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

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 prob...

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Vydané v:Electronics (Basel) Ročník 14; číslo 11; s. 2261
Hlavní autori: Zhu, Zihao, Funabiki, Nobuo, Mentari, Mustika, Aung, Soe Thandar, Kao, Wen-Chung, Lee, Yi-Fang
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Basel MDPI AG 31.05.2025
Predmet:
Applications programs
Artificial intelligence
Chatbots
Computational linguistics
Computer science
Curricula
Design
Education
Embedded systems
Gamification
Generative artificial intelligence
Java
Language processing
Learning
Learning disabilities
Methods
Motivation
Natural language interfaces
Object oriented programming
Object-oriented languages
Personalized learning
Problem solving
Programming languages
Prompt engineering
Sciences education
Source code
Student participation
Syntax
Teachers
Teaching methods
Trends
Visualization
ISSN:2079-9292, 2079-9292
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Shrnutí: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.
Bibliografia:ObjectType-Article-1
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content type line 14
ISSN:2079-9292
2079-9292
DOI:10.3390/electronics14112261