Teaching Is An Art And Science

What Actually Happens When You Try to Teach Something

Most people talk about teaching as if it's some mystical balance between creativity and methodology. It's not. It's more like troubleshooting a machine while simultaneously trying to make the machine want to run. I've spent years watching instructors and learners interact in rooms, online spaces, and one-on-one settings, and the gap between what the phrase suggests and what actually occurs is enormous. The "science" side is straightforward enough — cognitive load theory, spaced repetition, formative assessment, scaffolding. These are measurable, testable, repeatable approaches. If you structure a lesson around reducing extraneous cognitive load and increasing germane load, your students will learn more in less time. That part is well documented. The problem is that every classroom looks nothing like the controlled conditions where those studies were conducted. The "art" side is what happens when you walk into a room and realize the lesson plan you spent six hours preparing is going to fail because half the group didn't sleep, one person is dealing with a family crisis, and the technology you built the module around doesn't work on their devices. You adjust. That adjustment isn't random. Experienced teachers develop an intuitive sense for pacing, tone, and when to push harder versus when to retreat and try a different angle. But calling it an "art" implies it can't be taught, which isn't quite true either.

I once had a situation where a student was consistently failing assessments despite attending every session and completing all assignments. The science side — the testing, the feedback loops, the remediation — was all there. Nothing was working. I spent weeks trying different instructional methods before realizing the problem wasn't instructional. The student had undiagnosed dyslexia and was reading every prompt backwards under time pressure. Once we adjusted for that — providing audio versions of all written materials and allowing verbal responses — performance jumped significantly. The "art" was noticing something the data wasn't showing. The "science" was knowing what interventions to try next. Here's the counter-intuitive part that most beginner instructors miss: the science often matters less than you think. Good pedagogy gets you to a baseline. But the variables that actually determine whether someone learns anything are almost never in the curriculum design. They're in the relationship between teacher and learner. A student who trusts the person teaching them will engage with poor material. A student who doesn't trust you will disengage from brilliant material. That's not sentimentality. It's documented in motivation research. Self-determination theory shows that autonomy, competence, and relatedness are the three primary drivers of intrinsic motivation, and relatedness — the connection to the teacher — is the one most people ignore in lesson planning. Another thing people overlook is that over-structuring lessons for the "science" side can actually harm learning. When you decompose every skill into micro-objectives and require mastery of each before progressing, you create what's called cognitive fragmentation. The learner understands the parts but can't integrate them into a coherent whole. This is especially common in technical training where practitioners are taught to follow addy steps without understanding the underlying mental model. You get people who can execute procedures correctly but can't troubleshoot when something goes outside the script.

The workaround I've found is to teach the mental model first, then layer the procedures on top. It feels backwards. It takes longer in the short term. Students get impatient because they want the shortcut. But retention and transfer improve dramatically. In my experience, this approach cuts remediation time by roughly half over a full course, even though the initial sessions feel less productive. There are also scenarios where the art-and-science framework completely breaks down. Online asynchronous instruction is one. Without real-time feedback, you can't calibrate your approach to the room. You're teaching to an avatar. The best platforms simulate this with adaptive learning paths, but those paths are still limited to what the question bank can assess. Anything requiring nuanced judgment — writing quality, problem-solving approaches, conceptual understanding — gets flattened into multiple choice or rubric-scored submissions that reward surface-level compliance. Another failure point is when the instructor themselves doesn't have deep domain knowledge. No amount of pedagogical training compensates for not understanding what you're teaching. I've sat through workshops led by competent educators who were clearly teaching material they'd only encountered at arm's length. Their techniques were textbook-perfect and the students learned nothing of substance because the instructor couldn't answer the follow-up questions that actually drive deep understanding.

If you're looking to actually apply this rather than just nod along to the phrase, start by auditing one of your own sessions. Record it if possible. Watch it back and note every moment where the group's attention dropped or confusion appeared. Then cross-reference those moments with your lesson plan. You'll likely find a mismatch between what you thought you were teaching and what they actually received. That gap is where the real work lives. It's not going to be fixed by another certificate or a better slide deck. It's going to be fixed by paying attention to what's actually happening in front of you and adjusting accordingly.