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programming education with ChatGPT: outcomes for beginners and intermediate students

education AND INFORMATION TECHNOLOGIES 2025年 1-26页

作者： Suh, Jihae Lee, Kyuhan Lee, Jaehwan Seoul Natl Univ Sci & Technol Dept Business Adm Mugeun Hall 512232Gongneung Ro Seoul 01811 South Korea Korea Univ Business Sch 145 Anam Ro Seoul 02841 South Korea Chungnam Natl Univ Sch Business 99 Daehak Ro Daejeon 34134 South Korea

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 of use in asking and answering questions using natural language. This study investigates the effectiveness of ChatGPT in assisting the learning process of university students enrolled in Python programming courses. The primary question addressed is how differently the use of ChatGPT affects two groups at different levels of programming proficiency-beginners and intermediate. The study compares the impact of ChatGPT on academic performance between these two groups. The results show that for beginners, ChatGPT did not significantly contribute to improved learning outcomes. In addition, a survey was conducted to explore students'perceptions of the benefits and challenges of using ChatGPT, which revealed differences in responses between the two groups of learners. This research provides valuable insights into the potential applications of AI tools in educational settings, particularly in the context of programming education.

关键词： Generative AI education Tool ChatGPT programming education Prior Knowledge Activation Proficiency level

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A Bibliometric Exposition and Review on Leveraging LLMs for programming education

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IEEE ACCESS 2025年 13卷 58364-58393页

作者： Amos, Joanah Pwanedo Amodu, Oluwatosin Ahmed Mahmood, Raja Azlina Raja Abdulqudus, Akanbi Bolakale Zakaria, Anies Faziehan Iyanda, Abimbola Rhoda Bukar, Umar Ali Mohd Hanapi, Zurina Elizade Univ Informat & Commun Engn Dept Ilara Mokin 340271 Nigeria Univ Putra Malaysia Dept Commun Technol & Network Serdang 43400 Selangor Malaysia Elizade Univ Dept Math & Comp Sci Ilara Mokin 340271 Nigeria Univ Kebangsaan Malaysia Fac Engn & Built Environm Dept Engn Educ Bangi 43600 Malaysia Obafemi Awolowo Univ Comp Sci & Engn Dept Ife 220005 Nigeria Taraba State Univ Fac Comp & Artificial Intelligence Dept Comp Sci Jalingo 660213 Nigeria Multimedia Univ Fac Informat Sci & Technol Ctr Intelligent Cloud Comp CICC Melaka 75450 Malaysia

The world is experiencing an AI revolution, with large language models (LLMs) transforming various industries, including education. Academics are striving to harness the potential of LLMs while also contending with their risks. This paper presents the first bibliometric analysis focused on LLM research in programming education, identifying leading countries, authors, and institutions while analyzing key terms and popular keywords in this field. Additionally, it highlights influential studies on topics such as introductory programming, computer science, computing, programming education, and prompt engineering, discussing key insights from these works. Findings indicate that LLMs could play a significant role in programming education and may be integrated into computer science curricula. However, careful consideration is needed to ensure their benefits outweigh their risks across various use cases. This study specifically examines ChatGPT as a representative LLM, exploring its benefits and limitations as both a learning aid for students and a support tool for professionals. It also evaluates the quality of ChatGPT-generated code and its effectiveness in simplifying programming concepts for beginners. Furthermore, the ethical implications of increasing reliance on LLMs for programming tasks, including concerns about dependency, plagiarism, and potential effects on critical thinking, are addressed. By contributing to the ongoing discourse on integrating AI tools like ChatGPT in programming education, this research emphasizes the importance of responsible and ethical usage to maximize benefits for students, educators, and the broader educational community.

