NotesFAQContact Us
Collection
Advanced
Search Tips
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing 1 to 15 of 354 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Neil C. C. Brown; Pierre Weill-Tessier; Juho Leinonen; Paul Denny; Michael Kölling – ACM Transactions on Computing Education, 2025
Motivation: Students learning to program often reach states where they are stuck and can make no forward progress--but this may be outside the classroom where no instructor is available to help. In this situation, an automatically generated next-step hint can help them make forward progress and support their learning. It is important to know what…
Descriptors: Artificial Intelligence, Programming, Novices, Technology Uses in Education
Diana Franklin; Paul Denny; David A. Gonzalez-Maldonado; Minh Tran – Cambridge University Press & Assessment, 2025
Generative AI is a disruptive technology that has the potential to transform many aspects of how computer science is taught. Like previous innovations such as high-level programming languages and block-based programming languages, generative AI lowers the technical expertise necessary to create working programs, bringing the power of computation…
Descriptors: Artificial Intelligence, Technology Uses in Education, Computer Science Education, Expertise
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
PDF on ERIC Download full text
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
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Hüseyin Gokal; Cem Ufuk Baytar – Turkish Online Journal of Educational Technology - TOJET, 2025
This study aims to examine university students' intentions to use artificial intelligence (AI) applications in their educational processes within the context of job characteristics (JC), technology characteristics (TC), task-technology fit (TTF), and self-efficacy (SE). The research was conducted with 965 students enrolled in Information…
Descriptors: College Students, Intention, Technology Uses in Education, Artificial Intelligence
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
PDF on ERIC Download full text
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Jihae Suh; Kyuhan Lee; Jaehwan Lee – Education and Information Technologies, 2025
Artificial Intelligence (AI) has rapidly emerged as a powerful tool with the potential to enhance learning environments. However, effective use of new technologies in education requires a good understanding of the technology and good design for its use. Generative AI such as ChatGPT requires particularly well-designed instructions due to its ease…
Descriptors: Programming, Computer Science Education, Artificial Intelligence, Technology Uses in Education
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Senad Orhani; Kyvete Shatri – Educational Process: International Journal, 2025
Background/purpose: In the modernized society with advanced technology, as education becomes increasingly dependent on information technology, there is a need to prepare the next generation of students with a wide variety of skills and abilities necessary for future scientific careers. Modern educational challenges include the task of engaging…
Descriptors: Computer Games, Technology Uses in Education, Game Based Learning, Student Motivation
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Previous Page | Next Page »
Pages: 1  |  2  |  3  |  4  |  5  |  6  |  7  |  8  |  9  |  10  |  11  |  ...  |  24