Publication Date
In 2025 | 6 |
Since 2024 | 17 |
Since 2021 (last 5 years) | 29 |
Since 2016 (last 10 years) | 36 |
Since 2006 (last 20 years) | 46 |
Descriptor
Artificial Intelligence | 47 |
College Students | 47 |
Computer Science Education | 44 |
Foreign Countries | 21 |
Programming | 17 |
Student Attitudes | 17 |
Technology Uses in Education | 17 |
Computer Software | 16 |
Electronic Learning | 11 |
Teaching Methods | 11 |
Educational Technology | 10 |
More ▼ |
Source
Author
Ahmet Ayaz | 1 |
Alexander Tobias Neumann | 1 |
Alexandra R. Costa | 1 |
Amandi, Analia | 1 |
Amélia Caldeira | 1 |
Anqi Xu | 1 |
Anusha Kamath | 1 |
Arzu Deveci Topal | 1 |
Asiye Toker Gokce | 1 |
Atharva Naik | 1 |
Aynur Kolburan Geçer | 1 |
More ▼ |
Publication Type
Journal Articles | 36 |
Reports - Research | 34 |
Speeches/Meeting Papers | 6 |
Collected Works - Proceedings | 5 |
Reports - Descriptive | 4 |
Reports - Evaluative | 4 |
Information Analyses | 1 |
Tests/Questionnaires | 1 |
Education Level
Higher Education | 47 |
Postsecondary Education | 45 |
Adult Education | 3 |
Elementary Secondary Education | 3 |
Secondary Education | 3 |
Junior High Schools | 2 |
Middle Schools | 2 |
Elementary Education | 1 |
Grade 9 | 1 |
High Schools | 1 |
Audience
Teachers | 1 |
Location
Brazil | 3 |
Germany | 3 |
Australia | 2 |
Canada | 2 |
Connecticut | 2 |
Italy | 2 |
Japan | 2 |
Philippines | 2 |
Portugal | 2 |
Spain | 2 |
Taiwan | 2 |
More ▼ |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Atharva Naik; Jessica Ruhan Yin; Anusha Kamath; Qianou Ma; Sherry Tongshuang Wu; R. Charles Murray; Christopher Bogart; Majd Sakr; Carolyn P. Rose – British Journal of Educational Technology, 2025
The relative effectiveness of reflection either through student generation of contrasting cases or through provided contrasting cases is not well-established for adult learners. This paper presents a classroom study to investigate this comparison in a college level Computer Science (CS) course where groups of students worked collaboratively to…
Descriptors: Cooperative Learning, Reflection, College Students, Computer Science Education
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
Cheng, Yu-Ping; Cheng, Shu-Chen; Huang, Yueh-Min – International Review of Research in Open and Distributed Learning, 2022
Online learning has been widely discussed in education research, and open educational resources have become an increasingly popular way to help learners acquire knowledge. However, these resources contain massive amounts of information, making it difficult for learners to identify Web articles that refer to computer science knowledge. This study…
Descriptors: Internet, Online Searching, Information Retrieval, Artificial Intelligence
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
Fadoua Balabdaoui; Nora Dittmann-Domenichini; Henry Grosse; Claudia Schlienger; Gerd Kortemeyer – Discover Education, 2024
We report the results of a 4800-respondent survey among students at a technical university regarding their usage of artificial intelligence tools, as well as their expectations and attitudes about these tools. We find that many students have come to differentiated and thoughtful views and decisions regarding the use of artificial intelligence. The…
Descriptors: Foreign Countries, College Students, Artificial Intelligence, Student Attitudes
Gunasilan, Uma – Higher Education, Skills and Work-based Learning, 2022
Purpose: Debates are well known to encompass a variety of skills we would like higher education candidates to embody when they graduate. Design/methodology/approach: Debates in a classroom with computer science as the main subject has been popular in high schools particularly with emerging issues around the area, however it does not have as an…
Descriptors: Debate, Learning Activities, Teaching Methods, Programming
Asiye Toker Gokce; Arzu Deveci Topal; Aynur Kolburan Geçer; Canan Dilek Eren – Education and Information Technologies, 2025
Artificial intelligence (AI) literacy is critical to shaping students' academic experiences and future opportunities inhigher education. This study examines AI literacy among university students, examining variables such as gender, frequency of use of AI applications, completion of AI-related courses, and field of study. The research involved 664…
Descriptors: Artificial Intelligence, Technological Literacy, College Students, Decision Making
Noura Zeroual; Mahnane Lamia; Mohamed Hafidi – Education and Information Technologies, 2024