关键词： Chatbots programming profession education Bibliometrics Market research Large language models Codes Ethics Requirements engineering Mathematics ChatGPT code generation ethical concerns large language models (LLMs) introductory programming programming education prompt engineering

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Automated Code Assessment and Feedback: A Comprehensive Model for Improved programming education

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IEEE ACCESS 2025年 13卷 56642-56658页

作者： Parvathy, R. Thushara, M. G. Kannimoola, Jinesh M. Amrita Vishwa Vidyapeetham Amrita Sch Comp Dept Comp Sci & Engn Amritapuri 690525 Kerala India Amrita Vishwa Vidyapeetham Amrita Sch Comp Dept Comp Sci & Applicat Amritapuri 690525 Kerala India

programming skills are essential in nearly every job today. To prepare students for the growing demand for programming expertise, they must be proficient in coding. This poses a challenge for educators who must ensure students are well-equipped to meet these demands. In Today's time, most of the schools and universities have introduced advanced curricula and syllabi with programming courses, thus an effective and conventional model to evaluate the codes submitted by students in a timely manner is very much required. Traditional grading systems were often slow, biased, and lacked the ability to provide meaningful feedback, which is crucial for student improvement. This study proposes an extensive automated code assessment and feedback model that addresses these issues and provides timely feedback to students. The model evaluates different aspects of the codes like originality, accuracy, structure, and syntax. By using the Abstract Syntax Tree (AST) analysis for code structure, plagiarism detection, and syntax error identification, the model offers an improved approach to evaluating student's coding skills. To evaluate the model, a group of 60 engineering students participated, and the model demonstrated a 40% increase in grading efficiency, reducing grading time while maintaining quality. The feedback on scores provided students with valuable insights about their understanding of programming concepts. This model not only supports skill development through actionable feedback but also promotes larger educational goals of accessibility and inclusivity by offering a sustainable solution for quality learning.

关键词： Codes programming profession Syntactics Encoding education Accuracy Semantics Plagiarism Testing Sustainable development Automated assessment code evaluation plagiarism detection programming education student feedback sustainable education

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Code-Review-as-an-educational-Service: A tool for Java code review in programming education

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SOFTWAREX 2025年 29卷

作者： Beattie, Matthew Watson, Moira Greer, Desmond Toh, Bee-Yen Li, Zheng Queens Univ Belfast Sch Elect Elect Engn & Comp Sci Belfast BT9 5AF North Ireland

High-quality source code is the foundation of successful and sustainable software development, while code review plays a crucial role in ensuring code quality. We place a special emphasis on the educational application of code review, aiming to assist novice students who are entry-level programmers establish industry-standard programming practices while reducing the likelihood of vulnerabilities and technical debt. Given that existing code review tools often require complex setups and are designed for large-scale, enterprise-level software projects, we advocate for the development of an easy-to-use, zero-configuration, and lightweight tool that is specifically tailored to the needs of educational environments. This paper reports our development of such a cloud-native code review tool as an educational service. Although still at the proof-of-concept stage, our internal and preliminary assessment has confirmed the promising usability and usefulness of this tool both for students (e.g., self-reviewing an individual exercise) and for educators (e.g., examining cohort exercises and prioritising teaching materials). By integrating this tool into our innovative project Automating programming education in Java, we believe that such an educational service would be able to make contributions to faster maturation of programming skills in students.

关键词： Cloud-native architecture Code quality Code review programming education Software as a service Tooling support

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A Knowledge-Driven Approach to AI-Based Personalized Test Paper Creation in programming education

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INTERNATIONAL JOURNAL OF KNOWLEDGE MANAGEMENT 2025年第1期21卷

作者： Wu, Zhiqiang Wan, Shuhui Henan Police Coll Dept Network Secur Zhengzhou Peoples R China

Computer programming education plays an important role in modern society, however, students' knowledge base, learning style, and ability level vary widely. Personalized teaching has become a key issue in education reform. As the existing question bank system mainly labels the difficulty coefficient of the questions by manual means, and cannot objectively and accurately provide personalized learning paths for different students. This paper puts forward two parameters of "students' ability value" and "difficulty value of test question", constructs the corresponding relationship table between students' ability value and difficulty value of test question, establishes the mathematical model, and generates the test paper that meets students' learning ability. Compared with other algorithms, the algorithm designed in this paper has a faster convergence speed and the success rate of paper generation. Through practical application and questionnaires, it is evident that the personalized question bank designed in this paper can effectively help students better grasp programming knowledge.

