Comparing the Effectiveness of Generative AI for Learning and Developing Flutter Application
The rapid growth of business demands modern technological advancements, leading to an increased need for accelerated learning and development of tools. Generative AI has become a key player in enhancing these areas by aiding in code generation for application development. Specifically, Generative AI can produce functional code for various programming languages, aiding in the setup of UI components, navigation, and complex state management. This study evaluates the effectiveness of three widely-used Generative AI tools— ChatGPT, Copilot, and Codeium—chosen for their popularity and diverse approaches to code generation. Standardized prompts were used to generate Flutter code for beginner, intermediate, and advanced tasks. The results show that ChatGPT outperformed other tools, consistently generating runnable and comprehensive code, while Copilot and Codeium exhibited some limitations in handling complex tasks. These findings suggest that integrating Generative AI into Flutter development can significantly accelerate the coding process and enhance application quality.
Authors
- Pheng‐Ann Heng (ORCID: https://orcid.org/0000-0003-3055-5034)
- Parkpoom Chaisiriprasert (ORCID: https://orcid.org/0009-0002-4148-5043)
- Karn Yongsiriwit (ORCID: https://orcid.org/0000-0001-5914-9051)
Institutions
- Rangsit University (TH)
Publication Details
- Published
- 2024-11-14
- DOI
- https://doi.org/10.1109/incit63192.2024.10810490
- Citations
- 1
- Primary Topic
- Model Reduction and Neural Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.28