Maybe They Aren’t Apathetic: Rethinking Student Resistance to Difficult Learning

Fifteen years ago, telling a class that we were going to play a game was almost guaranteed to change the energy in the room. Students got excited. They wanted to figure it out, compete, experiment, and keep going when something did not work. So when I began integrating more games and simulations into my Business and Computer Science classes again, I expected some version of that same reaction.

Instead, I started hearing something different: “This is hard.” “This is boring.” “I don’t get it.” “Do we have to do this?” Sometimes the reaction was even more striking. A student would reach a difficult section of the game and simply stop. They would not ask for help, try another strategy, or become disruptive. They would just sit in front of the monitor and stare at it.

That behavior has made me rethink something teachers talk about constantly: student apathy. I am beginning to wonder whether some of what we label as apathy is actually something different. Perhaps some students are not apathetic about learning at all. Perhaps they have a strong aversion to sustained cognitive effort, especially when a task requires multiple steps, uncertainty, experimentation, and the possibility of failure.

Games happen to be where I noticed it most clearly, but this is not really an article about games.

The same thing can happen in any classroom where students are asked to complete a complex, authentic task. A colleague of mine teaches business students who design T-shirts, develop a marketing effort around them, and actually sell the products. That sounds engaging, and it certainly can be. But think about what the students are really being asked to do. They have to create a product, make design decisions, think about an audience, communicate a message, consider costs, market the product, respond to feedback, and ultimately see whether people are willing to buy what they created.

There is no worksheet that tells them exactly what the correct T-shirt should look like.

There is no answer key for the perfect marketing strategy.

That is the point.

Whether the activity is a game, a business simulation, an engineering challenge, a research project, a coding problem, or a real entrepreneurial experience, complex learning asks students to do something very different from completing a sequence of predetermined tasks. It gives them an objective while leaving at least part of the path unresolved.

That is where genuine problem solving begins.

When the Path Is Not Obvious

In my own classes, I use Pizza Connection 3, a restaurant management simulation, and while True: learn(), a game built around computational puzzles. Both appear to be games on the surface, but cognitively they function as complex problem-solving environments.

Students are not simply following instructions. They have to determine what information matters, decide what to try, evaluate the result, and revise their approach when something fails. In Pizza Connection 3, a restaurant can lose money for several different reasons. In while True: learn(), students may have several tools available but no obvious indication of how they should be combined.

The game gives them the goal. It does not always give them the path.

A more traditional assignment often works differently. The teacher demonstrates the process, the student practices it, and each new problem resembles the previous one closely enough that the next step is usually visible. That kind of practice is useful and necessary, but it can also allow students to complete substantial amounts of work without spending much time in the uncomfortable state of genuinely not knowing what to do next.

Complex tasks expose that state immediately.

A student working on a real marketing campaign might ask, “Why isn’t anyone buying this?” A programmer may wonder why the code behaves correctly in one situation and fails in another. A student running a simulated restaurant may see sales declining without knowing whether the problem is price, staffing, customer preferences, or location.

At that moment, the student has crossed from completing work into solving a problem.

For some students, that appears to be exactly where they withdraw.

Maybe “Apathy” Is the Wrong Diagnosis

Psychological research helps explain why this may happen. Cognitive effort is not experienced as neutral. A 2024 meta-analysis published in Psychological Bulletin examined 170 studies and found a strong relationship between mental effort and negative affect. Put simply, difficult thinking frequently feels unpleasant.

Other research on cognitive effort discounting shows that people tend to value an activity less as the mental effort required to complete it increases. Similar effects have been observed in children. That raises an important possibility for teachers: weak engagement with a difficult task does not necessarily mean the student lacks the ability to complete it.

There is a meaningful distinction between two statements.

Apathy is essentially, “I do not care whether I succeed.”

Cognitive effort avoidance may be closer to, “I want to succeed, but I do not want to endure this much uncertainty and mental effort to get there.”

From across the classroom, those students can look remarkably similar.