关键词： Adaptive Learning Question Bank Compose Test Paper Genetic Algorithm programming education

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Enhancing SQL programming education: addressing cheating challenges in online judge systems

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education AND INFORMATION TECHNOLOGIES 2025年第1期30卷 715-745页

作者： Wang, Jinshui Chen, Shuguang Tang, Zhengyi Lin, Pengchen Wang, Yupeng Fujian Univ Technol Sch Comp Sci & Math Fuzhou 350118 Peoples R China Fujian Univ Technol Fujian Prov Key Lab Big Data Min & Applicat Fuzhou 350118 Peoples R China

Mastering SQL programming skills is fundamental in computer science education, and Online Judging Systems (OJS) play a critical role in automatically assessing SQL codes, improving the accuracy and efficiency of evaluations. However, these systems are vulnerable to manipulation by students who can submit "cheating codes" that pass the tests without genuinely solving programming problems or demonstrating authentic SQL skills. This study analyzed over 5.8 million SQL codes validated by OJS and identified four types of cheating codes: Explicit Result Output, Quantitative Output Manipulation, Data-Observed Clause Manipulation, and DML-Driven Test Case Distortion. The initial experiment treated SQL codes as plain text using the Bag of Words vector model and processed them with six machine learning models to detect cheating. The results showed an average recall of 74.73% and precision of 97.10%, confirming the efficacy of automated detection. In the subsequent experiments, the first of these used 12 syntactic and semantic features of SQL codes, achieving a recall rate of 59.55% and precision of 87.26%. The final experiment added two more characteristic features of cheating codes to these models, significantly improving recall to 89.35% and precision to 95.25%. This highlights the importance of characteristic cheating features in identifying cheating codes. The study's findings deepen our understanding of cheating codes and contribute to enhancing online programming education and assessment quality.

关键词： Online judge systems Cheating codes Machine learning Automated detection programming education

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A comparative study of student perceptions on generative AI in programming education across Sub-Saharan Africa

COMPUTERS AND EDUCATION OPEN

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COMPUTERS AND education OPEN 2025年 8卷

作者： Oyelere, Solomon Sunday Aruleba, Kehinde Lulea Univ Technol Dept Comp Sci Elect & Space Engn Skelleftea Sweden Univ Exeter Dept Comp Sci Exeter EX4 4PY England Univ Johannesburg Johannesburg Business Sch JBS Res Grp Data Artificial Intelligence & Innovat Dig Johannesburg South Africa Univ Leicester Sch Comp & Math Sci Leicester LE1 7RH England

In today's era of technological evolution, programming education is crucial for shaping the future workforce and fostering innovation. However, access to quality computer science education remains a significant challenge with Sub-Saharan Africa nations experiencing a pronounced digital divide. Despite growing interest in technology, these countries struggle with unequal access to educational resources. AI-driven tools like ChatGPT, Codey, and GitHub Copilot offer personalized learning experiences that could democratize access to knowledge and reshape programming education. This quantitative study examines the impact of these AI tools on fostering inclusive education in Kenya, Nigeria, and South Africa. It involves 322 university students, using purposive sampling and online questionnaires. Various quantitative analyzes, including descriptive statistics, country-wise comparisons, one-way ANOVA, Kruskal-Wallis tests, and correlation analysis, were conducted. The study reveals students' motivations for programming, their attitudes towards AI-driven educational tools, and the perceived impact on equity, diversity, and inclusion. Significant variations were found in attitudes based on educational level and country of residence, highlighting the need for tailored strategies to enhance the inclusivity and effectiveness of AI-driven programming education tools.

关键词： Generative AI programming education Equity Diversity Inclusion Sub-Saharan Africa

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programming education and learner motivation in the age of generative AI: student and educator perspectives

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INFORMATION AND LEARNING SCIENCES 2024年第1/2期126卷 91-109页

作者： Boguslawski, Samuel Deer, Rowan Dawson, Mark G. CODE Univ Appl Sci Berlin Germany

