Responsible Adoption of Generative AI in Higher Education: Developing a "Points to Consider" Approach Based on Faculty Perspectives
Project Overview
The document explores the responsible integration of generative AI (GenAI) in higher education, advocating for a 'points to consider' approach that aligns with institutional values and governance. It outlines the potential benefits of GenAI, such as enhancing learning experiences, offering personalized feedback, and assisting educators with various tasks, while also addressing the associated risks and barriers to its adoption. Key challenges include ethical concerns, the accuracy of AI-generated content, and the necessity for established guidelines to ensure academic integrity and freedom. To navigate these complexities, the document proposes a comprehensive framework aimed at fostering the effective use of GenAI in educational practices, ultimately seeking to maximize its advantages while mitigating potential downsides.
Key Applications
Generative AI for Personalized Learning and Feedback
Context: Higher education, targeting faculty, students, and collaborative project teams in various disciplines including curriculum design, assignments, and team-based projects.
Implementation: Instructors and students use Generative AI tools to generate assignments and teaching materials, analyze written submissions, provide instant feedback on grammar, style, and content, and facilitate collaboration in group projects by suggesting roles and providing tailored resources.
Outcomes: Enhanced student engagement, improved academic performance through tailored assistance, faster feedback cycles, and improved collaboration efficiency leading to better project outcomes.
Challenges: Potential for academic dishonesty, reliance on AI that may inhibit skill development, concerns about the quality and accuracy of AI feedback, and the challenge of aligning AI recommendations with group member preferences.
Assignments Incorporating GenAI
Context: Higher education, targeting students, focusing on assignments designed to utilize GenAI while promoting critical engagement.
Implementation: Assignments encourage students to analyze AI-generated outputs or revise drafts with the help of GenAI tools, fostering critical thinking and engagement with course material.
Outcomes: Encouragement of critical thinking and active engagement with course materials.
Challenges: Possibility of students using GenAI to circumvent learning foundational skills.
Institutional Guidelines for GenAI Use
Context: Higher education, targeting faculty and administration, focusing on the governance of GenAI use in teaching, research, and administration.
Implementation: Development of policies and guidelines to standardize practices around GenAI use, ensuring protection of academic integrity and equitable access to technology.
Outcomes: Standardization of practices and improved academic integrity across the institution.
Challenges: Resistance to policy changes and differing interpretations of academic freedom.
Implementation Barriers
Awareness Barrier
Low faculty familiarity with GenAI tools and their potential impacts
Proposed Solutions: Professional development programs to educate faculty about GenAI and its applications.
Workload Barrier
Incorporating GenAI requires substantial additional labor from faculty, which may be uncompensated
Proposed Solutions: Institutional support for faculty workload management and compensation for additional responsibilities.
Ethical Barrier
Concerns about academic integrity, including plagiarism, and the potential for GenAI to facilitate cheating and ethical implications.
Proposed Solutions: Designing assignments that minimize the potential for GenAI-assisted cheating and developing clear guidelines and policies to govern the ethical use of AI in educational contexts.
Technical Barrier
The accuracy and reliability of AI-generated content can vary, leading to misinformation.
Proposed Solutions: Continuous improvement of AI algorithms and incorporating human review processes to verify AI outputs.
Accessibility Barrier
Not all students may have equal access to AI tools, leading to disparities in educational support.
Proposed Solutions: Ensuring equitable access to technology and resources for all students, including training sessions on using AI tools.
Project Team
Ravit Dotan
Researcher
Lisa S. Parker
Researcher
John G. Radzilowicz
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Ravit Dotan, Lisa S. Parker, John G. Radzilowicz
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18