WIP: Assessing the Effectiveness of ChatGPT in Preparatory Testing Activities
Fuente:
arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866913721622724608 |
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| author | Haldar, Susmita Pierce, Mary Capretz, Luiz Fernando |
| author_facet | Haldar, Susmita Pierce, Mary Capretz, Luiz Fernando |
| contents | This innovative practice WIP paper describes a research study that explores the integration of ChatGPT into the software testing curriculum and evaluates its effectiveness compared to human-generated testing artifacts. In a Capstone Project course, students were tasked with generating preparatory testing artifacts using ChatGPT prompts, which they had previously created manually. Their understanding and the effectiveness of the Artificial Intelligence generated artifacts were assessed through targeted questions. The results, drawn from this in-class assignment at a North American community college indicate that while ChatGPT can automate many testing preparation tasks, it cannot fully replace human expertise. However, students, already familiar with Information Technology at the postgraduate level, found the integration of ChatGPT into their workflow to be straightforward. The study suggests that AI can be gradually introduced into software testing education to keep pace with technological advancements. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_03951 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | WIP: Assessing the Effectiveness of ChatGPT in Preparatory Testing Activities Haldar, Susmita Pierce, Mary Capretz, Luiz Fernando Software Engineering Artificial Intelligence This innovative practice WIP paper describes a research study that explores the integration of ChatGPT into the software testing curriculum and evaluates its effectiveness compared to human-generated testing artifacts. In a Capstone Project course, students were tasked with generating preparatory testing artifacts using ChatGPT prompts, which they had previously created manually. Their understanding and the effectiveness of the Artificial Intelligence generated artifacts were assessed through targeted questions. The results, drawn from this in-class assignment at a North American community college indicate that while ChatGPT can automate many testing preparation tasks, it cannot fully replace human expertise. However, students, already familiar with Information Technology at the postgraduate level, found the integration of ChatGPT into their workflow to be straightforward. The study suggests that AI can be gradually introduced into software testing education to keep pace with technological advancements. |
| title | WIP: Assessing the Effectiveness of ChatGPT in Preparatory Testing Activities |
| topic | Software Engineering Artificial Intelligence |
| url | https://arxiv.org/abs/2503.03951 |