Purposeprogramming education is being rapidly transformed by generative AI tools and educators must determine how best to support students in this context. This study aims to explore the experiences of programming educators and students to inform future education ***/methodology/approachTwelve students and six members of faculty in a small technology-focused university were interviewed. Thematic analysis of the interview data was combined with data collected from a survey of 44 students at the same university. Self-determination theory was applied as an analytical *** themes were identified - bespoke learning, affect and support - that significantly impact motivation and learning outcomes in programming education. It was also found that students are already making extensive use of large language models (LLMs). LLMs can significantly improve learner autonomy and sense of competence by improving the options for bespoke learning;fostering emotions that are conducive to engendering and maintaining motivation;and inhibiting the negative affective states that discourage learning. However, current LLMs cannot adequately provide or replace social support, which is still a key factor in learner *** limitations/implicationsIntegrating the use of LLMs into curricula can improve learning motivation and outcomes. It can also free educators from certain tasks, leaving them with more time and capacity to focus their attention on developing social learning opportunities to further enhance learner ***/valueTo the best of the authors' knowledge, this is the first attempt to explore the relationship between motivation and LLM use in programming education.

关键词： programming education Large language models LLMs Generative AI ChatGPT Copilot Introductory programming Learning science Self-determination theory Motivation

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programming education for Primary Schoolchildren Using a Textual programming Language 45

Programming Education for Primary Schoolchildren Using a Tex...

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45th Annual Frontiers in education Conference (FIE)

作者： Tsukamoto, Hidekuni Takemura, Yasuhiro Nagumo, Hideo Ikeda, Isamu Monden, Akito Matsumoto, Ken-ichi Osaka Univ Arts Dept Character Creat Arts Osaka Japan Niigata Seiryo Univ Dept Social Welf & Psychol Niigata Japan Inst Informat Educ Support Kitakyushu Fukuoka Japan Okayama Univ Grad Sch Nat Sci & Technol Okayama Japan Nara Inst Sci & Technol Grad Sch Informat Sci Nara 6300101 Japan

ISBN: (纸本)9781479984541

In this research, a Textual programming Language (TPL) is used in programming education for primary schoolchildren because of the following reasons: (1) it is more practical to use the programming languages similar to the ones used for developing real applications, (2) typing statements could be easier for primary schoolchildren than generally thought, (3) there exist programming environments such as Processing that are easy to use and produce very attractive graphical outcomes. Teaching material for programming education with Processing was developed. In this teaching material, cartoons were used to explain difficult concepts. The learners who use this teaching material were supposed to draw some computational figures with chosen colors. Trial experiments of programming education using this teaching material was conducted to a cohort of seven primary schoolchildren (six 4th grade and one 5th grade children) in two consecutive weekend classes (one hour each). Since the authors' aim of this programming education was to create a sense of fun and excitement in the children and inculcate a desire to engage with computing, the motivation of the children was assessed using the questionnaire based on the ARCS (Attention, Relevance, Confidence, and Satisfaction) motivation model. The results were encouraging and suggested that TPLs could be used in programming education for primary schoolchildren.

关键词： programming education primary school textual programming language Processing

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programming education in the frameworks of reverse engineering and theory of didactical situations

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education AND INFORMATION TECHNOLOGIES 2022年第5期27卷 6513-6532页

作者： Abdusselam, Mustafa Serkan Turan-Guntepe, Ebru Durukan, Ummu Gulsum Giresun Univ Dept Comp Educ & Instruct Technol Giresun Turkey Giresun Univ Dept Math & Sci Educ Giresun Turkey

This study aims to evaluate the teaching of the programming process carried out through scenarios related to daily life within the framework of Reverse Engineering and the Theory of Didactical Situations. The sample of the study consists of 15 prospective computer and instructional technology education teachers. Quantitative and qualitative data were collected simultaneously and analysed independently in this study, which was designed according to an embedded mixed method. In the study, the prospective teachers' perceptions of self-efficacy, holistic and analytical thinking skills in problem-solving, academic achievements, and data collected for reverse engineering processes were evaluated in accordance with the effectiveness of programming education. After applications based on Reverse Engineering and the Theory of Didactical Situations, it was determined that the prospective teachers' perceptions of self-efficacy towards programming and their academic achievement increased, and that their analytical and holistic thinking skills when solving problems were also positively affected.

关键词： programming education Reverse engineering Theory of didactical situations Self-efficacy Thinking skills

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