5.2. AI in Education: Teaching, Learning, and Student Support

Artificial intelligence is rapidly becoming a part of the educational ecosystem, extending far beyond the classroom. For faculty, AI offers new ways to design courses, provide timely feedback, and personalize learning. For staff, it can streamline advising, improve scheduling, and automate routine administrative tasks that free up time for meaningful student interaction. And for students, AI provides tools for tutoring, accessibility, and self-directed study. Taken together, these applications reveal that AI in education is not simply about teaching efficiency; it reshapes the relationships between learners, educators, and institutional support systems. To engage responsibly, we must ask not only how AI can make our work easier, but also how it can strengthen learning communities as a whole.

AI for Faculty

AI can extend a faculty member’s reach, not by replacing expertise, but by streamlining repetitive tasks. Instructors report using AI to:

• Provide draft feedback on writing or projects, then revising it to match their own voice and standards.
• Generate quiz questions, practice problems, or case studies more efficiently.
• Translate or adapt content for multilingual classrooms.
• Experiment with adaptive lessons that meet diverse learning needs.

These uses do not replace faculty judgment. Instead, they free up more time for mentoring, dialogue, and deeper engagement.

Here are some example prompts relevant to faculty:

• Prompt – Learning Outcomes
  • “You are a curriculum designer. I am creating a graduate-level occupational therapy course on community-based practice. Draft three measurable learning outcomes that align with Bloom’s taxonomy and emphasize critical thinking and cultural responsiveness.”
• Prompt – Discussion Board Creation
  • “Design a discussion prompt for a master’s-level course that encourages reflection on social determinants of health and connects theory to clinical experience. Include 2–3 guiding questions and a short example student response.”
• Prompt – Accessible Content
  • “Summarize the following lecture content for a student with reading comprehension challenges. Use plain language, short sentences, and key vocabulary definitions.”

AI for Students

Students also experiment with AI to support their studies. Productive uses include:

• Creating personalized study aids such as flashcards, summaries, or practice quizzes.
• Brainstorming ideas for writing or projects, while remaining responsible for synthesis and originality.
• Using tutoring-style prompts to clarify concepts or practice problems.
• Translating or simplifying technical texts for accessibility.

As with faculty, students benefit most when AI is a support for learning, not a shortcut around it.

Here are some example prompts relevant to students looking for AI support:

• Prompt – Clarifying Complex Concepts
  • “Explain [concept, e.g., neuroplasticity] in simple language for a first-year occupational therapy student. Include an analogy and a brief real-world example.”
• Prompt – Creating Study Guides
  • “Summarize the key ideas from this lecture outline into a one-page study guide. Use concise bullet points and define all key terms.”
• Prompt – Visual Learning
  • “Create a short list of ideas for visuals or diagrams that would help students grasp [specific concept]. Describe each in words only.”
• Prompt – Group Project Roles
  • “Suggest a clear division of roles and responsibilities for a three-student group project on community-based health promotion.”
• Prompt – Peer Review Practice
  • “Provide a model peer review comment that balances strengths and areas for improvement on a draft research proposal.”
• Prompt – Communication Confidence
  • “Generate role-play prompts to help students practice delivering professional feedback to a peer.”

Opportunities and Risks

While AI can personalize and extend support, it also brings risks. Over-reliance on AI for tutoring may lead to shallow understanding. Automated grading can reproduce bias or miss nuance. Faculty must guide students to see AI as supplementary, not substitutive. Likewise, students must remain alert to errors and responsible for verifying information.

Practical AI for Instructors and Students

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Looking Ahead

Next, in 5.3 AI in Research, we will examine how AI supports scholarly inquiry—helping with literature reviews, data analysis, and academic writing—while also raising important ethical questions.