Publication Date
In 2025 | 28 |
Since 2024 | 91 |
Since 2021 (last 5 years) | 162 |
Since 2016 (last 10 years) | 188 |
Since 2006 (last 20 years) | 215 |
Descriptor
Artificial Intelligence | 257 |
Computer Science Education | 257 |
Computer Software | 69 |
Foreign Countries | 68 |
Programming | 65 |
Teaching Methods | 65 |
Technology Uses in Education | 57 |
College Students | 44 |
Student Attitudes | 43 |
Undergraduate Students | 33 |
Educational Technology | 31 |
More ▼ |
Source
Author
Barnes, Tiffany | 4 |
Chi, Min | 3 |
Abdulhadi Shoufan | 2 |
Abelson, Hal | 2 |
Cha, Teryn | 2 |
Chen, Huan | 2 |
Chu, Samuel Kai Wah | 2 |
Dai, Yun | 2 |
Ernst Bekkering | 2 |
Grignetti, Mario C. | 2 |
Hauck, Jean C. R. | 2 |
More ▼ |
Publication Type
Education Level
Audience
Teachers | 10 |
Practitioners | 8 |
Researchers | 4 |
Location
Australia | 7 |
Brazil | 6 |
China | 6 |
Turkey | 6 |
Spain | 5 |
Taiwan | 5 |
Germany | 4 |
Hong Kong | 4 |
Pennsylvania | 4 |
Washington | 4 |
California | 3 |
More ▼ |
Laws, Policies, & Programs
Assessments and Surveys
Flesch Reading Ease Formula | 1 |
Massachusetts Comprehensive… | 1 |
What Works Clearinghouse Rating
Jinshui Wang; Shuguang Chen; Zhengyi Tang; Pengchen Lin; Yupeng Wang – Education and Information Technologies, 2025
Mastering SQL programming skills is fundamental in computer science education, and Online Judging Systems (OJS) play a critical role in automatically assessing SQL codes, improving the accuracy and efficiency of evaluations. However, these systems are vulnerable to manipulation by students who can submit "cheating codes" that pass the…
Descriptors: Programming, Computer Science Education, Cheating, Computer Assisted Testing
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
Ishaya Gambo; Faith-Jane Abegunde; Omobola Gambo; Roseline Oluwaseun Ogundokun; Akinbowale Natheniel Babatunde; Cheng-Chi Lee – Education and Information Technologies, 2025
The current educational system relies heavily on manual grading, posing challenges such as delayed feedback and grading inaccuracies. Automated grading tools (AGTs) offer solutions but come with limitations. To address this, "GRAD-AI" is introduced, an advanced AGT that combines automation with teacher involvement for precise grading,…
Descriptors: Automation, Grading, Artificial Intelligence, Computer Assisted Testing
Nicolas Pope; Juho Kahila; Henriikka Vartiainen; Matti Tedre – IEEE Transactions on Learning Technologies, 2025
The rapid advancement of artificial intelligence and its increasing societal impacts have turned many computing educators' focus toward early education in machine learning (ML). Limited options for educational tools for teaching novice learners about the mechanisms of ML and data-driven systems presents a recognized challenge in K-12 computing…
Descriptors: Artificial Intelligence, Computer Oriented Programs, Computer Science Education, Grade 4
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
Han Wan; Hongzhen Luo; Mengying Li; Xiaoyan Luo – IEEE Transactions on Learning Technologies, 2024
Automatic program repair (APR) tools are valuable for students to assist them with debugging tasks since program repair captures the code modification to make a buggy program pass the given test-suite. However, the process of manually generating catalogs of code modifications is intricate and time-consuming. This article proposes contextual error…
Descriptors: Programming, Computer Science Education, Introductory Courses, Assignments
Rui Wang; Haili Ling; Jie Chen; Huijuan Fu – International Journal of Distance Education Technologies, 2025
This study adopted the Latent Dirichlet Allocation (LDA) to extract learners' needs based on 70,145 reviews from online course designed for software design and development in China and then applied Quality Function Deployment (QFD) to map learners' differentiated needs into quality attributes. Taking national first-class courses as the…
Descriptors: Educational Improvement, Student Needs, Computer Science Education, Foreign Countries
Dai, Yun; Liu, Ang; Qin, Jianjun; Guo, Yanmei; Jong, Morris Siu-Yung; Chai, Ching-Sing; Lin, Ziyan – Journal of Engineering Education, 2023
Background: The recent discussion of introducing artificial intelligence (AI) knowledge to K-12 students, like many engineering and technology education topics, has attracted a wide range of stakeholders and resources for school curriculum development. While teachers often have to directly interact with external stakeholders out of the public…
Descriptors: Artificial Intelligence, Technology Education, Curriculum Development, Computer Science Education
David M. Woods; Andrea Hulshult – Information Systems Education Journal, 2025
IT/IS educators continue to work to develop content and activities for teaching Agile practices, processes, and methodologies to their courses to ensure students have the skills expected by businesses. Given the wide range of tools and technologies that fall under the umbrella of Agile and the wide range of places where Agile is applied, educators…
Descriptors: Information Technology, Information Science Education, Computer Science Education, Teaching Methods
Madhav Sharma; Roger McHaney – Decision Sciences Journal of Innovative Education, 2025
Many management information systems (MIS) faculty have adopted a project-oriented approach in their systems analysis and design courses. In these courses, students use a software development methodology to create a web or mobile application project, which can be based on a predefined case or developed for an external stakeholder. Because most…
Descriptors: Computer Software, Artificial Intelligence, Instructional Design, Computer Science Education
Xiaojing Duan; Bo Pei; G. Alex Ambrose; Arnon Hershkovitz; Ying Cheng; Chaoli Wang – Education and Information Technologies, 2024
Providing educators with understandable, actionable, and trustworthy insights drawn from large-scope heterogeneous learning data is of paramount importance in achieving the full potential of artificial intelligence (AI) in educational settings. Explainable AI (XAI)--contrary to the traditional "black-box" approach--helps fulfilling this…
Descriptors: Academic Achievement, Artificial Intelligence, Prediction, Models
Randy Connolly – ACM Transactions on Computing Education, 2024
The belief that AI technology is on the cusp of causing a generalized social crisis became a popular one in 2023. While there was no doubt an element of hype and exaggeration to some of these accounts, they do reflect the fact that there are troubling ramifications to this technology stack. This conjunction of shared concerns about social,…
Descriptors: Artificial Intelligence, Computers, Technology Uses in Education, Public Opinion
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
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
Lukas Höper; Carsten Schulte – Informatics in Education, 2024
In K-12 computing education, there is a need to identify and teach concepts that are relevant to understanding machine learning technologies. Studies of teaching approaches often evaluate whether students have learned the concepts. However, scant research has examined whether such concepts support understanding digital artefacts from everyday life…
Descriptors: Student Empowerment, Data Use, Computer Science Education, Artificial Intelligence