Exploring Learning and Teaching in the Age of AI

Textbooks have been the foundation of education for centuries. Carefully curated, peer-reviewed, and built over years of academic rigor, they have served generations of learners. But today, we live in a time when artificial intelligence (AI) can answer a student’s question faster than any index page can be flipped. AI can explain concepts, solve problems, quiz students, and even design customized lessons on demand. This reality raises a serious question: Is it time to stop using textbooks?

AI Has Already Taken Over Many Aspects of Academia Professors and researchers — myself included — have started using AI tools to create exams, discussion questions, and even detailed rubrics. But this doesn’t happen by magic. It requires thoughtful prompting: specifying the learning objective, the desired difficulty, the type of thinking skill to be measured. Done well, the results are impressively aligned with modern educational standards. If we can design a good test by asking AI the right way, can students also learn accounting (or any subject) simply by interacting with AI? Imagine this: Instead of reading Chapter 5 of a textbook, a student could ask, “Explain revenue recognition with examples for a beginner,” and within seconds, get a detailed, conversational explanation tailored exactly to their level. In theory, this should make learning easier than ever before.

But is it? The Challenge of Attention in a TikTok World The truth is, both teaching and learning have never been more challenging. Students today are digital natives, but they’re also part of what some call the “15-second generation” — conditioned by TikTok, YouTube Shorts, and Instagram Reels to process information in tiny, entertaining bursts. Deep learning — the kind of learning needed to truly master accounting, engineering, or medicine — requires time, focus, and patience. Can AI-driven microlearning replace the sustained engagement that textbooks traditionally demanded? Or will students, spoiled by instant answers, struggle even more to develop the critical thinking and problem-solving skills they need in the real world? Textbooks Are Inflexible — But Are They Necessary?

One undeniable reality is that textbooks often fail to meet students where they are. They are static, one-size-fits-all, and slow to adapt. AI, by contrast, can instantly tailor content to a student’s needs, interests, and learning pace. But textbooks provide structure. They map a coherent learning journey — building foundational knowledge, reinforcing skills, and scaffolding complex ideas in a deliberate, tested sequence. AI can generate content, but without careful guidance, the student might miss important steps. Without a structured path, it’s easy to feel like you’re learning — but not actually mastering anything.

So…

Should We Stop Using Textbooks?

Maybe the better question is not whether we should abandon textbooks, but how we should reimagine them.

• Could AI and textbooks coexist — textbooks providing the framework, and AI delivering personalized exploration within it?

• Should students be trained not just in subjects like accounting, but also in how to ask the right questions to AI — a new kind of digital literacy?

• Should professors focus less on being content providers and more on being learning coaches, helping students navigate this ocean of instant information? These are the conversations we need to have. A Call for Discussion If you are a student: • How do you feel about learning without textbooks?

• Do you find AI a better teacher — or do you get lost without clear structure? If you are a professor or researcher:

• How are you using AI in your own teaching or research?

• What are the risks and benefits you see in relying more on AI than traditional materials?

I don’t claim to have the final answer. But I do know this: The future of learning won’t look like the past. And it’s up to us — students, teachers, researchers — to shape it wisely. What do you think? Let’s start the conversation.

Read related article: Integrating AI in Research