Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

7-2023

Abstract

In this study, we assess the efficacy of employing the ChatGPT language model to generate solutions for coding exercises within an undergraduate Java programming course. ChatGPT, a large-scale, deep learning-driven natural language processing model, is capable of producing programming code based on textual input. Our evaluation involves analyzing ChatGPT-generated solutions for 80 diverse programming exercises and comparing them to the correct solutions. Our findings indicate that ChatGPT accurately generates Java programming solutions, which are characterized by high readability and well-structured organization. Additionally, the model can produce alternative, memory-efficient solutions. However, as a natural language processing model, ChatGPT struggles with coding exercises containing non-textual descriptions or class files, leading to invalid solutions. In conclusion, ChatGPT holds potential as a valuable tool for students seeking to overcome programming challenges and explore alternative approaches to solving coding problems. By understanding its limitations, educators can design coding exercises that minimize the potential for misuse as a cheating aid while maintaining their validity as assessment tools.

Keywords

programming, Java, object-oriented, computer science education

Discipline

Programming Languages and Compilers | Software Engineering

Research Areas

Information Systems and Management

Publication

ITiCSE 2023: Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education, Turku, Finland, July 10-12

First Page

54

Last Page

60

ISBN

9798400701382

Identifier

10.1145/3587102.3588794

Publisher

ACM

City or Country

New York

Additional URL

https://doi.org/10.1145/3587102.3588794

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