Enhancing Educational Efficiency: Generative AI Chatbots and DevOps in Education 4.0
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866916297164455936 |
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| author | Mekić, Edis Jovanović, Mihailo Kuk, Kristijan Prlinčević, Bojan Savić, Ana |
| author_facet | Mekić, Edis Jovanović, Mihailo Kuk, Kristijan Prlinčević, Bojan Savić, Ana |
| contents | This research paper will bring forth the innovative pedagogical approach in computer science education, which uses a combination of methodologies borrowed from Artificial Intelligence (AI) and DevOps to enhance the learning experience in Content Management Systems (CMS) Development. It has been done over three academic years, comparing the traditional way of teaching with the lately introduced AI-supported techniques. This had three structured sprints, each one of them covering the major parts of the sprint: object-oriented PHP, theme development, and plugin development. In each sprint, the student deals with part of the theoretical content and part of the practical task, using ChatGPT as an auxiliary tool. In that sprint, the model will provide solutions in code debugging and extensions of complex problems. The course includes practical examples like code replication with PHP, functionality expansion of the CMS, even development of custom plugins, and themes. The course practice includes versions' control with Git repositories. Efficiency will touch the theme and plugin output rates during development and mobile/web application development. Comparative analysis indicates that there is a marked increase in efficiency and shows effectiveness with the proposed AI- and DevOps-supported methodology. The study is very informative since education in computer science and its landscape change embodies an emerging technology that could have transformation impacts on amplifying the potential for scalable and adaptive learning approaches. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_15382 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Enhancing Educational Efficiency: Generative AI Chatbots and DevOps in Education 4.0 Mekić, Edis Jovanović, Mihailo Kuk, Kristijan Prlinčević, Bojan Savić, Ana Computers and Society Artificial Intelligence Software Engineering This research paper will bring forth the innovative pedagogical approach in computer science education, which uses a combination of methodologies borrowed from Artificial Intelligence (AI) and DevOps to enhance the learning experience in Content Management Systems (CMS) Development. It has been done over three academic years, comparing the traditional way of teaching with the lately introduced AI-supported techniques. This had three structured sprints, each one of them covering the major parts of the sprint: object-oriented PHP, theme development, and plugin development. In each sprint, the student deals with part of the theoretical content and part of the practical task, using ChatGPT as an auxiliary tool. In that sprint, the model will provide solutions in code debugging and extensions of complex problems. The course includes practical examples like code replication with PHP, functionality expansion of the CMS, even development of custom plugins, and themes. The course practice includes versions' control with Git repositories. Efficiency will touch the theme and plugin output rates during development and mobile/web application development. Comparative analysis indicates that there is a marked increase in efficiency and shows effectiveness with the proposed AI- and DevOps-supported methodology. The study is very informative since education in computer science and its landscape change embodies an emerging technology that could have transformation impacts on amplifying the potential for scalable and adaptive learning approaches. |
| title | Enhancing Educational Efficiency: Generative AI Chatbots and DevOps in Education 4.0 |
| topic | Computers and Society Artificial Intelligence Software Engineering |
| url | https://arxiv.org/abs/2406.15382 |