Generative Artificial Intelligence in Higher Education: Evidence from an Analysis of Institutional Policies and Guidelines
<|reference_start|>Generative Artificial Intelligence in Higher Education: Evidence from an Analysis of Institutional Policies and Guidelines: The release of ChatGPT in November 2022 prompted a massive uptake of generative artificial intelligence (GenAI) across higher education institutions (HEIs). HEIs scrambled to respond to its use, especially by students, looking first to regulate it and then arguing for its productive integration within teaching and learning. In the year since the release, HEIs have increasingly provided policies and guidelines to direct GenAI. In this paper we examined documents produced by 116 US universities categorized as high research activity or R1 institutions to comprehensively understand GenAI related advice and guidance given to institutional stakeholders. Through an extensive analysis, we found the majority of universities (N=73, 63%) encourage the use of GenAI and many provide detailed guidance for its use in the classroom (N=48, 41%). More than half of all institutions provided sample syllabi (N=65, 56%) and half (N=58, 50%) provided sample GenAI curriculum and activities that would help instructors integrate and leverage GenAI in their classroom. Notably, most guidance for activities focused on writing, whereas code and STEM-related activities were mentioned half the time and vaguely even when they were (N=58, 50%). Finally, more than one half of institutions talked about the ethics of GenAI on a range of topics broadly, including Diversity, Equity and Inclusion (DEI) (N=60, 52%). Overall, based on our findings we caution that guidance for faculty can become burdensome as extensive revision of pedagogical approaches is often recommended in the policies.<|reference_end|>
@article{mcdonald2024generative,
    title={Generative Artificial Intelligence in Higher Education: Evidence from an
  Analysis of Institutional Policies and Guidelines},
    author={Nora McDonald, Aditya Johri, Areej Ali, Aayushi Hingle},
    journal={arXiv preprint arXiv:2402.01659},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.01659},
    primaryClass={cs.CY cs.AI}
}