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Mark Frydenberg; Anqi Xu; Jennifer Xu – Information Systems Education Journal, 2025
This study explores student perceptions of learning to code by evaluating AI-generated Python code. In an experimental exercise given to students in an introductory Python course at a business university, students wrote their own solutions to a Python program and then compared their solutions with AI-generated code. They evaluated both solutions…
Descriptors: Student Attitudes, Programming, Computer Software, Quality Assurance
Shu-Jie Chen; Xiaofen Shan; Ze-Min Liu; Chuang-Qi Chen – Educational Technology & Society, 2025
The introduction of programming education in K-12 schools to promote computational thinking has attracted a great deal of attention from scholars and educators. Debugging code is a central skill for students, but is also a considerable challenge when learning to program. Learners at the K-12 level often lack confidence in programming debugging due…
Descriptors: Programming, Coding, Elementary School Students, Secondary School Students
Brittany Devies; Lauren Bullock; Daniel M. Jenkins; Scott J. Allen; Joanna Stanberry – New Directions for Student Leadership, 2025
This article explores the pedagogical considerations of using pop-culture podcasts as an instructional strategy in leadership development. We clarify key concepts, evaluate podcasts as an instructional tool, and provide recommendations and implications for their integration into leadership learning experiences. While an important consideration for…
Descriptors: Leadership Training, Popular Culture, Audio Equipment, Telecommunications
Erkan Er; Gökhan Akçapinar; Alper Bayazit; Omid Noroozi; Seyyed Kazem Banihashem – British Journal of Educational Technology, 2025
Despite the growing research interest in the use of large language models for feedback provision, it still remains unknown how students perceive and use AI-generated feedback compared to instructor feedback in authentic settings. To address this gap, this study compared instructor and AI-generated feedback in a Java programming course through an…
Descriptors: Student Evaluation, Student Attitudes, Feedback (Response), Artificial Intelligence
Erik Forsberg; Anders Sjöberg – Measurement: Interdisciplinary Research and Perspectives, 2025
This paper reports a validation study based on descriptive multidimensional item response theory (DMIRT), implemented in the R package "D3mirt" by using the ERS-C, an extended version of the Relevance subscale from the Moral Foundations Questionnaire including two new items for collectivism (17 items in total). Two latent models are…
Descriptors: Evaluation Methods, Programming Languages, Altruism, Collectivism
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
Stella Xin Yin; Dion Hoe-Lian Goh; Choon Lang Quek; Zhengyuan Liu – Educational Technology & Society, 2025
With the growing popularity of computational thinking (CT) classes in K-12 schools, it is important to investigate public perceptions of these initiatives. Analyzing public discussions and opinions provides valuable insights that can inform future educational policies and reforms. In this paper, we collected questions and answers related to CT…
Descriptors: Computation, Thinking Skills, Elementary Secondary Education, Public Opinion
Seralidou, Eleni; Douligeris, Christos – Education and Information Technologies, 2021
The effective teaching of the concept of programming, where critical thinking is an important factor, is not so easy in secondary education. New teaching approaches, including, game-based learning, may provide a solution due to their inclusion of more fun and diverse activities but they still lack the active participation of the students in the…
Descriptors: Computer Science Education, Programming, Programming Languages, Educational Games
Luo, Xiao – Journal of Educational Measurement, 2020
Automated test assembly (ATA) is a modern approach to test assembly that applies advanced optimization algorithms on computers to build test forms automatically. ATA greatly improves the efficiency and accuracy of the test assembly. This study investigated the effects of the modeling methods and solvers in the mixed-integer programming (MIP)…
Descriptors: Test Construction, Automation, Programming, Models
Echeverri-Jimenez, Emmanuel; Oliver-Hoyo, Maria – Journal of Chemical Education, 2021
Gaussian-2-Blender is an open-source application programming interface (API) written in Python that allows for the conversion of Gaussian input files to 3D objects of different formats. This new tool was developed in response to the shortcomings of available programs to import Gaussian calculations into augmented reality (AR) or virtual reality…
Descriptors: Chemistry, Programming Languages, Computation, Computer Simulation
Cleuziou, Guillaume; Flouvat, Frédéric – International Educational Data Mining Society, 2021
Improving the pedagogical effectiveness of programming training platforms is a hot topic that requires the construction of fine and exploitable representations of learners' programs. This article presents a new approach for learning program embeddings. Starting from the hypothesis that the function of a program, but also its "style", can…
Descriptors: Programming, Computer Science Education, Electronic Learning, Data Analysis
Arif Akçay; Arif Altun – Education and Information Technologies, 2024
Debugging is an intellectually rich and a challenging process when learning a programming language. This process is important for increasing the quality of the program and making it functional. Debugging, by its nature, is thought to be a practice with a state of focus and concentration. This study explored whether the debugging performance could…
Descriptors: Attention, Networks, Troubleshooting, Programming
Hua-Xu Zhong; Jui-Hung Chang; Chin-Feng Lai; Pei-Wen Chen; Shang-Hsuan Ku; Shih-Yeh Chen – Education and Information Technologies, 2024
Artificial intelligence (AI) education is becoming an advanced learning trend in programming education. However, AI subjects can be difficult to understand because they require high programming skills and complex knowledge. This makes it challenging to determine how different departments of students are affected by them. This study draws on…
Descriptors: Undergraduate Students, Artificial Intelligence, Programming, STEM Education
Stamatios, Papadakis – International Journal of Educational Reform, 2024
Computational Thinking (CT) and the understanding of how programs are being executed is internationally acknowledging as a necessity for today's students and citizens of tomorrow. Despite the multifaceted nature of CT, the introduction of CT and associate concepts such as coding is regarded as developmental acceptable for preschool and…
Descriptors: Preschool Children, Computation, Thinking Skills, Programming
Miaoting Cheng; Xiaoyan Lai; Da Tao; Juntong Lai; Jun Yang – Education and Information Technologies, 2024
While numerous studies have highlighted the potential benefits of programming environment (PE) use for children's learning, the boundary conditions of children's PE acceptance within the programming education context are less clear. This study fills this gap in the literature by investigating the critical determinants of children's PE use…
Descriptors: Programming, Intention, Competition, Computation