An Automatic Code Generation Tool Using Generative Artificial Intelligence for Element Fill-in-the-Blank Problems in a Java Programming Learning Assistant System

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Detalles Bibliográficos
Publicado en:Electronics vol. 14, no. 11 (2025), p. 2261
Autor principal: Zhu Zihao
Otros Autores: Funabiki Nobuo, Mustika, Mentari, Aung Soe Thandar, Wen-Chung, Kao, Yi-Fang, Lee
Publicado:
MDPI AG
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Acceso en línea:Citation/Abstract
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Resumen:Presently, Java is a fundamental object-oriented programming language that can be mastered by any student in information technology or computer science. To assist both teachers and students, we developed the Java Programming Learning Assistant System (JPLAS). It offers several types of practice problems with different levels and learning goals for step-by-step self-study, where any answer is automatically marked in the system. One challenge for teachers that is addressed with JPLAS is the generation of proper exercise problems that meet learning requirements. We implemented programs for generating new problems from given source codes, as collecting and evaluating suitable codes remains time-consuming. In this paper, we present an automatic code generation tool using generative AI to solve this challenge. Prompt engineering is used to help generate an appropriate source code, and the quality is controlled by optimizing the prompt based on the outputs. For applications in JPLAS, we implement a web application system to automatically generate an element fill-in-the-blank problem (EFP) in JPLAS. For evaluation, we select the element fill-in-the-blank problem (EFP) as the target type in JPLAS and generate several instances using this tool. The results confirm the validity and effectiveness of the proposed method.
ISSN:2079-9292
DOI:10.3390/electronics14112261
Fuente:Advanced Technologies & Aerospace Database