A student reaches a difficult problem, the next move becomes unclear, and the activity stops. The mouse stops moving. The pencil stops. The student no longer experiments. They may not even ask for assistance.

That student may not be unwilling to work in general. They may simply not know how to remain cognitively engaged when success is no longer obvious.

Experienced problem solvers respond to uncertainty by testing something. They think, “I do not know what works yet, so I need to try something and see what happens.” A struggling student may instead think, “I do not know the correct answer, so I cannot continue.”

Complex problem solving requires the first mindset. It requires students to act without knowing in advance that the action will be correct and to treat failed attempts as information rather than as evidence that they cannot solve the problem.

Why Student Feedback Can Mislead Us

This creates a difficult problem for teachers because we are constantly gathering feedback from students, both formally and informally. We notice whether students appear engaged. We hear whether they enjoyed the activity. We see whether they complain. We watch the energy in the room.

Those signals matter, but they are not always reliable measures of learning.

One of the clearest demonstrations of this comes from research by Louis Deslauriers and colleagues at Harvard. Students were randomly assigned to learn the same physics content through either active instruction or highly polished passive instruction. The students in the active-learning classrooms learned more, but they reported feeling as though they had learned less.

The researchers concluded that students can mistake increased cognitive effort for ineffective instruction.

That finding should make teachers cautious.

A worksheet is relatively easy to measure. I can count how many questions a student completed. I can grade the answers. I can calculate a percentage. The product of the lesson is visible.

Cognitive effort is much harder to measure.

How do I measure the moment when a student realizes that their first marketing idea is not working and changes direction? How do I quantify the thinking required to identify why a simulated business is failing? How do I score the ten minutes a student spends testing possibilities before finally finding the structure of a difficult coding solution?

Those moments may represent some of the most important learning occurring in the classroom, yet they do not necessarily produce an immediately visible artifact.

Worse, they may actually produce negative student feedback.

“This is confusing.”

“This is too hard.”

“I liked the worksheet better.”

For a teacher, that creates an uncomfortable possibility: the lesson requiring the most meaningful thinking may feel less successful than the lesson producing the neatest stack of completed papers.

This does not mean teachers should ignore student feedback. It means we have to interpret it carefully.

Student enjoyment is not the same thing as cognitive engagement. Visible compliance is not the same thing as thinking. Frustration is not automatically evidence of good instruction, but neither is it automatically evidence of bad instruction.

The Danger of Rescuing Students From the Thinking

This becomes especially important when students struggle.

A student becomes frustrated, and the teacher naturally wants to help. We walk over and show them what to click, what to change, what equation to use, or what their next step should be. The student starts moving again, so it appears that the problem has been solved.

But sometimes we have restored activity without restoring cognition.

Research on productive failure and desirable difficulties suggests that students can benefit from struggling with challenging problems when those problems are accessible and support is appropriately calibrated. Productive struggle does not mean leaving students hopelessly confused. It means providing enough support to help them continue without taking ownership of the reasoning away from them.

That distinction matters.

If a student cannot find a menu because the software interface is confusing, help them. If the assignment directions are unclear, clarify them. If prerequisite knowledge is missing, teach it. Those are barriers that interfere with learning.

But if a student understands the objective, knows how the tools work, and simply does not know which strategy will succeed, that uncertainty may be the learning.

My shorthand has become: remove unnecessary friction, but preserve cognitive friction.

In the T-shirt project, for example, a teacher may need to explain how the equipment works, how costs are calculated, or how an order is processed. But deciding which design will appeal to customers or how to market the product should remain with the students. That is the intellectual work the activity was designed to create.

Likewise, if a student playing a business simulation does not know where a particular menu is located, I can show them. If they do not know why their business is losing money, I should be much more cautious about supplying the answer.

Instead, I can ask, “What have you already tried?” “What do you know is working?” “What variable could you change?” or “What is one reasonable thing you could test?”

The objective is not to withhold help. The objective is to make the next thinking move manageable while keeping the thinking with the student.

Teachers Have to Tolerate Some Discomfort Too

There is another side to productive struggle that receives less attention: it requires persistence from the teacher.

