AI in Education: How to Personalize Inquiry Learning Using AI Tools


AI has been a huge force in education for some time now, changing the way educators and students teach and learn. In our rapidly evolving educational landscape, teachers are constantly seeking new and creative ways to engage students and tailor instruction to meet individual needs. Some teachers use it to optimize their lesson planning and preparation, while others use it to identify areas for improvement. AI can also be incredibly beneficial in creating personalized learning in the inquiry classroom.

AI has infinite potential to revolutionize education by offering personalized learning experiences that cater to each student. This is especially powerful when combined with inquiry learning, where students actively participate in their education through questioning and exploration.

In this article, we’ll explore how AI can be used to personalize learning in the inquiry classroom in a multitude of different ways.


Understanding the power of AI in education

When people hear “artificial intelligence”, they sometimes associate it with “replacing humans”. Artificial intelligence in education is not about replacing teachers, but rather enhancing their capabilities. For example, automating tasks like data analysis, or providing insights into student learning patterns. AI-powered platforms can also provide teachers with access to vast libraries of educational content, including videos, simulations, and interactive activities. These resources can help create engaging learning experiences to complement in-class teaching.

Despite all the benefits AI can bring to education, most institutions do not have a formal strategy or policy regarding the use of AI. This signifies that while most people acknowledge the need for an AI strategy, they might lack the tools or clarity on how to implement one. In this case, it’s important to recognize that AI is still evolving, so a concrete strategy isn’t necessary right now. Instead, start small and implement policies that work, and build from there.

How AI can personalize learning

At the heart of personalized learning lies inquiry-based instruction, an approach that encourages students to ask questions, investigate, and construct their understanding of the world around them. AI complements inquiry learning by providing personalized recommendations for resources, activities, and assessments based on students’ inquiries. In turn, this helps to foster autonomy, critical thinking, and problem-solving skills. To learn more about developing soft skills in the classroom, check out our article about how inquiry learning is redefining schools in the 21st century. Here are a few ways AI can personalize learning in your classroom:

1. Helping to differentiate instruction

For teachers, AI can offer personalized lesson planning based on student data. This can help with differentiation, including making activities simpler or more challenging, depending on each students’ abilities.

Using a paraphrasing tool or switching the output to “simpler” or “more casual” can help simplify a passage and make it easier to understand.

Consider these scenarios:

  • Social studies project: AI can assess each students’ prior knowledge of Indigenous cultures and history. Based on this assessment, the platform delivers customized content, from introductory information for beginners, to in-depth for advanced learners. For example, begin a unit with a KWL chart, and summarize student learning into different groups based on knowledge level. Then, create a prompt that asks ChatGPT to provide an inquiry question to anchor each student’s project at their specific learning level.
  • Language arts / English writing: For students who struggle with writing, text-to-speech tools can assist them with reading difficulties. Using teacher or student prompts provides customizable tasks for students based on their reading or writing level. By scaffolding the writing process like this, text-to-speech AI tools help students progress with their reading and writing skills in a personalized way that meets them where they are.
  • Science lesson in biology: For a student who struggles with dense biology terminology, AI tools can help condense and simplify concepts. For example, using a paraphrasing tool or switching the output to “simpler” or “more casual” can help make a passage easier to understand. In this way, students can build their understanding at a slower pace to ensure they fully understand before moving onto a more complex concept.
  • Math extensions: In a math classroom, a student might grasp concepts quickly and require more difficult work to apply their skills. In this scenario, teachers input a request for a word problem or extension for the student to complete. For instance, “generate a word problem that involves quadratic equations and an ice cream shop. Express the word problem in two ways – one that is simpler and one that is more challenging”. Present the first word problem, then progress to the more challenging one if they can complete it successfully.

2. Becoming an equalizer in the classroom

AI promotes equity through its ability to offer real-time analytics and insights. For example, it can analyze data on student performance and monitor student engagement and learning behaviours. Additionally, AI can help assist teachers in their delivery methods by tracking the effectiveness of their teaching methods to see what works best. The benefits of personalization through AI have been well-documented in classrooms around the world.

