Generative AI in Higher Education: From Fear to Functional Tool

By: Adrienna Bartnicki

When generative AI first emerged, many educators (including myself) reacted with apprehension, conjuring images of dystopian sci-fi scenarios (I, Robot in my case). Therefore, my gut response was to avoid it for as long as I could. Turns out, that would not be very long. 

When invited to enter into a discussion about using generative AI within the summer Writing Across the Curriculum (WAC) Program, my teaching partner and I inputted our culminating semester final project assignments into Chat GPT.  Would you guess that the information we read and graded favorably looked very similar? We arrived at the conclusion that generative AI is not going anywhere and our students are, in fact, using this tool. AI continues to have more and more influence on student learning and assignment completion. As this technology becomes more prevalent in academic settings, it's clear that avoidance is not a viable strategy. 

Instead, we are seeking to embrace generative AI as a supportive tool that can enhance teaching and learning when used ethically and thoughtfully while maintaining academic integrity and fostering genuine learning. Occupational therapists in the field are currently using AI to:

• Brainstorm intervention ideas, activities, or modification;

• Simplify complex medical concepts; 

• Generate instructions, education & visual supports;

• Draft documentation;

• Suggest phrasing for observations;

• Summarize research for evidence-based practice;

• Study & engage in professional development.

Based on what we have done in the occupational therapy program thus far, here are some insights and strategies for purposefully integrating AI into the curriculum:

For skeptical instructors who worry AI will enable cheating or replace critical thinking, consider how it has the potential to enhance the learning experience. You can teach students to critically evaluate AI-generated content, demonstrate real-world applications, and prepare students for a future where AI may have a regular and significant role in their daily work. Use of AI image generators like Canva's AI to create custom visuals can enhance lectures and course materials. Leveraging AI to create multi-modal content can support diverse learning styles and needs. 

Giving students permission to use generative AI, guidance for how and when to use it, and explicit instructions to analyze, edit, refine, critique, and polish the information, is our responsibility as teachers and leaders. My current policy includes the following: You may use generative AI to help brainstorm ideas. However, you may not submit any work generated by an AI program as your own. If you include material generated by an AI program, it should be cited like any other reference material with due consideration for the quality of the reference. 

Using my reframed fear during WAC, we created an assignment revolving around using generative AI to identify “answers” for treatment planning, but then using human intuition, problem-solving, and flexible thinking for students to debate responses with sound rationale. Additionally, I have assigned a learning activity in class where students use generative AI to create a list of interventions. They then use the list to collaborate and problem-solve with their “peer client” to identify which interventions are a best fit for that person’s lifestyle. Generating information alone without the human collaboration component would not be sufficient. As with any technology, we must regularly review and update course content to include current and relevant AI topics and skills.

For students trying to determine how to use AI ethically and effectively, I encourage them to view AI as a collaborative tool. Directly submitting AI-generated work as one's own is a form of academic dishonesty. However, it can be used for brainstorming, simplifying complex concepts, and establishing a starting point. Students should disclose when they have used AI in their assignments and show how they have enhanced the content. Students can use AI to help summarize research, generate questions, structure essays, or provide suggestions for writing. AI can even generate flashcards or summarize notes to help prepare for exams! I have had students take initiative to create an individualized visualization intervention for their pediatric clients! 

While AI can offer benefits, the limitations and challenges must also be discussed. AI-generated content can be inaccurate or biased. Everyone should be cautious and critical of AI results and answers. AI has the potential to stifle creativity and independent thinking, if used exclusively. Not all students may have equal access to and understanding of the supports and concerns of AI tools, potentially creating disparities in academic performance. 

Moreover, rather than assuming expertise on the part of students, professors should incorporate lessons on AI literacy to intentionally teach all students how to critically evaluate AI-generated content to limit this. Leaders are responsible for staying current with AI advancements and how it applies (for better and worse) to each of our fields. Working with colleagues within and across disciplines to develop best practices for AI integration and alternative uses for the benefit of learning is recommended.

AI use in higher education and the health and medical field is happening! Ultimately, the goal is to foster environments where AI is neither feared nor blindly embraced, but thoughtfully integrated into the process. This approach will not only enhance the quality of education, but also prepare students for a world where AI is an integral part of many professions. 

As we navigate decisions regarding AI in higher education, let's approach it with curiosity, critical thinking, and a commitment to maintaining the highest standards of academic integrity. By doing so, we can ensure that AI becomes a powerful ally in our quest for knowledge and understanding, rather than a threat to the fundamental values of education.

Please note the above blog post was created following 3 iterations of drafting, generation using Perplexity AI, analysis, and editing.