CHATGPT-ASSISTED EDUCATIONAL GAME DEVELOPMENT: A PROMPT ENGINEERING TECHNIQUE FOR TEACHERS WITHOUT CODING EXPERIENCE
Extensive research in AI has raised various questions, including how AI transformers can advance teaching and learning practice. Typically, ChatGPT is employed for tasks like content creation, research assistance, and language learning, including coding in computer languages. The main objective of this study was to examine the possibilities of teachers designing and developing teaching material based on educational games, assuming they lack coding competencies. This study presents the development and implementation of an easy educational card game known as the Memory Game (also called Matching Pairs or Concentration) using HTML5, CSS3, and JavaScript. The game aims to enhance memory retention and cognitive skills through a classic card-matching game. The method used here is to create a carefully designed prompt using natural language. The prompt suggested here can be classified as a software development task prompt focusing on educational game design using web technologies. It provides a mix of functional requirements (game mechanics, grid layout) and non-functional requirements (aesthetic consistency, performance). Such prompts are commonly used in software engineering to guide developers through structured feature implementations for applications that have both educational and entertainment value. The first significant finding of this study highlights ChatGPT’s remarkable capacity to emulate programmer-like responses. Secondly, the results obtained indicate that a carefully tailored prompting approach can be the preferred strategy for teachers with a lack of coding competencies when generating educational games using ChatGPT. In conclusion, the research suggests that slight modifications and adjustments of the presented prompt can be used in the design of similar educational card games. The continuation of this research should demonstrate the possibilities of ChatGPT and similar AI tools in designing more complex educational games.
Authors
- Aleksandar Spasić (ORCID: https://orcid.org/0000-0002-0307-0982)
- Lazar Stоšić (ORCID: https://orcid.org/0000-0003-0039-7370)
- Miljana Mladenović (ORCID: https://orcid.org/0000-0002-7973-452X)
- Bratislav Nikolić (ORCID: https://orcid.org/0009-0008-7834-7115)
Publication Details
- Published
- 2025-01-01
- DOI
- https://doi.org/10.46793/edai24.153s
- Primary Topic
- Online Learning and Analytics
- Type
- article
- Field-Weighted Citation Impact
- 0.00