The Cognitive Corner

Is Disciplinary Knowledge All You Need to Be a Good Teacher? 

In a recent Chronicle of Higher Education article, philosophy professor Paul Schofield discusses the appearance of a relatively new trend in post-secondary institutions called teaching-and-learning centers. The core argument Schofield asserts is that “evidence-based” pedagogy is often unreliable, that what counts as effective teaching varies by discipline, and that subject-matter experts—not generalists—are the real teaching experts. 

While Schofield’s argument is aimed at post-secondary institutions, several of his core claims warrant closer scrutiny. Firstly, Schofield’s claim that there are no general features of effective teaching collapses under even basic evidence from cognitive science. Decades of research on how people learn show that, across subjects, some principles show up again and again as constraints on what works for human learning. I’ve seen this repeatedly. Across classrooms and content areas, many of the same instructional challenges emerge not because subjects are the same, but because learners generally benefit from similar instructional models. These include clarity of explanation and modeling, sequencing knowledge from simple to more complex, attention to prior knowledge, guided practice before independence, frequent checking for understanding, and feedback that helps students improve (Sweller, 1988; 2011; Rosenshine, 2012; Ausubel, 1968). Because these are characteristics of how people learn, they are not subject specific. Novices in any domain benefit from structured guidance, while unstructured discovery tends to overload working memory (Kirschner et al., 2006). While there may be no such thing as generic good teaching in its full expression—there absolutely are general principles that constrain what good teaching can be. 

One of the most important points he makes throughout the article is that teaching practices ought to be embedded in discipline-specific practices, to avoid low-value activities that lack instructional depth (as he mentions—games or vague ‘engagement’ strategies). This, of course, is a point that I don’t think many would dispute, though perhaps not for the reasons Schofield would propose. Disciplinary knowledge matters in teaching not because it guarantees expertise, but because it allows teachers to interpret and respond to student thinking in real time. Teachers with deep content knowledge can diagnose misconceptions precisely, anticipate where students will struggle, and adjust explanations on the fly. This is fundamentally different from simply “knowing a lot.” Without such knowledge, instruction lacks precision. But without attention to how students learn, that same expertise can obscure understanding as easily as it supports it. Left unchecked, disciplinary expertise can produce worse instruction by obscuring what students don’t yet understand

Another point Schofield seems to miss is that even if teaching is discipline-specific, it is not discipline-exclusive. Schofield’s dismissal of general teaching principles overlooks a basic reality: students must be able to learn what is taught before they can apply it. This is precisely where expertise alone can fall short. For one thing, experts are often bad at seeing what novices don’t know. For example, I’ve seen this most clearly when highly knowledgeable teachers move too quickly through material, assuming connections that students simply haven’t built yet. In cognitive science, this is often called the curse of knowledge (Hinds, 1999). Once you understand something deeply, it becomes hard to remember what it’s like not to understand it. Experts tend to compress knowledge into chunks and skip steps that feel “obvious” to them but are invisible to learners (Nathan & Koedinger, 2000). There is strong evidence that this is widespread—particularly in higher ed. Experts often overestimate student understanding and readiness, and research shows that perceptions of learning during lectures can diverge significantly from actual learning (Deslauriers et al., 2019). We tend to think novices can’t and don’t exist in post-secondary institutions, but the reality is that novices can and do exist, even in post-secondary, when content is new or unfamiliar to them (Sweller, 1988). Research consistently shows that novices require explicit guidance and structured explanations, not just exposure to expert thinking. 

While Schofield’s central argument—that teaching is deeply tied to disciplinary knowledge—is laudable, he underplays that expertise includes knowing how to make a subject learnable. While he isn’t wrong that generic pedagogy certainly does little to improve student learning, some forms of pedagogical knowledge are essential to student learning. His assertion that what applies to one discipline is “banal” in another too readily dismisses the shared features of how students learn, particularly knowledge about how novices learn within a discipline. Students must be able to process, understand, and retain what they are taught, and those requirements are not discipline-specific. They cannot be dismissed as trivial.  

