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Hongfeng Zhang; Fanbo Li; Xiaolong Chen – Journal of Educational Computing Research, 2025
This study addresses the gap in understanding graduate students' sustained engagement behavior (SEB) with generative artificial intelligence (GAI) by integrating the Technology Acceptance Model (TAM), Expectation Confirmation Theory (ECT), and Theory of Reasoned Action (TRA) into a comprehensive embedding model. It introduces the Technology…
Descriptors: Graduate Students, Artificial Intelligence, Learner Engagement, Foreign Countries
Eunsung Park; Jongpil Cheon – Journal of Educational Computing Research, 2025
Debugging is essential for identifying and rectifying errors in programming, yet time constraints and students' trivialization of errors often hinder progress. This study examines differences in debugging challenges and strategies among students with varying computational thinking (CT) competencies using weekly coding journals from an online…
Descriptors: Undergraduate Students, Programming, Computer Software, Troubleshooting
Lin Zhang; Qiang Jiang; Weiyan Xiong; Wei Zhao – Journal of Educational Computing Research, 2025
This study seeks to deepen the understanding of the direct and indirect effects of human-computer dialogic interaction programming activities, facilitated by ChatGPT, on student engagement. Data were collected from 109 Chinese high school students who engaged in programming tasks using either ChatGPT-driven dialogic interaction or traditional pair…
Descriptors: Artificial Intelligence, Computer Software, Computer Science Education, Programming
Joseph, Lumy; Abraham, Sajimon; Mani, Biju P.; N., Rajesh – Journal of Educational Computing Research, 2022
A fixed learning path for all learners is a major drawback of virtual learning systems. An online learning path recommendation system has the advantage of offering flexibility to select appropriate learning content. Learning Analytics Intervention (LAI) provides several educational benefits, particularly for low-performing students. Researchers…
Descriptors: Cognitive Style, Learning Analytics, Educational Benefits, Integrated Learning Systems
Meier, Heidi; Lepp, Marina – Journal of Educational Computing Research, 2023
Especially in large courses, feedback is often given only on the final results; less attention is paid to the programming process. Today, however, some programming environments, e.g., Thonny, log activities during programming and have the functionality of replaying the programming process. This information can be used to provide feedback, and this…
Descriptors: Programming, Introductory Courses, Computer Science Education, Teaching Methods
Xiao, Ya; Hew, K. F. – Journal of Educational Computing Research, 2022
Evolving information and communication technology (ICT) reshapes people's reading activities by popularizing digital reading. Past studies focused on the relationships between students' frequency of ICT use and reading performance but neglected the possible interrelationships between students' ICT-related psychological factors, school contextual…
Descriptors: Comparative Analysis, Information Technology, Telecommunications, Psychological Patterns
Xiaoman Wang; Rui Huang; Max Sommer; Bo Pei; Poorya Shidfar; Muhammad Shahroze Rehman; Albert D. Ritzhaupt; Florence Martin – Journal of Educational Computing Research, 2024
The purpose of this research study was to examine the overall effect of adaptive learning systems deployed using artificial intelligence technology across a range of relevant variables (e.g., duration, student level, etc.). Following a systematic procedure, this meta-analysis examined literature from 18 academic databases and identified N = 45…
Descriptors: Meta Analysis, Outcomes of Education, Artificial Intelligence, Learning Management Systems
Lee, Hsin-Yu; Cheng, Yu-Ping; Wang, Wei-Sheng; Lin, Chia-Ju; Huang, Yueh-Min – Journal of Educational Computing Research, 2023
Given the inadequacy of assessed outcomes (e.g., final exam) and the importance of evaluating the learning process in STEM education, we use deep learning to develop the STEM learning behavior analysis system (SLBAS) to assess the behavior of learners in STEM education. We map learner behavior to the ICAP (interactive, constructive, active,…
Descriptors: Learning Processes, Instructional Effectiveness, STEM Education, Student Behavior
Chengliang Wang; Xiaojiao Chen; Yifei Li; Pengju Wang; Haoming Wang; Yuanyuan Li – Journal of Educational Computing Research, 2025
This study explored the impact of MetaClassroom, a virtual immersive programming learning environment designed based on the three-dimensional learning progression (3DLP) concept, on students' multidimensional development. Utilizing a quasi-experimental research design, this study compared students' programming learning achievements (PLA),…
Descriptors: Programming, Computer Science Education, Metacognition, Computer Simulation
Qing Guo; Junwen Zhen; Fenglin Wu; Yanting He; Cuilan Qiao – Journal of Educational Computing Research, 2025
The rapid development of large language models (LLMs) presented opportunities for the transformation of science and STEM education. Research on LLMs was in the exploratory phase, characterized by discussions and observations rather than empirical investigations. This study presented a framework for incorporating LLMs into Science and Engineering…
Descriptors: STEM Education, Computational Linguistics, Teaching Methods, Educational Change
Su, Yu-Sheng; Shao, Mingming; Zhao, Li – Journal of Educational Computing Research, 2022
Scratch, a kind of visual programming software, has been widely used in instruction for primary school children. Scratch constructs a digital world for children to design, develop, and create coursework in which their creative thinking is fostered. Different instructional methods have been designed and implemented to stimulate children's creative…
Descriptors: Cognitive Mapping, Creative Thinking, Creativity Tests, Computer Software
Lijuan Feng – Journal of Educational Computing Research, 2025
This study investigates the impact of AI-assisted language learning (AIAL) strategies on cognitive load and learning outcomes in the context of language acquisition. Specifically, the study explores three distinct AIAL strategies: personalized feedback and adaptive learning, interactive exercises with speech recognition, and intelligent tutoring…
Descriptors: Artificial Intelligence, Computer Assisted Instruction, Second Language Learning, Second Language Instruction
Shin, Yoonhee; Song, Donggil – Journal of Educational Computing Research, 2022
This study explores the effect of self-regulated learning support on learners' cognitive load and problem-solving performance, considering cases from well-structured to ill-structured tasks in a computer programing course. Sixty-seven undergraduate students in a computer programing fundamentals course were randomly assigned into one of two groups:…
Descriptors: Cognitive Ability, Computer Science Education, Programming, Problem Solving
Hwang, Gwo-Jen; Tung, Li-Hsien; Fang, Jian-Wen – Journal of Educational Computing Research, 2023
Fostering students' computer programming skills has become an important educational issue in the globe. However, it remains a challenge for students to understand those abstract concepts when learning computer programming, implying the need to provide instant learning diagnosis and feedback in computer programming activities. In this study, a…
Descriptors: Programming, Thinking Skills, Problem Solving, Computer Science Education
Wu, Ting-Ting; Chen, Jian-Ming – Journal of Educational Computing Research, 2022
Many countries have incorporated computational thinking (CT) and programming languages into their science and technology courses. Students can improve their CT ability by learning programming languages. Moreover, situated learning enables students to generate knowledge and master problem-solving skills through interaction with situations. This…
Descriptors: Computer Software, Thinking Skills, Programming, Situated Learning