Traditional education systems do not provide students with much freedom to choose the right training of study that suits them, which leads on long-term to the negative effects not only on social, economic and mental' well-being of student, but also will have a negative effect on the quality of the work produced by this student in the future. In…
Descriptors: Artificial Intelligence, Technology Uses in Education, Foreign Countries, Computer Science Education
Roland Kiraly; Sandor Kiraly; Martin Palotai – Education and Information Technologies, 2024
Deep learning is a very popular topic in computer sciences courses despite the fact that it is often challenging for beginners to take their first step due to the complexity of understanding and applying Artificial Neural Networks (ANN). Thus, the need to both understand and use neural networks is appearing at an ever-increasing rate across all…
Descriptors: Artificial Intelligence, Computer Science Education, Problem Solving, College Faculty
Embracing Artificial Intelligence to Improve Self-Directed Learning: A Cybersecurity Classroom Study
Jim Marquardson – Information Systems Education Journal, 2024
Generative artificial intelligence (AI) tools were met with a mix of enthusiasm, skepticism, and fear. AI adoption soared as people discovered compelling use cases--developers wrote code, realtors generated narratives for their websites, students wrote essays, and much more. Calls for caution attempted to temper AI enthusiasm. Experts highlighted…
Descriptors: Artificial Intelligence, Capstone Experiences, Computer Security, Information Security
Tanaka, Tetsuo; Ueda, Mari – International Association for Development of the Information Society, 2023
In this study, the authors have developed a web-based programming exercise system currently implemented in classrooms. This system not only provides students with a web-based programming environment but also tracks the time spent on exercises, logging operations such as program editing, building, execution, and testing. Additionally, it records…
Descriptors: Scores, Prediction, Programming, Artificial Intelligence
Van Petegem, Charlotte; Deconinck, Louise; Mourisse, Dieter; Maertens, Rien; Strijbol, Niko; Dhoedt, Bart; De Wever, Bram; Dawyndt, Peter; Mesuere, Bart – Journal of Educational Computing Research, 2023
We present a privacy-friendly early-detection framework to identify students at risk of failing in introductory programming courses at university. The framework was validated for two different courses with annual editions taken by higher education students (N = 2 080) and was found to be highly accurate and robust against variation in course…
Descriptors: Pass Fail Grading, At Risk Students, Introductory Courses, Programming
Sunil Hazari – Journal of Educational Research and Practice, 2024
In this article, I present a justification for implementing AI literacy courses in higher education. I explore the ethical concerns and biases surrounding AI technologies, highlighting the importance of critical analysis and responsible use of AI. I then propose a conceptual framework, focusing on awareness, skill development, and the practical…
Descriptors: Artificial Intelligence, Higher Education, Critical Thinking, Innovation
User Experiences of ChatGPT among Engineering Students, Teachers, and Working Professionals in India
G. S. Prakasha; R. Sanskriti; B. Ishani – Journal of Educators Online, 2024
The introduction of Chat Generative Pre-Trained Transformer (ChatGPT) in November 2022 brought about rapid changes in the workplace and academia. Its usage ranged from student assignments to workplace targets in the engineering field. Although it has brought novel ideas to its application in various fields and task efficiency in the workplace, its…
Descriptors: Users (Information), Artificial Intelligence, Computer Software, Synchronous Communication
Chen, Huan; Li, You; Wang, Ye; Lee, Yugyung; Petri, Alexis; Cha, Teryn – Journal of Ethnographic & Qualitative Research, 2022
Artificial intelligence (AI) has been widely adopted in higher education. However, the current research on AI in higher education is limited, lacking both breadth and depth. In the present study, we addressed this research gap by exploring students' perception of learning in AI-related courses facilitated by an open experiential AI platform.…
Descriptors: Artificial Intelligence, Technology Integration, Computer Science Education, Communications