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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
Sanz, Cecilia; Coma-Rosello, Teresa; Aguelo, Antonio; Alvarez, Pedro; Baldassarri, Sandra – IEEE Transactions on Education, 2023
Contribution: This article proposes and applies a new systemic 3-D model and a methodology for empathy awareness and development, integrating different partial approaches found in the literature for developing empathy as a transversal competence. Background: Empathy is a competence linked to collaboration and teamwork. Perspective taking (PT) is…
Descriptors: Empathy, Computer Science Education, Models, Emotional Development
Remsh Nasser Alqahtani; Ahmad Zaid Almassaad – Education and Information Technologies, 2025
The aim of research is to reveal the effect of a training program based on the TAWOCK model for teaching computational thinking skills on teaching self-efficacy among computer teachers. It used the quasi-experimental approach, with a pre-test and post-test design with a control group. An electronic training program based on the TAWOCK model was…
Descriptors: Models, Teaching Methods, Computation, Thinking Skills
Maciej Pankiewicz; Yang Shi; Ryan S. Baker – International Educational Data Mining Society, 2025
Knowledge Tracing (KT) models predicting student performance in intelligent tutoring systems have been successfully deployed in several educational domains. However, their usage in open-ended programming problems poses multiple challenges due to the complexity of the programming code and a complex interplay between syntax and logic requirements…
Descriptors: Algorithms, Artificial Intelligence, Models, Intelligent Tutoring Systems
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
Bolloju, Narasimha – ACM Transactions on Computing Education, 2022
Domain models in software engineering--often represented as class diagrams--depict relevant classes in a given problem domain along with necessary relationships among those classes. These models are important because they establish links between the requirements of a given system under development and the subsequent phases of the systems…
Descriptors: Models, Computer Software, Student Attitudes, Cooperation
Christina Glasauer; Martin K. Yeh; Lois Anne DeLong; Yu Yan; Yanyan Zhuang – Computer Science Education, 2025
Background and Context: Feedback on one's progress is essential to new programming language learners, particularly in out-of-classroom settings. Though many study materials offer assessment mechanisms, most do not examine the accuracy of the feedback they deliver, nor give evidence on its validity. Objective: We investigate the potential use of a…
Descriptors: Novices, Computer Science Education, Programming, Accuracy
Xiaojing Duan; Bo Pei; G. Alex Ambrose; Arnon Hershkovitz; Ying Cheng; Chaoli Wang – Education and Information Technologies, 2024
Providing educators with understandable, actionable, and trustworthy insights drawn from large-scope heterogeneous learning data is of paramount importance in achieving the full potential of artificial intelligence (AI) in educational settings. Explainable AI (XAI)--contrary to the traditional "black-box" approach--helps fulfilling this…
Descriptors: Academic Achievement, Artificial Intelligence, Prediction, Models
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
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
Kamil Çelik; Ahmet Ayaz – Educational Technology Research and Development, 2025
Technological advancements in recent years have accelerated the development of information and communication technologies, introducing numerous innovations. One prominent innovation is the concept of the metaverse, which has gained significant popularity and is increasingly influencing various sectors, including the economy, art, entertainment,…
Descriptors: Artificial Intelligence, Technology Uses in Education, Intention, Computer Science Education
Muhammet Yildirim; Yigit Emrah Turgut – Journal of Pedagogical Research, 2025
This study aimed to examine the impact of the flipped classroom model applied in the information technologies courses on pre-service teachers' candidates' academic achievements, self-regulated learning skills, and classroom engagement. The research was conducted with a total of 96 pre-service teachers teacher candidates, 48 in the experimental…
Descriptors: Flipped Classroom, Academic Achievement, Metacognition, Comparative Analysis
Andreas Marougkas; Christos Troussas; Akrivi Krouska; Cleo Sgouropoulou – Smart Learning Environments, 2025
Virtual Reality has proven to be highly promising within the field of learning. Most VR learning methods do not effectively implement pedagogical models or adapt to the individual's learning style. This research aims to bridge this gap by integrating Fuzzy Cognitive Maps (FCMs), Flow Theory and Gamification within an educational Virtual Reality…
Descriptors: Computer Simulation, Computer Games, Educational Games, Computer Science Education
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
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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