When students complain about a cognitively demanding lesson, the teacher experiences pressure as well. We planned the activity. We want it to work. We want students to enjoy our class. When several students tell us that an assignment is boring, confusing, or too difficult, it is natural to wonder whether we made a mistake.

Sometimes we did.

But sometimes the students are simply experiencing what sustained thinking feels like.

That means teachers have to diagnose the source of the discomfort rather than automatically eliminate it.

If the task is poorly designed, redesign it. If students are overwhelmed, scaffold it. If the instructions are unclear, fix them. But if the difficulty comes from having to make decisions, test ideas, reconsider assumptions, and persist when the answer is not immediately apparent, reducing that difficulty may remove the very learning we were trying to create.

The goal is not struggle for the sake of struggle. The goal is successful struggle.

A student encounters something difficult, does not immediately know what to do, tries something, discovers that it does not work, changes direction, and eventually solves the problem.

That final moment matters.

A student who completes a difficult problem has learned something different from a student who successfully followed a demonstrated procedure. They now have evidence that they can enter a situation without knowing the answer and still find a way forward.

That kind of confidence cannot simply be explained to students.

They have to experience it.

Maybe We Need to Rethink What We Call Apathy

I still believe student apathy exists. Some students genuinely do not care about an assignment or learning objective.

But I am becoming much more cautious about reaching that conclusion too quickly.

The student staring at a difficult puzzle, freezing during an open-ended project, or failing to make the next decision in a complex task may not be saying, “I do not care.”

They may be saying, “I do not know what to do next, and I do not know how to operate in that state.”

That is something schools can teach.

We can teach students how to break large problems into smaller ones, test hypotheses, interpret unsuccessful attempts, ask productive questions, and keep making reasonable moves when the solution is not obvious. We can provide scaffolds without immediately providing solutions. Most importantly, we can give students repeated opportunities to experience genuine success at something that initially felt beyond them.

Perhaps one of the most important things we can teach a student is that not knowing what to do next does not mean the work is over. It means the problem-solving portion of the work has begun.

Games happened to make this visible to me. Another teacher may see it during a laboratory investigation, an engineering project, a research assignment, a coding challenge, a student-run business, or an authentic marketing campaign.

The instructional medium is not really the point.

The point is that when we ask students to use the full breadth of their thinking—to plan, decide, analyze, test, revise, and persist—the experience may not always look like enthusiastic engagement from the outside.

Sometimes it looks messy.

Sometimes students complain.

Sometimes they stop.

And sometimes the teacher has to resist the temptation to interpret that discomfort as proof that the lesson failed.

The worksheet may be easier to grade.

The complex task may be harder to measure.

But somewhere inside that difficult, uncertain work may be exactly the kind of thinking we hoped school would teach.

Selected Research

David, L., Vassena, E., & Bijleveld, E. (2024). The unpleasantness of thinking: A meta-analytic review of the association between mental effort and negative affect. Psychological Bulletin, 150(9), 1070–1093.

Deslauriers, L., McCarty, L. S., Miller, K., Callaghan, K., & Kestin, G. (2019). Measuring actual learning versus feeling of learning in response to being actively engaged in the classroom. Proceedings of the National Academy of Sciences, 116(39), 19251–19257.

Freeman, S., Eddy, S. L., McDonough, M., et al. (2014). Active learning increases student performance in science, engineering, and mathematics. Proceedings of the National Academy of Sciences, 111(23), 8410–8415.

Chase, C. C., Malkiewich, L. J., Lee, A., Slater, S., Choi, A., & Xing, C. (2021). Can typical game features have unintended consequences? A study of players’ learning and reactions to challenge and failure in an educational programming game. British Journal of Educational Technology, 52(1), 57–74.

de Bruin, A. B. H., Biwer, F., Baars, M., Wijnia, L., Paas, F., & de Bruin, A. (2023). Worth the effort: The Start and Stick to Desirable Difficulties framework. Educational Psychology Review, 35.