Lastly, Schofield argues that faculty defer too much to instructional specialists rather than developing their own teaching expertise, framing this as part of a broader cultural tendency to overvalue credentialed experts. Yet many of the practices he identifies as essential to developing as an educator—collaborating with colleagues, grappling with difficult material, and engaging meaningfully with ideas and students—are precisely the kinds of work that strong instructional specialists aim to support. These are also core features of effective professional learning communities. While such structures are common in K–12, faculty learning communities in higher education show similar promise: research suggests they can improve collaboration, reflection, and the adoption of new instructional practices (Cox, 2004; Beach et al., 2016). However, the evidence is far less clear that they consistently improve student outcomes. Like many forms of professional development, their impact depends less on participation itself and more on the quality and focus of the work—particularly whether it is grounded in how students learn and tied to specific instructional practices.

As institutions face increasing pressure to improve student retention, completion, and academic success—and some colleges, particularly smaller tuition-dependent institutions, face mounting financial strain—classroom instruction is a central lever for improving those outcomes. At its core, Schofield’s argument reflects a deeper unease about the standardization of teaching. His critique suggests not only a skepticism of evidence-based pedagogy, but a resistance to the idea that teaching can be meaningfully guided outside of disciplinary expertise. Yet teaching-and-learning centers emerged because teaching is inconsistent, and disciplinary expertise alone has never reliably produced strong instruction at scale (Shulman, 1986; Sadler et al., 2013). Effective teaching requires deliberate development and feedback (Kraft et al., 2018; Hattie, 2009). In many ways, Schofield is right that generic, outdated, and unproven practices continue to circulate in schools of education—and they do little to improve outcomes for students. But Schofield’s solution rests on a romanticized view of how teaching develops in practice. Teaching quality varies widely even among experts, and improvement does not occur simply through continued practice. Departments do not automatically function as communities of expert educators; in many cases, teaching remains isolated and uneven. The challenge then is not to eliminate structures for instructional improvement, but to ensure that they are focused, evidence-informed, and grounded in the work of teaching itself.  Good teaching is not the rejection of pedagogy, nor the blind application of it; it is the exercise of judgement that integrates both. Without that, we risk mistaking expertise for effectiveness, and coverage for learning. 

References

Ausubel, D. P. (1968). Educational psychology: A cognitive view. Holt, Rinehart & Winston.

Beach, A. L., Sorcinelli, M. D., Austin, A. E., & Rivard, J. K. (2016). Faculty development in the age of evidence: Current practices, future imperatives. Stylus Publishing.

Cox, M. D. (2004). Introduction to faculty learning communities. New Directions for Teaching and Learning, (97), 5–23. https://doi.org/10.1002/tl.129

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. https://doi.org/10.1073/pnas.1821936116

Hattie, J. (2009). Visible learning: A synthesis of over 800 meta-analyses relating to achievement. Routledge.

Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41(2), 75–86. https://doi.org/10.1207/s15326985ep4102_1

Kraft, M. A., Blazar, D., & Hogan, D. (2018). The effect of teacher coaching on instruction and achievement: A meta-analysis of the causal evidence. Review of Educational Research, 88(4), 547–588. https://doi.org/10.3102/0034654318759268

Nathan, M. J., & Koedinger, K. R. (2000). Teachers’ and researchers’ beliefs about the development of algebraic reasoning. Journal of Research in Mathematics Education, 31(2), 168–190. https://doi.org/10.2307/749750

Rosenshine, B. (2012). Principles of instruction: Research-based strategies that all teachers should know. American Educator, 36(1), 12–39. https://www.aft.org/sites/default/files/Rosenshine.pdf

Sadler, P. M., Sonnert, G., Coyle, H. P., Cook-Smith, N., & Miller, J. L. (2013). The influence of teachers’ knowledge on student learning in middle school physical science classrooms. American Educational Research Journal, 50(5), 1020–1049. https://doi.org/10.3102/0002831213477680

Shulman, L. S. (1986). Those who understand: Knowledge growth in teaching. Educational Researcher, 15(2), 4–14. https://doi.org/10.3102/0013189X015002004

Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1207/s15516709cog1202_4

Sweller, J., Ayres, P., & Kalyuga, S. (2011). Cognitive load theory. Springer 


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