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Muhammad Fawad Akbar Khan; Max Ramsdell; Erik Falor; Hamid Karimi – International Educational Data Mining Society, 2024
This paper undertakes a thorough evaluation of ChatGPT's code generation capabilities, contrasting them with those of human programmers from both educational and software engineering standpoints. The emphasis is placed on elucidating its importance in these intertwined domains. To facilitate a robust analysis, we curated a novel dataset comprising…
Descriptors: Artificial Intelligence, Automation, Computer Science Education, Programming
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
Marwan, Samiha; Price, Thomas W. – IEEE Transactions on Learning Technologies, 2023
Novice programmers often struggle on assignments, and timely help, such as a hint on what to do next, can help students continue to progress and learn, rather than giving up. However, in large programming classrooms, it is hard for instructors to provide such real-time support for every student. Researchers have, therefore, put tremendous effort…
Descriptors: Data Use, Cues, Programming, Computer Science Education
Peer reviewedPriti Oli; Rabin Banjade; Jeevan Chapagain; Vasile Rus – Grantee Submission, 2023
This paper systematically explores how Large Language Models (LLMs) generate explanations of code examples of the type used in intro-to-programming courses. As we show, the nature of code explanations generated by LLMs varies considerably based on the wording of the prompt, the target code examples being explained, the programming language, the…
Descriptors: Computational Linguistics, Programming, Computer Science Education, Programming Languages
Yuan-Chen Liu; Tzu-Hua Huang; Chien-Chia Huang – Interactive Learning Environments, 2024
In this study, an interactive programming learning environment was built with two types of error prompt functions: 1) the key prompt and 2) step-by-step prompt. A quasi-experimental study was conducted for five weeks, in which 75 sixth grade students from disadvantaged learning environments in Taipei, Taiwan, were divided into three groups: 1) the…
Descriptors: Programming, Computer Science Education, Cues, Grade 6
Grace Leah Akinyi; Robert Oboko; Lawrence Muchemi – Electronic Journal of e-Learning, 2024
The future of university learning in Sub-Saharan Africa has become increasingly digitally transformed by both e-Learning, and learning analytics, post-COVID-19 pandemic. Learning analytics intervention is critical for effective support of socially-shared regulated learning skills, which are crucial for twenty-first-century e-Learners.…
Descriptors: Electronic Learning, Student Attitudes, Learning Analytics, Feedback (Response)
Arun-Balajiee Lekshmi-Narayanan; Priti Oli; Jeevan Chapagain; Mohammad Hassany; Rabin Banjade; Vasile Rus – Grantee Submission, 2024
Worked examples, which present an explained code for solving typical programming problems are among the most popular types of learning content in programming classes. Most approaches and tools for presenting these examples to students are based on line-by-line explanations of the example code. However, instructors rarely have time to provide…
Descriptors: Coding, Computer Science Education, Computational Linguistics, Artificial Intelligence
Xiaoni Zhang – Journal of Information Systems Education, 2025
This teaching tip explores the integration of AI tools into database education. The author describes how instructors can use AI tools to prepare teaching materials and how students can use AI to facilitate database development. The teaching tips provided encompass both course-level objectives and assignment-specific strategies. The inclusion of AI…
Descriptors: Databases, Technology Integration, Critical Thinking, Thinking Skills
Fernando J. Rodriguez – ProQuest LLC, 2021
In computer science education, introductory computer programming courses tend to be the most challenging for novices, with higher dropout rates than other computer science courses. Recruitment and retention of students in computer science fields is an important area of focus in computer science education research, and previous research has…
Descriptors: Computer Science Education, Introductory Courses, Programming, Cooperative Learning
Hui Zhang; Yi Zhang; Tao Xu; Yun Zhou – Educational Technology Research and Development, 2024
Virtual Reality (VR) is increasingly recognized as a promising tool to enhance learning, yet research on the use of VR instructional approaches for online learning remains limited. The present study aims to address this research gap by examining the effects of VR instructional approaches and textual cues on learning. We conducted an educational VR…
Descriptors: Teaching Methods, Cognitive Ability, Computer Simulation, Cues
Ghadeer Sawalha; Imran Taj; Abdulhadi Shoufan – Cogent Education, 2024
Large language models present new opportunities for teaching and learning. The response accuracy of these models, however, is believed to depend on the prompt quality which can be a challenge for students. In this study, we aimed to explore how undergraduate students use ChatGPT for problem-solving, what prompting strategies they develop, the link…
Descriptors: Cues, Artificial Intelligence, Natural Language Processing, Technology Uses in Education
Ragazou, Vasiliki; Karasavvidis, Ilias – Interactive Technology and Smart Education, 2023
Purpose: Software training is a new trend in software applications. A key problem with software training is that video tutorials are developed without considering the target audience. Although video tutorials are popular, little attention is given to their design features. This study aims to investigate how two multimedia research principles,…
Descriptors: Visual Aids, Cues, Task Analysis, Video Technology
Haldeman, Georgiana; Babes-Vroman Monica; Tjang, Andrew; Nguyen, Thu D. – ACM Transactions on Computing Education, 2021
Autograding systems are being increasingly deployed to meet the challenges of teaching programming at scale. Studies show that formative feedback can greatly help novices learn programming. This work extends an autograder, enabling it to provide formative feedback on programming assignment submissions. Our methodology starts with the design of a…
Descriptors: Student Evaluation, Feedback (Response), Grading, Automation
Ragazou, Vasiliki; Karasavvidis, Ilias – International Association for Development of the Information Society, 2021
Video tutorials substantially support demonstration-based training where the main goal is to enhance procedural knowledge by observing various understandable examples of performing a task. Although video tutorials are broadly popular nowadays, little attention is given to the design features of an instructional tutorial. The aim of this study is…
Descriptors: Instructional Design, Video Technology, Educational Technology, Cues
Martha Partridge; Yen-En Kuo; Nattanan Hamapongnitinan; Liming Chen; Haoyuan Huang – International Journal for Students as Partners, 2024
Students as Partners (SaP) approaches have gained more and more traction in higher education in recent years (Dai & Matthews, 2022). Rooted in values such as reciprocity and shared responsibility, SaP can offer opportunities for internationalizing the curriculum and departing from traditional teacher-student hierarchies (Green & Baxter,…
Descriptors: Artificial Intelligence, Digital Literacy, Higher Education, Teacher Student Relationship
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