mlsanityData to 14 Oct 2026

Generative AI in Higher Education: Seeing ChatGPT Through Universities' Policies, Resources, and Guidelines

arXiv 2312.05235 ↗First posted 8 Dec 2023cs.CL cs.CYcited by 11

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Abstract (arXiv)

The advancements in Generative Artificial Intelligence (GenAI) provide opportunities to enrich educational experiences, but also raise concerns about academic integrity. Many educators have expressed anxiety and hesitation in integrating GenAI in their teaching practices, and are in needs of recommendations and guidance from their institutions that can support them to incorporate GenAI in their classrooms effectively. In order to respond to higher educators' needs, this study aims to explore how universities and educators respond and adapt to the development of GenAI in their academic contexts by analyzing academic policies and guidelines established by top-ranked U.S. universities regarding the use of GenAI, especially ChatGPT. Data sources include academic policies, statements, guidelines, and relevant resources provided by the top 100 universities in the U.S. Results show that the majority of these universities adopt an open but cautious approach towards GenAI. Primary concerns lie in ethical usage, accuracy, and data privacy. Most universities actively respond and provide diverse types of resources, such as syllabus templates, workshops, shared articles, and one-on-one consultations focusing on a range of topics: general technical introduction, ethical concerns, pedagogical applications, preventive strategies, data privacy, limitations, and detective tools. The findings provide four practical pedagogical implications for educators in teaching practices: accept its presence, align its use with learning objectives, evolve curriculum to prevent misuse, and adopt multifaceted evaluation strategies rather than relying on AI detectors. Two recommendations are suggested for educators in policy making: establish discipline-specific policies and guidelines, and manage sensitive information carefully.

Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 6 of its 62 references that are in the map. First posted on arXiv 8 Dec 2023.

Builds on

6 of 62 references.

References · 6

  1. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 13,028
  2. 2023Can AI-Generated Text be Reliably Detected?cited by 386
  3. 2023The political ideology of conversational AI: Converging evidence on ChatGPT's pro-environmental, left-libertarian orientationcited by 189
  4. 2023Testing of Detection Tools for AI-Generated Textcited by 90
  5. 2023The Robots are Here: Navigating the Generative AI Revolution in Computing Educationcited by 86
  6. 2023Generative AI in Computing Education: Perspectives of Students and Instructorscited by 17

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 2; 2025: 3; 2026: 6.

11 papers.