Through tools like ChatGPT, AI has become a household buzzword. But its usage continues to lag among educators. There are various reasons for this: lack of awareness, resistance to change, and of course the lack of robust research.
It makes sense that some educators view AI with skepticism. But giving into this resistance would be a missed opportunity, because AI can help teachers reduce their workload so that they can focus on the moments that matter — the time spent with students.
To guide educators on how to get the most out of generative AI in this manner, we picked three important aspects of instructional practice: lesson planning, providing explanations, and retrieval practice.
Generative AI Drives Lesson Plan Efficiency and Effectiveness
Building an effective and engaging lesson plan takes time and effort. For each lesson plan, teachers have to determine how to best deliver content while tailoring the quantity and complexity of materials to students’ pre-existing knowledge.
In this respect, generative AI tools can do much of the heavy lifting. When carefully prompted, it can present thorough lesson plan recommendations to educators.
Effective lesson planning leads to durable and lasting learnings. Without an educator or a machine doing this work, lesson designs can become iterative, repetitive, or out-of-date. For this reason, through generative AI, educators are better supported and students get the best out of their learning.
Here’s a handy microlesson on “Using AI to design lessons aligned with cognitive load theory”.
Generative AI Can Personalize Explanations
Another use case for generative AI is generating explanations. Much like lesson planning, providing explanations for students is ESSENTIAL. Explanations are needed so that students can make sense of new knowledge and process it deeply to connect it with their pre-existing knowledge. Students need quality explanations for semantic processing — this is the kind of processing that allows them to construct meaning of new incoming knowledge.
Instructors must understand their students’ prior knowledge. They need to develop explanations with appropriate simplicity, oftentimes using stories and analogies to land their explanations effectively. All of this is a complex (and time consuming) process.
Generative AI tools can tailor its outputs to its audience. By asking generative AI tools to translate complex ideas in simple terms, students are more likely to understand concepts. Instructors can also directly inform the generative AI tool the level of their students’ prior knowledge and the machine can respond accordingly. Generative AI tools can also develop stories and analogies in the form of explanations to suit students’ interests and hence have a better chance of capturing their attention which then leads to deep processing of new knowledge.
Here’s a handy microlesson on “Using AI for deep processing through explanations”.
Generative AI Automates the Development of Retrieval Practice Exercises
Retrieval practice is a learning strategy that involves actively recalling information from memory without having it in front of you. It’s a powerful strategy for students because it helps them retain information better. The added challenge of recalling knowledge from memory allows it to be stored better.
It’s a great formative assessment tool for educators because when students can retrieve knowledge with accuracy and fluency, it gives them an idea of how well the students are learning. And if students are found to be struggling, it provides educators with direction to tweak their instruction.
The evidence in support of retrieval practice as a learning strategy and as an instructional technique is so robust and has been dated back almost 100 years. A common retrieval practice technique used by instructors is low-stakes or no-stakes quizzes.
Regular creation of retrieval practice devices such as low-stakes quizzes, multiple choice questions, and polls is an exhausting process. The act of creating quizzes requires creativity, expertise, and a whole lot of time. Educators generating these devices from scratch often require a large amount of time and effort. Time and effort that overworked teachers often do not have.
The automation of this process with generative AI creates the efficiency necessary to implement retrieval practice on a regular basis. By using generative AI in this manner, teachers would be able to deliver best practices in teaching to their students without having to work beyond their means.
Here’s a handy microlesson on “Using AI for retrieval practice”.
Conclusion
In this article, we highlighted a few ways teachers can use generative AI to optimize their work. It is always important to remember that generative AI is an assistive tool. Teachers are the experts and they should always take the time to fact check anything generated by AI. Instructors also know their students best. Ultimately, only they can assess whether the content created by AI is suitable or useful for their learners.
Dr. Peter Zhang, PharmD, MBA, is a Hospital Pharmacist at Southlake Regional Health Centre, and a PhD student at the University of Toronto’s Leslie Dan Faculty of Pharmacy.
Dr. Nidhi Sachdeva, MA, PhD, is a post-secondary educator, researcher, and teaches in the Teacher Education program at the Ontario Institute for Studies in Education (OISE). Nidhi is the co-author of a newsletter called the Science of Learning, which aims to reduce existing gaps between educational research and instructional practice.
