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Eunsung Park; Jongpil Cheon – Journal of Educational Computing Research, 2025
Debugging is essential for identifying and rectifying errors in programming, yet time constraints and students' trivialization of errors often hinder progress. This study examines differences in debugging challenges and strategies among students with varying computational thinking (CT) competencies using weekly coding journals from an online…
Descriptors: Undergraduate Students, Programming, Computer Software, Troubleshooting
Harry Barton Essel; Dimitrios Vlachopoulos; Henry Nunoo-Mensah; John Opuni Amankwa – British Journal of Educational Technology, 2025
Conversational user interfaces (CUI), including voice interfaces, which allow users to converse with computers via voice, are gaining wide popularity. VoiceBots allow users to receive a response in real-time, regardless of the communication device. VoiceBots have been explored in fields such as customer service to automate repetitive queries and…
Descriptors: Foreign Countries, Artificial Intelligence, Program Effectiveness, Undergraduate Students
Antonio Estevan Martinez IV – Digital Experiences in Mathematics Education, 2024
Many areas of mathematics naturally lend themselves to machine-based computing environments, which suggests that computational environments may serve as useful mediating tools for the teaching and learning of mathematical content. While some mathematics classes are leveraging the use of computational tools, the implementation of computer…
Descriptors: Mathematics Education, Programming, Undergraduate Students, Competency Based Education
Heinsen Egan, Matthew; McDonald, Chris – Computer Science Education, 2021
Background and Context: Students learning the C programming language struggle to debug, and to understand the runtime behaviour of, their programs. Objective: We examine a tool that combines several novice-focused error detection, program visualization, and debugging techniques, to investigate which features students use in real study sessions,…
Descriptors: Computer Science Education, Programming Languages, Programming, Novices
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
Cheers, Hayden; Lin, Yuqing – Computer Science Education, 2023
Background and Context: Source code plagiarism is a common occurrence in undergraduate computer science education. Many source code plagiarism detection tools have been proposed to address this problem. However, such tools do not identify plagiarism, nor suggest what assignment submissions are suspicious of plagiarism. Source code plagiarism…
Descriptors: Plagiarism, Programming, Computer Science Education, Identification
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
Diana Kirk; Andrew Luxton-Reilly; Ewan Tempero – ACM Transactions on Computing Education, 2025
Objectives: Code style is an important aspect of text-based programming because programs written with good style are considered easier to understand and change and so improve the maintainability of the delivered software product. However teaching code style is complicated by the existence of many style guides and standards that contain…
Descriptors: Computer Science Education, Programming, Computer Software, Teaching Methods
Adam Diamant – INFORMS Transactions on Education, 2024
Managers are increasingly being tasked with overseeing data-driven projects that incorporate prescriptive and predictive models. Furthermore, basic knowledge of the data analytics pipeline is a fundamental requirement in many modern organizations. Given the central importance of analytics in today's business environment, there is a growing demand…
Descriptors: Business Administration Education, Graduate Students, Prediction, Mathematical Concepts
Taskeen Hasrod; Yannick B. Nuapia; Hlanganani Tutu – Journal of Chemical Education, 2024
In order to improve the accessibility and user friendliness of an accurately pretrained stacking ensemble machine learning regressor used to predict sulfate levels (mg/L) in Acid Mine Drainage (AMD), a Graphical User Interface (GUI) was developed using Python by combining human input with ChatGPT and deployed in the Jupyter Notebook environment.…
Descriptors: Artificial Intelligence, Natural Language Processing, Educational Technology, Computer Software
Cheers, Hayden; Lin, Yuqing; Yan, Weigen – Informatics in Education, 2023
Source code plagiarism is a common occurrence in undergraduate computer science education. Many source code plagiarism detection tools have been proposed to address this problem. However, most of these tools only measure the similarity between assignment submissions, and do not actually identify which are suspicious of plagiarism. This work…
Descriptors: Plagiarism, Assignments, Computer Software, Computer Science Education
Morales-Trujillo, Miguel Ehecatl; Galster, Matthias; Gilson, Fabian; Mathews, Moffat – IEEE Transactions on Education, 2022
Background: Peer evaluation in software engineering (SE) project courses enhances the learning experience of students. It also helps instructors monitor and assess both teams and individual students. Peer evaluations might influence the way individual students and teams work; therefore, the quality of the peer evaluations should be tracked through…
Descriptors: Undergraduate Students, Computer Software, Programming, Peer Evaluation
Rafael Mellado; Claudio Cubillos – Journal of Computer Assisted Learning, 2024
Background: Effective learning in computer programming courses has been a constant challenge for university teachers and has become a relevant competence for current professionals. The literature on gamification in learning presents mixed results, mainly due to problems in instructional design and inconsistency in gamification. Studies with…
Descriptors: Engineering Education, College Students, Computer Software, Technical Occupations
Niklas Humble; Jonas Boustedt; Hanna Holmgren; Goran Milutinovic; Stefan Seipel; Ann-Sofie Östberg – Electronic Journal of e-Learning, 2024
Artificial Intelligence (AI) and related technologies have a long history of being used in education for motivating learners and enhancing learning. However, there have also been critiques for a too uncritical and naïve implementation of AI in education (AIED) and the potential misuse of the technology. With the release of the virtual assistant…
Descriptors: Cheating, Artificial Intelligence, Technology Uses in Education, Computer Science Education
Chen Zhong; J. B. Kim – Journal of Information Systems Education, 2024
Data Analytics has emerged as an essential skill for business students, and several tools are available to support their learning in this area. Due to the students' lack of programming skills and the perceived complexity of R, many business analytics courses employ no-code analytical software like IBM SPSS Modeler. Nonetheless, generative…
Descriptors: Business Education, Regression (Statistics), Programming, Artificial Intelligence