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

• URL: http://arxiv.org/abs/2312.05235v3
• Date: Fri, 12 Jul 2024 04:21:46 GMT
• Title: Generative AI in Higher Education: Seeing ChatGPT Through Universities' Policies, Resources, and Guidelines
• Authors: Hui Wang, Anh Dang, Zihao Wu, Son Mac,
• Abstract summary: This study analyzes academic policies and guidelines established by top-ranked U.S. universities regarding the use of GenAI. Results show that the majority of these universities adopt an open but cautious approach towards GenAI. Findings provide four practical implications for educators in teaching practices.
• Score: 11.470910427306569
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

Related papers

• Early Adoption of Generative Artificial Intelligence in Computing Education: Emergent Student Use Cases and Perspectives in 2023 [38.83649319653387]
  There is limited prior research on computing students' use and perceptions of GenAI. We surveyed all computer science majors in a small engineering-focused R1 university. We discuss the impact of our findings on the emerging conversation around GenAI and education.
  arXiv  Detail & Related papers  (2024-11-17T20:17:47Z)
• Analysis of Generative AI Policies in Computing Course Syllabi [3.7869332128069773]
  Since the release of ChatGPT in 2022, Generative AI (GenAI) is increasingly being used in higher education computing classrooms across the U.S. We collected 98 computing course syllabi from 54 R1 institutions in the U.S. and studied the GenAI policies they adopted and the surrounding discourse. Our analysis shows that 1) most instructions related to GenAI use were as part of the academic integrity policy for the course and 2) most syllabi prohibited or restricted GenAI use, often warning students about the broader implications of using GenAI.
  arXiv  Detail & Related papers  (2024-10-29T17:34:10Z)
• Could ChatGPT get an Engineering Degree? Evaluating Higher Education Vulnerability to AI Assistants [175.9723801486487]
  We evaluate whether two AI assistants, GPT-3.5 and GPT-4, can adequately answer assessment questions. GPT-4 answers an average of 65.8% of questions correctly, and can even produce the correct answer across at least one prompting strategy for 85.1% of questions. Our results call for revising program-level assessment design in higher education in light of advances in generative AI.
  arXiv  Detail & Related papers  (2024-08-07T12:11:49Z)
• A Systematic Review of Generative AI for Teaching and Learning Practice [0.37282630026096586]
  There are no agreed guidelines towards the usage of GenAI systems in higher education. There is a need for additional interdisciplinary, multidimensional studies in HE through collaboration.
  arXiv  Detail & Related papers  (2024-06-13T18:16:27Z)
• Securing the Future of GenAI: Policy and Technology [50.586585729683776]
  Governments globally are grappling with the challenge of regulating GenAI, balancing innovation against safety. A workshop co-organized by Google, University of Wisconsin, Madison, and Stanford University aimed to bridge this gap between GenAI policy and technology. This paper summarizes the discussions during the workshop which addressed questions, such as: How regulation can be designed without hindering technological progress?
  arXiv  Detail & Related papers  (2024-05-21T20:30:01Z)
• Generative Artificial Intelligence in Higher Education: Evidence from an Analysis of Institutional Policies and Guidelines [4.438312734352056]
  ChatGPT in November 2022 prompted a massive uptake of generative artificial intelligence (GenAI) across higher education institutions (HEIs) In the year since the release, HEIs have increasingly provided policies and guidelines to direct GenAI. This paper examined documents produced by 116 US universities categorized as high research activity or R1 institutions to understand GenAI related advice and guidance given to institutional stakeholders.
  arXiv  Detail & Related papers  (2024-01-12T14:58:13Z)
• PapagAI:Automated Feedback for Reflective Essays [48.4434976446053]
  We present the first open-source automated feedback tool based on didactic theory and implemented as a hybrid AI system. The main objective of our work is to enable better learning outcomes for students and to complement the teaching activities of lecturers.
  arXiv  Detail & Related papers  (2023-07-10T11:05:51Z)
• The AI generation gap: Are Gen Z students more interested in adopting generative AI such as ChatGPT in teaching and learning than their Gen X and Millennial Generation teachers? [0.0]
  Gen Z students were generally optimistic about the potential benefits of generative AI (GenAI) Gen X and Gen Y teachers expressed heightened concerns about overreliance, ethical and pedagogical implications.
  arXiv  Detail & Related papers  (2023-05-04T14:42:06Z)
• Students' Voices on Generative AI: Perceptions, Benefits, and Challenges in Higher Education [2.0711789781518752]
  This study explores university students' perceptions of generative AI (GenAI) technologies, such as ChatGPT, in higher education. Students recognized the potential for personalized learning support, writing and brainstorming assistance, and research and analysis capabilities. Concerns about accuracy, privacy, ethical issues, and the impact on personal development, career prospects, and societal values were also expressed.
  arXiv  Detail & Related papers  (2023-04-29T15:53:38Z)
• An Experience Report of Executive-Level Artificial Intelligence Education in the United Arab Emirates [53.04281982845422]
  We present an experience report of teaching an AI course to business executives in the United Arab Emirates (UAE) Rather than focusing only on theoretical and technical aspects, we developed a course that teaches AI with a view to enabling students to understand how to incorporate it into existing business processes.
  arXiv  Detail & Related papers  (2022-02-02T20:59:53Z)
• Creation and Evaluation of a Pre-tertiary Artificial Intelligence (AI) Curriculum [58.86139968005518]
  The Chinese University of Hong Kong (CUHK)-Jockey Club AI for the Future Project (AI4Future) co-created an AI curriculum for pre-tertiary education. A team of 14 professors with expertise in engineering and education collaborated with 17 principals and teachers from 6 secondary schools to co-create the curriculum. The co-creation process generated a variety of resources which enhanced the teachers knowledge in AI, as well as fostered teachers autonomy in bringing the subject matter into their classrooms.
  arXiv  Detail & Related papers  (2021-01-19T11:26:19Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.