This series explores a rarely discussed strength of direct instruction: its power to motivate students. While critics often paint explicit teaching as boring or uninspiring, the truth is that its structure, pace, and design motivate kids better than any other system.
There is a certain romance in education about the idea of “Productive Struggle.” The notion goes something like this: if we want students to be like mathematicians, we must let them struggle like mathematicians. After all, isn’t wrestling with hard problems the essence of the discipline?
It sounds plausible until you remember that mathematicians are experts. Their ability to make progress on difficult problems is not a function of raw struggle but of the vast knowledge structures stored in long-term memory. As Sweller and colleagues explain in cognitive load theory, it is these schema that allow experts to bypass the limits of working memory and think productively about complex tasks. Novices, by contrast, lack such schema. Their working memory is easily overloaded, and so what can be “productive” for the expert becomes aimless and discouraging for the beginner (Sweller, Ayres, & Kalyuga, 2011).
This is consistent with the wider expertise literature. Chi (2006) found experts see deep structures, patterns, and relationships in problems because they have rich mental models stored in long-term memory. Novices typically see only surface features. Asking them to “think like experts” is to ask them to do the impossible.
Like the “Balanced” in Balanced Literacy, the “Productive” in Productive Struggle does most of the work. If the struggle leads to nowhere, we’re told that’s not Productive, and if a student happens to stumble onto the answer, that counts as the good kind of struggle. In this way, anything and everything can be folded into the term, which makes it unscientific and unfalsifiable. Education is littered with such labels—vague, elastic phrases that masquerade as wisdom. Far from elevating the craft, they actually de-professionalize it by replacing transparent, evidence-based practices with slogans.
Motivation Springs from Success
Perhaps the most puzzling claim is that struggle builds motivation. Anyone who has failed repeatedly at something difficult knows how it usually ends: with disengagement and quitting. Motivation doesn’t spring from failure, but from the feeling that your effort paid off, that you’re getting somewhere. That you can do it. This is supported by research on self-efficacy (Bandura, 1997). When students experience success, their belief in their ability grows, which in turn fuels further effort. By contrast, repeated failure erodes confidence, even if we label it “productive.”
Direct instruction engineers success, and in doing so, it builds the most durable and empowering form of motivation: the belief that hard work leads somewhere. If we want motivated students, we shouldn’t romanticize their frustration. We need to ensure their success.
Consider this video of *Pritesh Raichura teaching science through direct instruction. What stands out immediately is the precision of his delivery. He presents each step crisply, checking for understanding constantly, and moving briskly enough to keep every student engaged. The result is unmistakable: his students are succeeding. The energy in the room isn’t borne of struggle but of confidence. You can see it in the way they lean forward, eager for the next question. Their motivation is the natural byproduct of visible progress.
Motivation is not built on failure dressed up as “productive.” It is built on success, on the sense that knowledge opens doors that were once closed. The point here isn’t that students should never be challenged. It’s that challenges must be pitched at the right level, supported by the right scaffolds, and taught with precision. That is what direct instruction delivers: the momentum of accomplishment and mastery.
References
*Pritesh is featured in the Steplab documentary. Interested in joining the North American training program for Steplab? Registration and info here.
- Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W. H. Freeman.
- Chi, M. T. H. (2006). Two approaches to the study of experts’ characteristics. In K. A. Ericsson, N. Charness, P. Feltovich, & R. Hoffman (Eds.), The Cambridge handbook of expertise and expert performance (pp. 21–30). Cambridge: Cambridge University Press.
- Sweller, J., Ayres, P., & Kalyuga, S. (2011). Cognitive load theory. New York: Springer.
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