Speeding up design and making to reduce time-to-project and time-to-market: an AI-Enhanced approach in engineering education
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arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866910886608764928 |
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| author | Adorni, Giovanni Grosso, Daniele |
| author_facet | Adorni, Giovanni Grosso, Daniele |
| contents | This paper explores the integration of AI tools, such as ChatGPT and GitHub Copilot, in the Software Architecture for Embedded Systems course. AI-supported workflows enabled students to rapidly prototype complex projects, emphasizing real-world applications like SLAM robotics. Results demon-started enhanced problem-solving, faster development, and more sophisticated outcomes, with AI augmenting but not replacing human decision-making. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_16307 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Speeding up design and making to reduce time-to-project and time-to-market: an AI-Enhanced approach in engineering education Adorni, Giovanni Grosso, Daniele Artificial Intelligence I.2; K.3 This paper explores the integration of AI tools, such as ChatGPT and GitHub Copilot, in the Software Architecture for Embedded Systems course. AI-supported workflows enabled students to rapidly prototype complex projects, emphasizing real-world applications like SLAM robotics. Results demon-started enhanced problem-solving, faster development, and more sophisticated outcomes, with AI augmenting but not replacing human decision-making. |
| title | Speeding up design and making to reduce time-to-project and time-to-market: an AI-Enhanced approach in engineering education |
| topic | Artificial Intelligence I.2; K.3 |
| url | https://arxiv.org/abs/2503.16307 |