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Andrew Millam; Christine Bakke – Journal of Information Technology Education: Innovations in Practice, 2024
Aim/Purpose: This paper is part of a multi-case study that aims to test whether generative AI makes an effective coding assistant. Particularly, this work evaluates the ability of two AI chatbots (ChatGPT and Bing Chat) to generate concise computer code, considers ethical issues related to generative AI, and offers suggestions for how to improve…
Descriptors: Coding, Artificial Intelligence, Natural Language Processing, Computer Software
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Cheers, Hayden; Lin, Yuqing – Computer Science Education, 2023
Background and Context: Source code plagiarism is a common occurrence in undergraduate computer science education. Many source code plagiarism detection tools have been proposed to address this problem. However, such tools do not identify plagiarism, nor suggest what assignment submissions are suspicious of plagiarism. Source code plagiarism…
Descriptors: Plagiarism, Programming, Computer Science Education, Identification
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Gerit Wagner; Laureen Thurner – Journal of Information Systems Education, 2025
Git, as the leading version-control system, is frequently employed by software developers, digital product managers, and knowledge workers. Information systems (IS) students aspiring to fill software engineering, management, or research positions would therefore benefit from familiarity with Git. However, teaching Git effectively can be…
Descriptors: Computer Science Education, Information Systems, Teaching Methods, Computer Software
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Sonia Lorente; Mónica Arnal-Palacián; Maximiliano Paredes-Velasco – European Journal of Psychology of Education, 2024
The European Higher Education Area (EHEA) proposes to enhance active learning and student protagonism in order to improve academic performance. In this sense, different methodologies are emerging to create scenarios for self-regulation of their learning. In this study the cooperative, collaborative and interdisciplinary learning methodologies were…
Descriptors: Cooperative Learning, Interdisciplinary Approach, Computer Software, Universities
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Leite, Ana Isabella Muniz; Lagoa, Lucas; Lopes, Samuel; Braga, Rosana; Antonino, Pablo Oliveira; Nakagawa, Elisa Yumi – IEEE Transactions on Education, 2022
Contribution: This article details the conduction of an experiment to investigate the knowledge that computer science graduate students have about safety-critical systems development, in particular, safety requirements specifications. Future research directions are also discussed. Background: Safety-critical systems have been increasingly used in…
Descriptors: Graduate Students, Computer Science Education, Knowledge Level, Safety
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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
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David R. Firth; Adam Gonzales; Michelle Louch; Bryan Hammer – Information Systems Education Journal, 2025
ChatGPT is having an impact on students, and information systems (IS) and computing academic professionals alike. Our goal for this paper is to help faculty and students know the conditions in which generative AI such as ChatGPT should or should not be used. To that end, we describe the development of a 2x2 matrix. On the horizontal axis we have…
Descriptors: Artificial Intelligence, Computer Software, Synchronous Communication, Information Systems
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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
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Srecko Stamenkovic; Nenad Jovanovic – IEEE Transactions on Learning Technologies, 2024
Although we are witnessing the accelerated development of computer science, and the opening of new fields of study, compiler construction is still a very important field that is taught at most world universities. Because of a large number of algorithms and complex theoretical constructions, these topics represent a difficult and complex domain for…
Descriptors: Computer Science, Computer Software, Educational Technology, Computer Simulation
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Magana, Alejandra J.; Amuah, Theodora; Aggrawal, Sakhi; Patel, Devang A. – International Journal of STEM Education, 2023
Background: Effectively facilitating teamwork experiences, particularly in the context of large-size courses, is difficult to implement. This study seeks to address the challenges of implementing effective teamwork experiences in large courses. This study integrated teamwork pedagogy to facilitate a semester-long project in the context of a…
Descriptors: Teamwork, Group Dynamics, Cooperative Learning, Large Group Instruction
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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
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Rebecka Weegar; Peter Idestam-Almquist – International Journal of Artificial Intelligence in Education, 2024
Machine learning methods can be used to reduce the manual workload in exam grading, making it possible for teachers to spend more time on other tasks. However, when it comes to grading exams, fully eliminating manual work is not yet possible even with very accurate automated grading, as any grading mistakes could have significant consequences for…
Descriptors: Grading, Computer Assisted Testing, Introductory Courses, Computer Science Education
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Holanda, Maristela; Da Silva, Dilma – IEEE Transactions on Education, 2022
Contributions: The underrepresentation of women in computer science (CS) majors has long been a focus of attention in many academic documents, the majority of them from the United States and Europe. There is, however, a lack of information about educational interventions (EIs) for women in computing in Latin America. The contribution of this…
Descriptors: Foreign Countries, Hispanic American Students, Disproportionate Representation, Computer Science
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Cheers, Hayden; Lin, Yuqing; Yan, Weigen – Informatics in Education, 2023
Source code plagiarism is a common occurrence in undergraduate computer science education. Many source code plagiarism detection tools have been proposed to address this problem. However, most of these tools only measure the similarity between assignment submissions, and do not actually identify which are suspicious of plagiarism. This work…
Descriptors: Plagiarism, Assignments, Computer Software, Computer Science Education
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Turhan, Cigdem; Akman, Ibrahim; Hacaloglu, Tuna – Interactive Learning Environments, 2022
The instructors generally utilize conventional methods in teaching software engineering courses, where the students are provided theoretical knowledge based on text books or lecture notes. Usage of collaborative tools may be a solution to the problems of not practicing the depth of the components of the subject. This study proposes the usage of a…
Descriptors: Computer Mediated Communication, Computer Software, Computer Science Education, Cooperation
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