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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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Chen, Peggy P. – New Directions for Teaching and Learning, 2023
Many introductory computer science (CS) courses are intended to address the increased demand for computer literacy and the development of cross-cutting concepts and practices of computational thinking (CT). Colleges and universities offer introductory CS courses every semester toward this end. The issue is centered on how to support CT learning in…
Descriptors: Introductory Courses, Computer Science Education, Computer Literacy, Thinking Skills
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Antti-Jussi Lakanen; Ville Isomöttönen – Informatics in Education, 2023
This research investigates university students' success in their first programming course (CS1) in relation to their motivation, mathematical ability, programming self-efficacy, and initial goal setting. To our knowledge, these constructs have not been measured in a single study before in the Finnish context. The selection of the constructs is in…
Descriptors: Foreign Countries, College Students, Student Motivation, Self Efficacy
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Vandenberg, Jessica; Lynch, Collin; Boyer, Kristy Elizabeth; Wiebe, Eric – Computer Science Education, 2023
Background and Context: Students' self-efficacy toward computing affect their participation in related tasks and courses. Self-efficacy is likely influenced by students' initial experiences and exposure to computer science (CS) activities. Moreover, student interest in a subject likely informs their ability to effectively regulate their learning…
Descriptors: Elementary School Students, Cooperative Learning, Programming, Network Analysis
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Priti Oli; Rabin Banjade; Jeevan Chapagain; Vasile Rus – Grantee Submission, 2023
This paper systematically explores how Large Language Models (LLMs) generate explanations of code examples of the type used in intro-to-programming courses. As we show, the nature of code explanations generated by LLMs varies considerably based on the wording of the prompt, the target code examples being explained, the programming language, the…
Descriptors: Computational Linguistics, Programming, Computer Science Education, Programming Languages
Méndez Irizarry, Alejandra S. – ProQuest LLC, 2023
This doctoral dissertation documents the experiences of women (student and faculty) in computer science programs. The research emerges from the literature on the gender gap in computing and video gaming. Thus, the author seeks to find the meaning that participants have granted to their experiences as undergraduate students and faculty, in a…
Descriptors: Females, Computer Science Education, Video Games, Gender Differences
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Amoudi, Ghada; Tbaishat, Dina – Education and Information Technologies, 2023
Social network analysis involves delicate and sophisticated mathematical concepts which are abstract and challenging to acquire by traditional methods. Many studies show that female students perform poorly in computer science-related courses compared to male students. To address these issues, this research investigates the impact of employing a…
Descriptors: Computer Science, Graduate Students, Outcomes of Education, Educational Technology
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Yuan-Chen Liu; Tzu-Hua Huang; Chien-Chia Huang – Interactive Learning Environments, 2024
In this study, an interactive programming learning environment was built with two types of error prompt functions: 1) the key prompt and 2) step-by-step prompt. A quasi-experimental study was conducted for five weeks, in which 75 sixth grade students from disadvantaged learning environments in Taipei, Taiwan, were divided into three groups: 1) the…
Descriptors: Programming, Computer Science Education, Cues, Grade 6
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Gang Yang; Dan Zheng; Ji-Huan Chen; Qun-Fang Zeng; Yun-Fang Tu; Xiao-Li Zheng – Interactive Learning Environments, 2024
The game-based learning approach to developing students' computational thinking (CT) current has received attention from researchers. However, the compatibility between games and instruction is often insufficient to accommodate the entertaining and educational nature of the curriculum entirely, and the benefits of game-based learning could be…
Descriptors: Role Playing, Educational Games, Mental Computation, Learner Engagement
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Hugo G. Lapierre; Patrick Charland; Pierre-Majorique Léger – Computer Science Education, 2024
Background and Context: Current programming learning research often compares novices and experienced programmers, leaving early learning stages and emotional and cognitive states under-explored. Objective: Our study investigates relationships between cognitive and emotional states and learning performance in early stage programming learners with…
Descriptors: Programming, Computer Science Education, Psychological Patterns, Cognitive Processes
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Dan Sun; Fan Ouyang; Yan Li; Chengcong Zhu; Yang Zhou – Journal of Computer Assisted Learning, 2024
Background: With the development of computational literacy, there has been a surge in both research and practice application of text-based and block-based modalities within the field of computer programming education. Despite this trend, little work has actually examined how learners engaging in programming process when utilizing these two major…
Descriptors: Computer Science Education, Programming, Computer Literacy, Comparative Analysis
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Orly Barzilai; Sofia Sherman; Moshe Leiba; Hadar Spiegel – Journal of Information Systems Education, 2024
Data Structures and Algorithms (DS) is a basic computer science course that is a prerequisite for taking advanced information systems (IS) curriculum courses. The course aims to teach students how to analyze a problem, design a solution, and implement it using pseudocode to construct knowledge and develop the necessary skills for algorithmic…
Descriptors: Statistics Education, Problem Solving, Information Systems, Algorithms
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Fan Xu; Ana-Paula Correia – Journal of Computing in Higher Education, 2024
As online learning has become an inevitable trend in the post-peak era of the COVID-19 pandemic, distributed pair programming (DPP) is gaining momentum in both education and industry. DDP serves as a collaborative programming approach and also benefits the development of computational thinking, a fundamental skill in today's world. This study…
Descriptors: Programming, Computer Science Education, Cooperative Learning, Learning Activities
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Ying-Chieh Liu; Hung-Yi Chen – IEEE Transactions on Education, 2025
Contribution: Expand the scope of factors influencing self-efficacy and highlight the importance of teaching quality, peer support, perceived course value, the moderating effects of self-regulation, and adversity quotient (AQ). Background: Self-efficacy has been regarded as an important factor in students' learning performance. However, little…
Descriptors: Foreign Countries, College Students, College Faculty, Programming
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Guangrui Fan; Dandan Liu; Rui Zhang; Lihu Pan – International Journal of STEM Education, 2025
Purpose: This study investigates the impact of AI-assisted pair programming on undergraduate students' intrinsic motivation, programming anxiety, and performance, relative to both human-human pair programming and individual programming approaches. Methods: A quasi-experimental design was conducted over two academic years (2023-2024) with 234…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Programming
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