By using a data-driven approach with AI’s assistance, teachers can:

  • Adjust the pace and difficulty of content based on student performance and engagement
  • Encourage students with learning difficulties to understand instructions and feel confident to fully participate
  • Remove barriers to learning that may not have been identified previously
Photo by Andrea De Santis on Unsplash

Natural Language Processing (NLP)

The use of Natural Language Processing tools allows for improvements in student writing and speech. NLP can analyze students’ written and spoken language to understand their comprehension levels and provide real-time feedback. A good example is an AI-powered writing tool that helps students improve their grammar and vocabulary by offering on-the-spot suggestions for improvements. Additionally, NLP can assist in the development of speech-to-text and text-to-speech applications, which are helpful for students with learning disabilities (such as dyslexia), or EAL students. This is a great starter guide for students interested in NLP and how to engineer the algorithms that allow this technology to work.

Implementing adaptive learning platforms

To be honest, teachers perform adaptive learning protocols everyday. For example, if a student finishes their work quickly, we respond by giving them a new, more challenging task to extend their skills. Similarly, if a student is struggling, we adapt by scaffolding the process for them, or providing guidance where needed. These are all examples of being adaptive and tailoring instructional content to student’s individual learning levels. This allows teachers to ensure that all students are engaged at an appropriate level of difficulty, thus promoting equitable opportunities in the classroom.

Suggested resources:

Although adaptive learning platforms and practices have been around for a long time, advances in artificial intelligence have resulted in more rigorous and personalized adaptations. An adaptive learning platform is a system that uses a student’s interaction with the system to create a unique learning path for them. In contrast with traditional “one-size-fits-all” approaches of the past, adaptive learning platforms provide specific and personalized learning for students. They rely on machine learning algorithms to assess student performance and modify the content and teaching approach.


3. Generating tailored inquiry questions

Sometimes the hardest part about beginning an inquiry unit is developing deep, high-quality inquiry questions with your students. If students haven’t been exposed to inquiry learning before, it can be a challenge to get them to understand the value of asking open-ended questions that have the potential for numerous answers.

Explore the topic

A good place to start teaching students about driving questions is to use provocations and invitations to stimulate interest in the topic. For example, if you want to begin an inquiry about skyscrapers and buildings, invite students to browse photos and blueprints of famous buildings. We’ve written about how to set up exciting learning provocations to make this process simple and fun, with four examples to try.

Once students have explored the topic or subject, encourage them to ask open-ended questions about what they’ve made or discovered by writing their questions down on whiteboards or sticky notes and add them to a wonder wall or Q-matrix (you can download a copy of a Q-matrix here). I sometimes refer to this as “question-storming”, where students simply write down any and all questions they have and stick them on a q-matrix. This way, they can pour out their curiosities and see what their peers are thinking about too.

Use AI to refine the questions

In some cases, students’ questions are too narrow. They focus on one specific question that will likely be answered in a matter of minutes. Sometimes their questions don’t meet the criteria for a “good” inquiry question because it’s one that can easily be searched. Other times, their question might be too “niche”, or focused on a sub-topic that doesn’t allow for expansion of thought.

On the other hand, students who get super excited about inquiry projects are likely to ask over-the-top questions that need to be narrowed down. For example, they might ask “How do robots work?” which in itself is a fair question. However, framing the question in a more narrow context allows students to still explore their original question, but the parameters for research are more manageable. When either of these instances happen, AI can be helpful to expand the scope of the question or narrow it down. Below are some prompts to use to accomplish this:

AI prompts to broaden the scope:

  • “Question” + broaden this inquiry question
  • Suggest ___ ways to expand this inquiry question: “Question”
  • How can this question – “Question” – be broadened for an inquiry project on ___?


AI prompts to narrow the scope:

  • “Question” + narrow the scope of this inquiry question
  • Suggest ___ ways to narrow down this inquiry question: “Question”
  • How can this question – “Question” – be narrowed down for an inquiry project on ___?

Key Takeaways:

(1) AI has been a huge force in education for some time now, changing the way educators and students teach and learn.

(2) AI in education is not about replacing teachers, but rather enhancing their capabilities.

(3) AI complements inquiry learning by providing personalized recommendations for resources, activities, and assessments based on students’ inquiries. It also helps narrow or broaden the scope of student questions.

(4) Although adaptive learning platforms and practices have been around for a long time, advances in AI have resulted in more rigorous and personalized adaptations.


Do you think AI has positively impacted education?
How have you utilized AI in your classroom?

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Cover image by Unsplash+ in collaboration with Getty Images

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