AI is here, and students are using it. While we may not want students to use AI to study, it's important to realize that you can have a big impact on how effective that AI use is. If we don't embrace AI use, students will just go back to free ChatGPT. And then they'll really not learn.
AI doesn't have to be the enemy, though! Studies have suggested that when still struggling with a problem first, using AI in studies has no detrimental effect and in some cases can be even better. In fact, it can make learning refreshing and fun in ways that were very hard to do before!
Here are some ideas on AI-complementary tutor moves
"Predict First"
Have students estimate or predict before using AI
Compare predictions with AI answers
Develop number sense and intuition Example: "What's your rough guess before we check?"
"Explain It Back"
Have students explain AI-generated answers in their own words
Ask "How would you teach this to a friend?"
Get them to identify the key steps or concepts Example: "I see UPbot solved this equation. Can you walk me through each step it took?"
"What If We Change..."
Modify the problem slightly
Ask students to predict how the answer would change
Help them understand patterns and relationships Example: "Now what if this number was negative instead of positive?"
"Find the Mistake"
Intentionally ask UPbot for multiple solutions
Have students compare and critique different approaches
Practice critical thinking by finding errors Example: "Let's ask UPbot to solve this two different ways. Which way makes more sense?"
"Build the Steps"
Ask students to outline the steps before checking AI
Compare their approach with AI's solution
Discuss different ways to reach the answer Example: "Before we check UPbot, what do you think our first step should be?"
"Why This Way?"
Question AI's method
Explore if there are simpler approaches
Discuss when different methods work best Example: "UPbot used this formula. When is this formula most useful?"
"Real World Connection"
Ask students to create real-world examples
Link AI solutions to practical applications
Make abstract concepts concrete Example: "Where might we use this kind of problem in real life?"
Are these practice pedagogically sound?
Yes, these strategies are solid and based on well-established educational principles, just adapted for AI. Here's why each one works:
"Predict First" develops estimation skills and number sense, which are especially important in an AI world where answers come easily.
"Explain It Back" is simply a version of the proven "teach to learn" method. When students have to articulate concepts, it reveals their actual understanding and reinforces learning.
"What If We Change" is about pattern recognition and transfer learning - both crucial skills. It moves beyond memorization to true comprehension.
"Find the Mistake" teaches critical thinking and helps students develop skepticism about AI answers, which is especially important now.
"Build the Steps" employs metacognition - thinking about thinking. Having students plan before checking AI helps them develop problem-solving strategies.
"Why This Way?" encourages deeper conceptual understanding rather than just following procedures.
"Real World Connection" helps with retention and motivation by making abstract concepts concrete.
The core principle behind all of these is: use AI as a tool to check work or generate examples, but keep the actual thinking and learning with the student. They're especially good because they:
Accept that students will use AI rather than fighting it
Turn AI use into a learning opportunity
Keep students actively engaged rather than passive
Build transferable skills