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At the end of this section, you should be able to reflect on your own learning habits and develop approaches to use GenAI intentionally and effectively. |
Now that you’ve seen how intentional learning builds on active learning and moves beyond passive consumption, it’s time to look inward.
GenAI can be a powerful and personalized learning tool, but only when used purposefully. It’s up to you to pause, reflect, and take ownership of how you engage with it.
Practicing double-loop learning means going beyond quick, surface-level answers. It involves examining the reasoning behind your choices and asking questions like:
The goal isn’t to avoid GenAI; it’s to develop strategies that keep you in control of your learning while still benefiting from what GenAI can offer.
Begin by reflecting on your learning habits. This short questionnaire will help you identify your patterns of GenAI use, spot risks of overreliance, and adopt approaches that strengthen critical thinking, reflection, and deep learning.
As learning with GenAI becomes more prevalent, the ability to think critically has never been more important.
| Critical thinking goes beyond recalling facts or making decisions based on intuition or anecdotal evidence. It is an intentional, reflective process of analyzing, evaluating, and synthesizing information to make reasoned judgments or solve problems 1. In practice, this means digging deeper - questioning assumptions, identifying patterns, and considering multiple viewpoints - making judgments and solving problems based on sound reasoning. |
For example, when writing an essay on climate change, it's not enough to simply present facts. Thinking critically means sorting through scientific data, political viewpoints, and ethical considerations, then weaving them together into a clear, well-reasoned stance.
Used thoughtfully, GenAI can extend your critical thinking in two key ways:
Pushing AI beyond surface-level tasks: Asking it to reason, explain, or explore different perspectives helps you practice deeper skills like analysis, evaluation, and synthesis, while staying in control of your learning.
Approaching AI with curiosity and healthy skepticism: Interrogating the information it provides moves you beyond passive consumption toward deeper understanding. For example, instead of copying an AI-generated answer, you might ask, “What assumptions is this response based on?” or “What would an opposing argument say?”
Critical thinking is the foundation of deep learning. It helps you move beyond surface-level understanding by challenging assumptions, engaging diverse perspectives, and making meaningful connections.
One effective way to strengthen your critical thinking when using GenAI is to level up your prompts using Bloom’s Taxonomy, a framework that organizes cognitive skills from basic recall to higher-level skills like analysis, evaluation, and creation.
Instead of asking GenAI to define or summarize, use Bloom’s action verbs to encourage more complex thinking. Try prompts that ask GenAI to:
Example:
Instead of: “Define photosynthesis”
Try: “Compare two theories of photosynthesis and evaluate which explains plant adaptation better.”
This strategy results in deeper, more meaningful responses and keeps you actively involved in the thinking process, as you read, question, and refine what the AI provides.
In short, if you're using GenAI to learn, adopt a probing mindset—one that continually questions, explores, and reflects.
Click on each hotspot below to explore how you can use GenAI to strengthen your thinking across different levels of learning, from remembering to creating. By prompting GenAI to analyze, evaluate, or synthesize, you’ll receive more meaningful responses and train yourself to think more critically about them.
TIP: The risk of overreliance on GenAI is highest at the lower levels of Bloom’s Taxonomy, where tasks tend to be more passive. At the higher levels, deeper, more meaningful engagement and reflection are required. Choosing your verbs wisely helps you move beyond surface learning and develop stronger critical thinking skills.
Source: This Bloom’s Image by Rawia Inaim, based on Bloom's Taxonomy of Learning, is licensed under a CC BY-SA (Attribution ShareAlike) license
These strategies will help you offload cognitive tasks in ways that support, rather than undermine, your learning when using GenAI.
Clearly define what you want to learn or remember, whether it’s understanding a concept deeply or preparing for an exam. Setting goals helps you engage meaningfully with GenAI responses. For example, you might ask GenAI to explain a concept, then summarize it in your own words to reinforce memory and understanding.
It is fine to let GenAI handle lower-level tasks like organizing information or generating outlines, as long as you stay focused on the higher-level thinking. Use these tools to free up mental space so you can analyze, evaluate, and create. Avoid relying on GenAI in ways that limit your independent thinking or prevent you from grappling with complex ideas and forming your own judgments.
Don't copy and past GenAI responses directly into your work. Analyse and evaluate what it produces. Compare AI-generated content with course materials or credible sources, highlight what is useful, and correct errors and biases. Engage actively with GenAI outputs and, if you are allowed to use GenAI in you work, be transparent about how you used it and where. This maintains trust and upholds academic integrity.
Test yourself periodically. Ask, “What do I remember without asking AI?” Retrieval practice strengthens memory, while reflection helps you identify what you’ve truly learned versus what you’ve simply consumed.
GenAI can handle surface-level tasks, but do not outsource the thinking that matters most. Ask yourself, "What parts of this task should I do myself to learn deeply?" Keep the essential mental work, like reflecting, reasoning, and making decisions, in your own hands.
1. Gerlich, M. (2025). AI Tools in Society: Impacts on Cognitive Offloading and the Future of Critical Thinking. Societies, 15(1), 6. https://doi.org/10.3390/soc15010006
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