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Lauren E. Margulieux; Yin-Chan Liao; Erin Anderson; Miranda C. Parker; Brendan D. Calandra – ACM Transactions on Computing Education, 2024
Integrated computing curricula combine learning objectives in computing with those in another discipline, like literacy, math, or science, to give all students experience with computing, typically before they must decide whether to take standalone CS courses. One goal of integrated computing curricula is to provide an accessible path to an…
Descriptors: Technology Uses in Education, Technology Integration, Computer Uses in Education, Computer Science
Marcus Messer; Neil C. C. Brown; Michael Kölling; Miaojing Shi – ACM Transactions on Computing Education, 2024
We conducted a systematic literature review on automated grading and feedback tools for programming education. We analysed 121 research papers from 2017 to 2021 inclusive and categorised them based on skills assessed, approach, language paradigm, degree of automation, and evaluation techniques. Most papers assess the correctness of assignments in…
Descriptors: Automation, Grading, Feedback (Response), Programming
Pavlos Toukiloglou; Stelios Xinogalos – Education and Information Technologies, 2024
Hour of Code is a widely recognized global event that aims to introduce programming to novice users and integrate computer science into education. This paper presents an analysis of the effectiveness of the support system and user interface of Minecraft Adventurer, a serious game designed for the Hour of Code global event. Although previous…
Descriptors: Novices, Programming, Coding, Computer Science Education
Ailsa Zayyan Salsabila; R. Yugo Kartono Isal; Harry B. Santoso – Journal of Educators Online, 2025
This study aims to provide recommendations for interaction design to enhance students' task interpretation, as one of the crucial aspects of Self-Regulated Learning (SRL) in online learning environments. Utilizing the Engineering Design Metacognitive Questionnaire (EDMQ), open-ended questions, and in-depth interviews, this study examines the…
Descriptors: Learning Processes, Electronic Learning, College Students, 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
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
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
A Comparison of Generative AI Solutions and Textbook Solutions in an Introductory Programming Course
Ernst Bekkering; Patrick Harrington – Information Systems Education Journal, 2025
Generative AI has recently gained the ability to generate computer code. This development is bound to affect how computer programming is taught in higher education. We used past programming assignments and solutions for textbook exercises in our introductory programming class to analyze how accurately one of the leading models, ChatGPT, generates…
Descriptors: Higher Education, Artificial Intelligence, Programming, Textbook Evaluation
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
Jiangyue Liu; Siran Li – Journal of Educational Computing Research, 2024
Pair Programming is considered an effective approach to programming education, but the synchronous collaboration of two programmers involves complex coordination, making this method difficult to be widely adopted in educational settings. Artificial Intelligence (AI) code-generation tools have outstanding capabilities in program generation and…
Descriptors: Artificial Intelligence, Programming, Technology Uses in Education, Coding
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
Leveraging Large Language Models to Generate Course-Specific Semantically Annotated Learning Objects
Dominic Lohr; Marc Berges; Abhishek Chugh; Michael Kohlhase; Dennis Müller – Journal of Computer Assisted Learning, 2025
Background: Over the past few decades, the process and methodology of automatic question generation (AQG) have undergone significant transformations. Recent progress in generative natural language models has opened up new potential in the generation of educational content. Objectives: This paper explores the potential of large language models…
Descriptors: Resource Units, Semantics, Automation, Questioning Techniques
Chiao Ling Huang; Lianzi Fu; Shih-Chieh Hung; Shu Ching Yang – Journal of Computer Assisted Learning, 2025
Background: Many studies have highlighted the positive effects of visual programming instruction (VPI) on students' learning experiences, programming self-efficacy and flow experience. However, there is a notable gap in the research on how these factors specifically impact programming achievement and learning intentions. Our study addresses this…
Descriptors: Attention, Self Efficacy, Visual Aids, Instructional Effectiveness
Sarah Emily Wilson; Joseph B. Wiggins; Lauren N. Wong; Tracy Gault Ulrich; Bill Causey; Jorge Parra; Nicholas A. Gage; Jose Blackorby – Journal of Special Education Technology, 2025
Over the past few decades, advances in computing power and the widespread adoption of the Internet have completely transformed the ways that people obtain information, communicate, educate, and conduct business. Unfortunately, access to technology and to the training required to use technology are not equitably distributed in the United States,…
Descriptors: Students with Disabilities, Educational Technology, Technology Uses in Education, Intervention