How Do We Learn in the Digital and AI Era?

‍By Timothy Godlove, Ph.D.
Founder & Editor, Long View Review

‍We have never had greater access to information—or easier access to answers.

‍A student sitting at a kitchen table can search millions of books and articles, watch lectures from universities around the world, collaborate with classmates hundreds of miles away, and ask artificial intelligence to explain a difficult concept in seconds—an extraordinary development.

But having more information does not necessarily mean we are learning more. And having an answer does not necessarily mean we understand it.

‍That is one of the defining educational challenges of the digital and AI era.

‍From Finding Information to Understanding It

For much of history, education operated in an environment of information scarcity. Books, experts, libraries, and educational institutions provided access to knowledge that could otherwise be difficult to obtain.

‍Today, the problem is often the opposite.

‍We live in an environment of information abundance and attention scarcity.

‍Search engines can provide thousands of sources. Social media continuously delivers information and opinion. Generative AI can produce an immediate and remarkably polished response to almost any question.

‍The challenge is increasingly not simply finding information. It is determining what deserves our attention, deciding what is credible, understanding what it means, connecting it with what we already know, and deciding what to do with it.

‍Those are learning skills.

A Simple Framework for Learning

One way to think about learning in this environment is through five connected activities:

‍Read → Think → Write → Communicate → Learn

‍Read. Engage carefully with ideas, evidence, data, arguments, and different perspectives.

‍Think. Question what you encounter. Distinguish evidence from assertion, recognize assumptions, consider alternatives, and resist accepting the first plausible answer.

Write. Put your thinking into words. Writing does more than communicate what we know; it often reveals what we understand—and what we do not.

‍Communicate. Test ideas through discussion, questions, explanation, listening, disagreement, and collaboration.

Learn. Reflect on the process. Connect new knowledge with what you already know and be willing to revise your understanding when better evidence emerges.

‍These activities are not necessarily a straight line. We may read something, write about it, discover a weakness in our reasoning, return to the source, discuss it with someone else, reconsider our assumptions, and write again.

‍That process is learning.

‍Why Critical Thinking Matters More Now

At the center of this process is critical thinking.

In an environment where information and answers can be produced almost instantly, students need more than the ability to locate information. They need to evaluate claims, examine evidence, recognize assumptions, compare competing explanations, and determine what deserves to be believed.

‍Critical thinking is therefore not simply another academic skill. It is part of what allows learners to remain intellectually responsible for what they accept, reject, and ultimately understand.

Recent research on generative AI makes that responsibility especially important. Li et al. (2026), in a systematic review of 67 empirical studies conducted between 2022 and 2025, found that ChatGPT could support critical and creative thinking when it was embedded within structured, inquiry-oriented learning environments emphasizing activities such as metacognitive regulation and argumentative reasoning. The same review found greater risks of cognitive dependence and diminished higher-order engagement when AI use was passive or insufficiently structured.

The important question, then, may not simply be whether students use AI. It is what intellectual work they continue to perform while using it.

‍ The Risk of Cognitive Offloading

‍Cognitive offloading occurs when we transfer some of our mental work to an external tool. That is not inherently harmful. Human beings have long used books, notes, calculators, computers, search engines, and other technologies to extend what they can accomplish.

‍ The problem arises when a tool begins performing the very cognitive activity the learner needs to develop.

‍Recent studies give us reason to pay attention to this distinction. Tian and Zhang (2025), in a study of 580 university students, found that greater dependence on AI was associated with lower levels of critical thinking, with cognitive fatigue partially mediating that relationship. Gerlich (2025), in research involving 666 participants, similarly reported a negative relationship between frequent AI-tool use and critical-thinking ability, with cognitive offloading playing an important mediating role.

‍These studies identify associations rather than establishing that AI use itself causes weaker critical thinking. Nevertheless, they highlight an educational risk: technology that makes intellectual work easier can also make it easier to avoid practicing that intellectual work.

‍None of this is entirely new. Every major learning technology, from the printing press to the calculator to the search engine, has prompted concerns about weakening thinking, and those concerns have not always aged well. Offloading routine work has often freed attention for more demanding thinking rather than replacing it.

