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Showing 1 to 15 of 67 results Save | Export
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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
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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
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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
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Ramon Mayor Martins; Christiane G. Von Wangenheim; Marcelo F. Rauber; Adriano F. Borgatto; Jean C. R. Hauck – ACM Transactions on Computing Education, 2024
As Machine Learning (ML) becomes increasingly integrated into our daily lives, it is essential to teach ML to young people from an early age including also students from a low socioeconomic status (SES) background. Yet, despite emerging initiatives for ML instruction in K-12, there is limited information available on the learning of students from…
Descriptors: Artificial Intelligence, Computer Science Education, Socioeconomic Status, Correlation
Zachary Opps – ProQuest LLC, 2024
As the use of artificial intelligence (AI), especially machine learning (ML), has dramatically increased, K-12 schools have begun to deliver AI education; however, little is known about teachers' views on the field. This qualitative study investigated how U.S. high school computer science (CS) teachers conceptualize AI, the role of AI in their CS…
Descriptors: Artificial Intelligence, High School Teachers, Computer Science Education, Teacher Education
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Xiaodong Huang; Chengche Qiao – Science & Education, 2024
Artificial intelligence is the unification of philosophy, cognitive science, mathematics, neurophysiology, psychology, computer science, information theory, cybernetics, and uncertainty theory. Therefore, it is feasible and necessary to utilize STEAM (Science, Technology, Engineering, Liberal Arts, and Mathematics) education to learn artificial…
Descriptors: Thinking Skills, Artificial Intelligence, STEM Education, Art Education
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Jiahong Su; Kai Guo; Xinyu Chen; Samuel Kai Wah Chu – Interactive Learning Environments, 2024
The teaching of artificial intelligence (AI) has increasingly become a topic of investigation among educational researchers. Studies of AI education have predominantly focused on the university level; less attention has been paid to teaching AI in K-12 classrooms. This study synthesised empirical studies on K-12 AI education, with the aims of…
Descriptors: Artificial Intelligence, Computer Science Education, Elementary Secondary Education, Teaching Methods
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Lin Zhang; Qiang Jiang; Weiyan Xiong; Wei Zhao – Journal of Educational Computing Research, 2025
This study seeks to deepen the understanding of the direct and indirect effects of human-computer dialogic interaction programming activities, facilitated by ChatGPT, on student engagement. Data were collected from 109 Chinese high school students who engaged in programming tasks using either ChatGPT-driven dialogic interaction or traditional pair…
Descriptors: Artificial Intelligence, Computer Software, Computer Science Education, Programming
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Christine Ladwig; Dana Schwieger; Reshmi Mitra – Information Systems Education Journal, 2025
The rapid rise of AI use is creating some very serious legal and ethical issues such as bias, discrimination, inequity, privacy violations, and--as creators everywhere fear--theft of protected intellectual property. Because AI platforms "learn" by scraping training materials available online or what is provided to them through their…
Descriptors: Copyrights, Plagiarism, Intellectual Property, Computer Software
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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
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Judith Galezer; Smadar Szekely – Informatics in Education, 2024
Spark, one of the products offered by MyQ (formerly Plethora), is a game-based platform meticulously designed to introduce students to the foundational concepts of computer science. By navigating through logical challenges, users delve into topics like abstraction, loops, and graph patterns. Setting itself apart from its counterparts, Spark boasts…
Descriptors: Learning Management Systems, Game Based Learning, Computer Science Education, Teaching Methods
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Guangrui Fan; Dandan Liu; Rui Zhang; Lihu Pan – International Journal of STEM Education, 2025
Purpose: This study investigates the impact of AI-assisted pair programming on undergraduate students' intrinsic motivation, programming anxiety, and performance, relative to both human-human pair programming and individual programming approaches. Methods: A quasi-experimental design was conducted over two academic years (2023-2024) with 234…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Programming
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David Roldan-Alvarez; Francisco J. Mesa – IEEE Transactions on Education, 2024
Artificial intelligence (AI) in programming teaching is something that still has to be explored, since in this area assessment tools that allow grading the students work are the most common ones, but there are not many tools aimed toward providing feedback to the students in the process of creating their program. In this work a small sized…
Descriptors: Intelligent Tutoring Systems, Grading, Artificial Intelligence, Feedback (Response)
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Sharin Rawhiya Jacob; Mark Warschauer – CATESOL Journal, 2024
Over the last decade, there has been an explosion of national interest in computer science (CS) education. In response to this, several organizations and initiatives have emerged in recent years to expand the CS pipeline. However, within these broad and laudable efforts, one important area has been largely overlooked--the instruction of CS to…
Descriptors: Elementary School Students, Artificial Intelligence, Computer Science Education, Technology Uses in Education
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Saadia, Drissi – International Journal of Web-Based Learning and Teaching Technologies, 2021
Cloud computing, internet of things (IoT), artificial intelligence, and big data are four very different technologies that are already discussed separately. The use of the four technologies is required to be more and more necessary in the present day in order to make them important components in today's world technology. In this paper, the authors…
Descriptors: Teaching Methods, Computer Science Education, Computer Software, Artificial Intelligence
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