4-Step Framework for Incorporating AI in Teaching

Writing for Harvard Business Publishing Education, Prof. Oguz A. Acar of King's College London encourages educators to shift their approaches towards incorporation rather than rejection of AI in their teaching.

"In my experience, building into the syllabus activities that help students develop Generative AI skills has not only enhanced student engagement and learning, but has also led to a noticeable improvement in their work." Prof. Oguz A. Acar, King's College London

The impact of generative AI in education is nothing short of remarkable, both in the magnitude of its reach and speed in evolving into various platforms. Addressing the topic of AI within learning and teaching is a daunting task, and institutions have been defensive in their strategies toward this unknown variable. In his post "Are Your Students Ready for AI?" Prof. Oguz A. Acar of King's College London encourages educators to shift their approaches towards incorporation rather than isolation of AI in their teaching. He encourages educators to focus on key skills learners need to effectively use generative AI to participate in a world of ever-evolving technology.

To support educators in the development of key skills in students, Acar shares his PAIR framework. Developed as an outcome of his research on the psychology of AI and student learning, the four-step framework is intended to support educators in their discussions and considerations around integrating AI into subject delivery and design of assessment tasks.

Component 1. Problem: Involves students identifying/formulating the core problem that students will focus on. This step is centred on inspiring students to spot, scrutinise and articulate their comprehension of the problem, and in doing so, communicate their expectations of AI tool(s) in detail and clarity.

Component 2. AI: Involves students researching and selecting a suitable AI tool that is suitable for their identified problem. This step is focused on encouraging students to apply a critical lens when approaching AI tools that are available to them to identify the most optimal tool for their purpose.

Component 3. Interaction: Involves students actively engaging/experimenting with the AI tool to evaluate the capabilities and limits of the platform. This step is intended to encourage students to put AI’s outputs under a microscope, differentiating what is beneficial and accurate from what is not and letting their critical thinking guide the way.

Component 4. Reflection: Involves students reflecting on their feelings through the experience and evaluating how the selected AI platform impacted the problem-solving process. This step is designed to afford students the opportunity to be introspective about lessons learned from working with generative AI tools and develop a better understanding of their emotional responses while utilising the tools.

For further information, please read the post "Are Your Students Ready for AI?". If you would like to further discuss the above strategies, please feel free to reach out to BEL+T.