Reconsidering Student Success in the Age of Artificial Intelligence (2024)

This report by Shouping Hu and Fengfeng Ke from Florida State University examines how artificial intelligence (AI) is reshaping the concept of student success in higher education. It explores the phases of AI integration in educational settings and the potential future impacts on teaching, learning, and the value of postsecondary credentials.

Main Takeaways:

• Current Phase: AI as a Tool for Enhancement

  • Integration of AI in Education: AI is currently being utilized to enhance teaching, advising, and administrative processes, aiming to improve student success within the existing educational framework.
  • AI-Mediated Tools: These include AI-assisted personalized teaching, tutoring, assessment, and advising, which provide timely and targeted support to students, helping them succeed academically.

• Future Phases: AI as an Agent of Change

  • AI Agents: As AI evolves, it is expected to become more proactive, performing tasks across applications and making suggestions before being asked. This could transform not only how we live but also how education systems operate.
  • Skillset Transformation: The advancement of AI will necessitate changes in the skillsets and credentials that are valuable in the labor market. Higher education must adapt to ensure students are equipped for a future where they will need to work alongside AI agents.

• Long-Term Considerations: Preparing for AGI

  • Artificial General Intelligence (AGI): In the long term, if AI reaches the stage of AGI, it could supplant many current skillsets. Higher education will need to be fundamentally transformed to prepare students for a world shared with intelligent machines.
  • Holistic Development: Emphasizing the holistic development of human nature might become crucial. Attributes such as creativity, empathy, and ethical reasoning could be areas where humans maintain an advantage over AI.

• Implications for Policy and Practice

  • Revised Educational Models: Institutions will need to reconsider and possibly overhaul their educational models to align with the evolving demands of an AI-powered world.
  • Lifelong Learning: Encouraging lifelong learning and adaptability will be key as the nature of work and required skills continue to change rapidly.
  • Ethical and Inclusive AI: Policies should ensure that AI applications in education are developed and used ethically and inclusively, considering the potential biases and inequalities they might perpetuate.