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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2401.08659 |
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| _version_ | 1866916103678066688 |
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| author | Łodzikowski, Kacper Foltz, Peter W. Behrens, John T. |
| author_facet | Łodzikowski, Kacper Foltz, Peter W. Behrens, John T. |
| contents | We discuss the implications of generative AI on education across four critical sections: the historical development of AI in education, its contemporary applications in learning, societal repercussions, and strategic recommendations for researchers. We propose ways in which generative AI can transform the educational landscape, primarily via its ability to conduct assessment of complex cognitive performances and create personalized content. We also address the challenges of effective educational tool deployment, data bias, design transparency, and accurate output verification. Acknowledging the societal impact, we emphasize the need for updating curricula, redefining communicative trust, and adjusting to transformed social norms. We end by outlining the ways in which educational stakeholders can actively engage with generative AI, develop fluency with its capacities and limitations, and apply these insights to steer educational practices in a rapidly advancing digital landscape. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_08659 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Generative AI and Its Educational Implications Łodzikowski, Kacper Foltz, Peter W. Behrens, John T. Computers and Society We discuss the implications of generative AI on education across four critical sections: the historical development of AI in education, its contemporary applications in learning, societal repercussions, and strategic recommendations for researchers. We propose ways in which generative AI can transform the educational landscape, primarily via its ability to conduct assessment of complex cognitive performances and create personalized content. We also address the challenges of effective educational tool deployment, data bias, design transparency, and accurate output verification. Acknowledging the societal impact, we emphasize the need for updating curricula, redefining communicative trust, and adjusting to transformed social norms. We end by outlining the ways in which educational stakeholders can actively engage with generative AI, develop fluency with its capacities and limitations, and apply these insights to steer educational practices in a rapidly advancing digital landscape. |
| title | Generative AI and Its Educational Implications |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2401.08659 |