Reports say AI hinders learning, but you can’t separate tech from its use.
Some recent reports argue that generative AI tools like ChatGPT, Claude, and Gemini actively harm student learning. Critics claim that AI fosters over-reliance, diminishes critical thinking, and reduces self-regulated learning. One commentator concludes, “Current research overwhelmingly suggests that generic Gen AI tools do not just fail to advance human learning—they often actively hinder it.”
This argument is misguided. Researchers repeatedly fall into the trap of attempting to separate technology from the user. The real issue isn’t AI itself—most students haven’t been taught how to use it for learning. Too often, these reports portray AI chatbots as passive information dispensers.
AI chatbots are interactive learning partners that encourage students to refine their thinking, engage in productive dialogue, and deepen their understanding of curriculum topics. Instead of simply providing answers, AI chatbots can guide students through discovery, prompting them to explain their reasoning, apply concepts to new scenarios, and critique their thinking.
The real problem is that few schools provide explicit training on using AI tools for inquiry-based learning, constructive dialogue, and understanding-building. Without structured instruction, students default to superficial AI use—using it as an answering machine—because that’s all they know. If we want AI to enhance rather than hinder student learning, we must teach students how to use it well.
AI as a Tool for Active Inquiry and Productive Dialogue
Gen AI is not just a content generator—it’s an interactive system capable of guiding students through complex reasoning, questioning assumptions, and prompting metacognitive reflection. Borrowing an example from my book, a student in an algebra class studying exponential growth could engage in a structured dialogue with an AI chatbot to enhance their understanding of the concept.
They might ask for real-world examples of exponential growth, such as compound interest, population growth, or the spread of a virus. A student might also ask the AI to explain exponential growth using metaphors or similes to solidify their grasp of the concept. The AI might frame exponential growth as “a rumor spreading in a school, doubling in reach each time it’s shared.” These metaphorical explanations provide an accessible way for students to internalize complex mathematical ideas by linking them to familiar, real-world phenomena.
In addition to these strategies, students can enhance their learning by engaging AI in multi-modal interactions. For instance, they could ask the AI to generate a diagram or graph to visualize the steep curve of exponential growth compared to the more gradual increase of linear growth. Seeing a visual representation of these functions can help students connect abstract mathematical principles to concrete images, reinforcing their understanding of how exponential patterns differ from other forms of change.
Additionally, students can use AI to explore different applications of exponential growth across diverse fields. For example, they might ask how the principle applies to physics (such as radioactive decay), economics (inflation rates), or computer science (algorithmic complexity and data storage growth). Imagine students now understand the connection between mathematical concepts and different disciplines. They develop an interdisciplinary perspective and a deeper appreciation for the real-world significance of what they are learning.
AI can also serve as an interactive tutor for problem-solving by providing feedback on a student’s initial approach before they reach a final solution. Rather than simply asking for an answer, students can present their reasoning step-by-step, prompting the AI to identify errors, suggest alternative methods, or highlight areas where additional clarification is needed. This kind of dialogue can mirror how a teacher might guide students through problem-solving, helping them build confidence in their ability to analyze and refine their work.
If students engage AI in varied and dynamic ways, they transform AI use into an interactive, exploratory process that deepens comprehension, encourages curiosity, and strengthens problem-solving skills. AI becomes a partner in intellectual inquiry, capable of guiding students through complex thought processes in a way that adapts to their learning needs.
The Current Lack of AI Guidance in Schools is the Real Problem
National studies repeatedly indicate that most educators have not received formal training in AI pedagogy. Teachers are unsure how to integrate AI into student activities, and without guidance, many schools default to either banning AI outright or pretending it doesn’t exist. Both approaches fail students. Banning AI does not stop students from using it; it only forces them to use it in unregulated and unexamined ways.
Meanwhile, unguided AI use leads to students using AI superficially—such as copying answers without understanding the underlying concepts.
Take this recent report on the impact of large language models on student learning outcomes. It discloses that students were using LLMs without specific, formal instructor guidance. The result? Some students relied heavily on AI for critical thinking. Is anyone surprised? Are students expected to use LLMs effectively for learning without any guidance from educators?
Cognitive Effort Is Not Removed—It’s Redirected
One of the most common criticisms of AI is that it reduces cognitive effort, making learning too easy. However, cognitive offloading is not inherently bad; it depends on how AI is used.
Remember when critics feared students would lose basic arithmetic skills if calculators were introduced in classrooms? Over time, it became clear that calculators freed up cognitive load, allowing students to focus on higher-level problem-solving. AI can operate similarly. Teachers can shift attention away from routine tasks and toward higher-order thinking skills, such as analysis, synthesis, and evaluation.
For example, students in a biology class might be asked to design an experiment to test the effects of temperature on enzyme activity. Instead of manually looking up experimental designs, students could use AI to generate a range of possible experimental setups, outlining different methodologies, variables, and control conditions.
In this case, the AI is a starting point for deeper inquiry. Students must then critically evaluate the proposed designs, considering factors such as feasibility, ethical concerns, and potential sources of error. They might adjust the AI-generated setup by refining measurement techniques, altering sample sizes, or improving controls to ensure reliable results.
The genuine concern should not be whether AI makes knowledge consumption too easy but whether students are being taught how to use AI in a way that enhances their cognitive development.
Recommendations for Effective AI Integration in Schools
If AI is to be a tool for deep learning, schools must take responsibility for guiding its use. This means developing explicit AI literacy curricula that teach students how to critically evaluate AI-generated content, engage in structured AI dialogues, and use AI as a learning partner rather than an answer machine.
Teachers must also receive professional development on effective AI pedagogy. Educators need training on how to structure AI-enhanced learning experiences that promote inquiry, creativity, and critical thinking. AI should not replace traditional teaching but rather serve as a scaffolding tool that helps students develop their own ideas and problem-solving skills.
Additionally, AI should be integrated into classroom discourse rather than treated as an isolated tool. In discussions, students can be asked to generate AI responses, analyze them for biases or inaccuracies, and refine their perspectives based on their evaluations. When AI is positioned as a thinking partner rather than a source of unquestioned truth, students learn to interact with it in a way that strengthens their intellectual autonomy.
Conclusion
It’s time to frame AI as a powerful vehicle for intellectual exploration. Yet, without guidance, students don’t know how to navigate it productively. If we fail to guide students on using AI critically, responsibly, and effectively, we risk allowing AI to become a crutch rather than a tool for growth. However, if schools take an active role in AI literacy, integrating structured AI interactions into curricula, AI has the potential to deepen learning rather than diminish it.
About the author
Find more AI tools, views, and how-to’s at tomdaccord.com.
A former high school teacher and edtech CEO, Tom Daccord is the creator of the popular “Tom’s Takes: AI Tools & Views” website and the author of the newly published book AI Tools & Uses: A Practical Guide for Teachers. Tom is our K12 Contributing Editor.
This article is republished with permission from the author, Tom Daccord. It was initially published on his Substack site, “Tom’s Takes: AI Tools & Views.”
