U.S. Department of Education: Navigating AI in Postsecondary Education – Building Capacity for the Road Ahead
Summary of Read Full Report
This U.S. Department of Education document offers guidance on responsibly integrating artificial intelligence (AI) into postsecondary education.
-
AI's Transformative Impact: The document emphasizes that AI is significantly transforming postsecondary education, impacting areas such as admissions, enrollment, academic advising, and learning environments. It also highlights the dual role of [higher education](/solutions/higher-education) to leverage AI to improve access and success for all students, while preparing students for the AI-driven job market.
-
Key Recommendations for AI Integration: The brief outlines five key recommendations for postsecondary institutions:
- Establish transparent policies for AI use.
- Create infrastructure to support AI in instruction, advising, and assessment.
- Test and evaluate AI tools rigorously.
- Seek collaborative partnerships for AI design.
- Review and supplement programs in light of AI's impact on future jobs. These recommendations are designed to be inclusive and adaptive for institutions with varying levels of resources and expertise.
-
Ethical Considerations and Transparency: The document stresses the importance of ethical AI practices, including ensuring equity, fairness, and non-discrimination. It uses examples of "stealth assessment" and "continuous monitoring" to demonstrate how a lack of transparency can erode trust and undermine institutional values. The document highlights the need for clear disclosure of data use and affirmative consent. It also mentions the potential for algorithmic discrimination and the need to mitigate this through rigorous testing and evaluation of AI systems.
-
AI Literacy: The document emphasizes the importance of developing AI literacy for students, faculty, and staff to ensure safe and effective use of AI. AI literacy includes understanding, using, and critically evaluating AI systems, as well as addressing how AI can facilitate discrimination and harassment. It notes that non-traditional students may face particular challenges in developing AI literacy skills. The document also states that faculty should be given the time to collaborate with their peers to learn how to implement AI models in their teaching and research.
-
Collaborative Partnerships: The document recommends forging partnerships with industry, non-profit organizations, and other postsecondary institutions on AI design and testing. It notes that collaborative partnerships can bring together educators' expertise in pedagogy, researchers’ expertise in measurement and evaluation, and technology companies’ technical expertise.
-
AI in Learning and Instruction: The document explores the use of AI in enhancing learning and instruction. It details the use of AI-driven adaptive learning environments to improve learning outcomes. It also points to the use of AI in providing just-in-time individualized help for students and for automating routine tasks for instructors. The document notes the capabilities of AI-enabled tools such as essay scoring systems and Automatic Short Answer Grading (ASAG). It also examines the use of AI to provide feedback to instructors on their practices. The use of AI to support students with disabilities, and the use of virtual and augmented reality for students with disabilities, are also explored. The document also discusses the transformative impact of AI on scientific research.
-
AI for Institutional Operations: The document details the use of AI to improve institutional operations including recruiting, admissions, retention, and enrollment services. It also examines how AI-enhanced student support can lead to improved learning outcomes. It addresses the use of AI-driven tools to support self-regulated learning, provide support for English language learners and students with disabilities, and support students' mental health.
-
The Need for Continuous Evaluation: The brief emphasizes that AI systems should be evaluated through iterative cycles of testing, feedback, and improvement, in order to build high-quality evidence on the abilities of AI platforms to support student services. It stresses the importance of determining what works, for whom, and under what conditions when implementing AI-driven tools.
-
Federal Guidance and Resources: This document is aligned with federal guidelines and guardrails. It highlights resources like the Blueprint for an AI Bill of Rights and the NIST AI Risk Management Framework as helpful tools for developing trustworthy AI systems. It also references resources such as the National AI Research Resource Pilot and the Center for Equitable AI and Machine Learning Systems.
These points illustrate the broad scope of the document in addressing the opportunities, challenges, and ethical considerations of integrating AI into postsecondary education. The document provides a comprehensive framework for educational leaders to navigate the complexities of AI implementation, while ensuring equitable and ethical use of these technologies.