‍What may be different about generative AI is the breadth of cognitive work it can perform on request—not simply retrieving information, but explaining ideas, constructing arguments, summarizing evidence, and synthesizing information.

‍ That is precisely why the instructional-design findings matter more than the technology itself.

‍Other recent research reinforces the importance of how AI is integrated into learning. Guo et al. (2026), in a systematic review of 65 empirical studies, found evidence that appropriately designed ChatGPT use can support analytical, interpretive, reasoning, and self-regulatory skills. At the same time, the authors found less consistent evidence that AI use develops deeper critical-thinking dispositions such as truth-seeking, openness, and systematic thinking.

‍That distinction matters. Education should develop not only the ability to think critically, but also the willingness and habit to do so.

‍This leads to a principle that should guide learning in the digital and AI era:

‍Use technology to extend your thinking—not to avoid thinking.

‍Where Does AI Fit?

Artificial intelligence can participate in almost every part of the learning process.

‍AI can help us understand a difficult passage. It can suggest questions, compare arguments, explain unfamiliar concepts, generate practice exercises, critique writing, organize ideas, or present a competing perspective.

‍Used thoughtfully, AI can become a powerful learning partner.

‍But there is an important distinction between asking:

‍Did AI help me learn this?

and

‍Did AI do this for me?

‍The difference matters.

Imagine a student—call her Maya—struggling to understand an argument in an assigned reading for a college course.

Maya might ask AI to summarize the reading and then submit that summary without carefully reading or evaluating the original work. The assignment may be completed, but much of the intellectual work has been outsourced.

‍Or Maya could read the material first, identify what is confusing, ask AI to explain that specific concept, compare the explanation with the original source, question the AI's interpretation, and then write an explanation in her own words.

‍The same technology is involved—but the learning process is very different.

‍AI Should Challenge Thinking, Not Replace It

‍Perhaps one of the most valuable uses of AI in education will not be asking it for answers.

It may be asking AI to challenge our answers.

‍Why might my argument be wrong?

‍What evidence contradicts my position?

‍What assumption am I making?

‍What would someone who disagrees with me say?

‍What information should I verify?

What have I overlooked?

‍Used this way, AI becomes less of an answer machine and more of an intellectual sparring partner.

‍The student still has to evaluate the response.

‍The student still has to verify the evidence.

‍The student still has to decide.

‍And the student still has to understand.

‍Learning Still Requires the Learner

The tools of education will continue to change.

‍Search engines changed how we find information. Online education changed where learning can occur. Generative AI is changing how we interact with knowledge. Agentic AI may increasingly perform complex intellectual tasks on our behalf.

‍Education should not pretend these technologies do not exist.

Nor should education simply surrender intellectual work to them.

Instead, we need to teach students how to work with increasingly powerful technologies while preserving the human capabilities those technologies are supposed to enhance.

That brings us back to a deceptively simple process:

‍Read.

Think.

Write.

‍Communicate.

‍Learn.

Technology can participate in every step.

‍But responsibility for learning ultimately remains with the learner.

Use technology to extend your thinking—not to avoid thinking.

Technology can provide information.

AI can provide answers.

Education begins when we learn what to do with them.

This essay previews an idea I am developing more fully in a forthcoming book on learning in the digital and AI era.

‍References

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

‍Guo, Y., Huang, L., Zhang, C., Li, Q., & Chen, M. (2026). ChatGPT in education: A systematic review of its impact on critical thinking skills and dispositions. Thinking Skills and Creativity, 60, 102106. https://doi.org/10.1016/j.tsc.2025.102106

Li, C., Cui, H., & Hagedorn, L. S. (2026). The cognitive impact of ChatGPT in higher education: A systematic review of critical and creative thinking outcomes. Computers and Education: Artificial Intelligence, 10, 100571. https://doi.org/10.1016/j.caeai.2026.100571

Tian, J., & Zhang, R. (2025). Learners' AI dependence and critical thinking: The psychological mechanism of fatigue and the social buffering role of AI literacy. Acta Psychologica, 260, 105725. https://doi.org/10.1016/j.actpsy.2025.105725

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