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Kevin Slonka; Matthew North; Neelima Bhatnagar; Anthony Serapiglia – Information Systems Education Journal, 2025
Continuing to fill the literature gap, this research replicated and expands a prior study of student performance in database normalization in an introductory database course. The data was collected from four different universities, each having different prerequisite courses for their database course. Student performance on a database normalization…
Descriptors: Required Courses, Academic Achievement, Information Systems, Databases
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
Jozsef Katona; Klara Ida Katonane Gyonyoru – TechTrends: Linking Research and Practice to Improve Learning, 2025
In the context of the digital economy, programming proficiency is an essential competency that promotes upward socio-economic mobility and expands career opportunities. However, students from socially disadvantaged backgrounds often face significant barriers to acquiring these skills, such as limited access to technology and educational resources.…
Descriptors: Artificial Intelligence, Technology Uses in Education, Programming, Computer Science Education
UK Department for Education, 2024
From September 2023 to March 2024, Faculty AI, the National Institute of Teaching (NIoT) and ImpactEd Group (representing the AI in Schools Initiative) have worked with the Department for Education (DfE) to deliver the Use Cases for Generative Artificial Intelligence in Education project. The project explored potential applications for Generative…
Descriptors: Artificial Intelligence, Technology Uses in Education, Ethics, Computer Science
Collins, Jazmin; Ford, Vitaly – Journal of Cybersecurity Education, Research and Practice, 2023
The use of the Capture the Flag (CTF)-style competitions has grown popular in a variety of environments as a method to improve or reinforce cybersecurity techniques. However, while these competitions have shown promise in student engagement, enjoyment, and the teaching of essential workforce cybersecurity concepts, many of these CTF challenges…
Descriptors: Computer Security, Computer Science Education, Coding, Competition
Tarling, Georgie; Melro, Ana; Kleine Staarman, Judith; Fujita, Taro – Pedagogies: An International Journal, 2023
Coding bootcamps targeting diverse learners are increasingly popular. However, little research has focused on the student experience of these courses: what pedagogic practices make learning coding meaningful for them and why. In a previous paper, we proposed a conceptual framework outlining three dimensions of learning opportunities in relation to…
Descriptors: Student Attitudes, Coding, Programming, Computer Science Education
Lung-Chun Chang; Hon-Ren Lin; Jian-Wei Lin – Education and Information Technologies, 2024
Many students want to enroll in programming courses but fear the challenges ahead. They aspire to design quality systems or games after acquiring related skills but report concerns that programming logic is too difficult to learn because memorization of the syntax is required. Thus, they experience anxiety, are demotivated to learn, and,…
Descriptors: Learning Motivation, Outcomes of Education, Anxiety, Programming
Grethe Sandstrak; Bjorn Klefstad; Arne Styve; Kiran Raja – IEEE Transactions on Education, 2024
Teaching programming efficiently to students in the first year of computer science education is challenging. It is especially cumbersome to retain the interest of both groups, when the student group consists of novice (i.e., those who have never programmed before) and expert programmers in the same crowd. Thus, individualized teaching cannot be…
Descriptors: Computer Science Education, Programming, Teaching Methods, College Freshmen
Olivares, Daniel; Hundhausen, Christopher; Ray, Namrata – ACM Transactions on Computing Education, 2022
As in other STEM disciplines, early computing courses tend to stress individual assignments and discourage collaboration. This can lead to negative learning experiences that compel some students to give up. According to social learning theory, one way to improve students' learning experiences is to help them form and participate actively in…
Descriptors: Intervention, Interpersonal Relationship, Programming, Computer Science Education
Mary Conyers Tucker – ProQuest LLC, 2022
Learning to program is increasingly important. Yet, it is becoming clear that most students struggle when learning to program (McCracken et al., 2001). This is leading to a divide where some people can program but many others can't. Prior research has traced poor student outcomes to their early experiences learning programming. Still, little is…
Descriptors: Teaching Methods, Programming, Computer Science Education, Student Motivation
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
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
Haoming Wang; Chengliang Wang; Zhan Chen; Fa Liu; Chunjia Bao; Xianlong Xu – Education and Information Technologies, 2025
With the rapid development of artificial intelligence technology in the field of education, AI-Agents have shown tremendous potential in collaborative learning. However, traditional Computer-Supported Collaborative Learning (CSCL) methods still have limitations in addressing the unique demands of programming education. This study proposes an…
Descriptors: Artificial Intelligence, Cooperative Learning, Programming, Computer Science Education
Domicián Máté; Judit T. Kiss; Mária Csernoch – Education and Information Technologies, 2025
The impact of cognitive biases, particularly biased self-assessment, on learning outcomes and decision-making in higher education is of great significance. This study delves into the confluence of cognitive biases and user experience in spreadsheet programming as a crucial IT skill across various academic disciplines. Through a quantitative…
Descriptors: Programming, Spreadsheets, Computer Science Education, STEM Education
Fu, Qian; Zheng, Yafeng; Zhang, Mengyao; Zheng, Lanqin; Zhou, Junyi; Xie, Bochao – Educational Technology Research and Development, 2023
Providing appropriate feedback is important when learning to program. However, it is still unclear how different feedback strategies affect learning outcomes in programming. This study designed four different two-step programming feedback strategies and explored their impact on novice programmers' academic achievement, learning motivations, and…
Descriptors: Feedback (Response), Academic Achievement, Novices, Programming

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