2024
Tangible programming combines the advantages of object manipulation with programmable hardware, which plays an essential role in improving programming skills. As a tool for ensuring the quality of projects and improving learning outcomes, the PDCA cycle strategy is conducive to cultivating reflective thinking. However, there is still a lack of…
Descriptors: Programming, Computer Science Education, Outcomes of Education, Reflection
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Zhang, Yingbin; Pinto, Juan D.; Fan, Aysa Xuemo; Paquette, Luc – Journal of Educational Data Mining, 2023
The second CSEDM data challenge aimed at finding innovative methods to use students' programming traces to model their learning. The main challenge of this task is how to decide which past problems are relevant for predicting performance on a future problem. This paper proposes a set of weighting schemes to address this challenge. Specifically,…
Descriptors: Problem Solving, Introductory Courses, Computer Science Education, Programming
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Duran, Rodrigo; Sorva, Juha; Seppälä, Otto – ACM Transactions on Computing Education, 2021
We propose a framework for identifying, organizing, and communicating learning objectives that involve program semantics. In this framework, detailed learning objectives are written down as rules of program behavior (RPBs). RPBs are teacher-facing statements that describe what needs to be learned about the behavior of a specific sort of programs.…
Descriptors: Behavioral Objectives, Computer Science Education, Programming, Evaluation Criteria
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Garcia, Manuel B. – Journal of Educational Computing Research, 2023
Computer programming is a difficult course for many students. Prior works advocated for group learning pedagogies in pursuit of higher-level reasoning and conceptual understanding. However, the methodological gaps in existing implementations warrant further research. This study conducted a three-armed cluster-randomized controlled trial to…
Descriptors: Computer Science Education, Programming, Cooperative Learning, Apprenticeships
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Guozhu Ding; Xiangyi Shi; Shan Li – Education and Information Technologies, 2024
In this study, we developed a classification system of programming errors based on the historical data of 680,540 programming records collected on the Online Judge platform. The classification system described six types of programming errors (i.e., syntax, logical, type, writing, misunderstanding, and runtime errors) and their connections with…
Descriptors: Programming, Computer Science Education, Classification, Graphs
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Chung, Cheng-Yu; Hsiao, I-Han; Lin, Yi-Ling – Journal of Research on Technology in Education, 2023
Creating practice questions for programming learning is not an easy job. It requires the instructor to diligently organize heterogeneous learning resources. Although educational technologies have been adopted across levels of programming learning, programming question generation (PQG) is still predominantly performed by instructors without…
Descriptors: Artificial Intelligence, Programming, Questioning Techniques, Heterogeneous Grouping
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Rosenberg-Kima, Rinat B.; Merrill, M. David; Baylor, Amy L.; Johnson, Tristan E. – Educational Technology Research and Development, 2022
Novice programmers, who have yet to form effective mental models of the domain, often experience high cognitive load, low confidence, and high anxiety, negatively affecting learning and retention rates. These cognitive and affective limitations pose an instructional challenge. This study aimed to investigate the effectiveness of a whole-task…
Descriptors: Computer Science Education, Instructional Effectiveness, Novices, Programming
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Dorodchi, Mohsen; Dehbozorgi, Nasrin; Fallahian, Mohammadali; Pouriyeh, Seyedamin – Informatics in Education, 2021
Teaching software engineering (SWE) as a core computer science course (ACM, 2013) is a challenging task. The challenge lies in the emphasis on what a large-scale software means, implementing teamwork, and teaching abstraction in software design while simultaneously engaging students into reasonable coding tasks. The abstraction of the system…
Descriptors: Computer Science Education, Computer Software, Teaching Methods, Undergraduate Students
Chongning Sun – ProQuest LLC, 2021
Self-efficacy is seen as a barrier for youth, females in particular, to enter computer science (CS). In this study, I presented a near-peer mentoring model that focused on changing the mentee's self-efficacy in CS. The present study had three objectives: (a) to design a near-peer mentoring model (i.e., a conceptual model) around the sources of…
Descriptors: Peer Teaching, Mentors, Self Efficacy, Programming
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Denis Zhidkikh; Ville Heilala; Charlotte Van Petegem; Peter Dawyndt; Miitta Jarvinen; Sami Viitanen; Bram De Wever; Bart Mesuere; Vesa Lappalainen; Lauri Kettunen; Raija Hämäläinen – Journal of Learning Analytics, 2024
Predictive learning analytics has been widely explored in educational research to improve student retention and academic success in an introductory programming course in computer science (CS1). General-purpose and interpretable dropout predictions still pose a challenge. Our study aims to reproduce and extend the data analysis of a privacy-first…
Descriptors: Learning Analytics, Prediction, School Holding Power, Academic Achievement
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