In education, the integration of GenAI offers a multitude of applications within your courses. Presented is a detailed table categorizing various use cases, outlining the specific roles they play, their pedagogical benefits, and potential risks associated with their implementation.
![ALT Text: "A table detailing various roles of AI use in an educational setting, along with their pedagogical benefits and risks. There are seven roles listed:
1. Mentor - Role: Providing feedback. Pedagogical Benefit: Frequent feedback improves learning outcomes, even if all advice is not taken. Pedagogical Risk: Not critically examining feedback, which may contain errors.
2. Tutor - Role: Direct instruction. Benefit: Personalized direct instruction is very effective. Risk: Uneven knowledge base of AI. Serious confabulation risks.
3. Coach - Role: Prompt metacognition. Benefit: Opportunities for reflection and regulation, which improve learning outcomes. Risk: Tone or style of coaching may not match student. Risks of incorrect advice.
4. Teammate - Role: Increase team performance. Benefit: Provide alternate viewpoints, help learning teams function better. Risk: Confabulation and errors. 'Personality' conflicts with other team members.
5. Student - Role: Receive explanations. Benefit: Teaching others is a powerful learning technique. Risk: Confabulation and argumentation may derail the benefits of teaching.
6. Simulator - Role: Deliberate practice. Benefit: Practicing and applying knowledge aids transfer. Risk: Inappropriate fidelity.
7. Tool - Role: Accomplish tasks. Benefit: Helps students accomplish more within the same time frame. Risk: Outsourcing thinking, rather than work."](https://ctlt-ai-2023.sites.olt.ubc.ca/files/2024/03/Ai_teaching_Use_cases-940x770.jpg)
A Complete Breakdown of each use case and the original image can be found here.
At UBC, a prevalent method of utilizing GenAI tools like ChatGPT involves professors projecting these AI-generated responses during class. This interactive approach includes an in-depth discussion of the AI’s output. Here, the emphasis is on expanding upon the AI’s typically broad, high-level responses. The students are then encouraged to delve deeper, providing a more nuanced and comprehensive analysis of the subject at hand. This method serves a dual purpose. Firstly, it functions as an engaging learning activity, fostering critical thinking and deeper understanding among students. Secondly, it acts as a practical lesson on the responsible use of AI technologies. It highlights that while AI can be a valuable tool, its output should be critically evaluated and not relied upon as an all-encompassing solution. This approach educates students on the importance of discernment and the need for human oversight when integrating AI into various fields of study.