Hands-on, and textbooks, and sims — oh my!

Photo by NeONBRAND on Unsplash

I was trained to teach in the era of inquiry. In the science classroom, this meant that we couldn’t just tell students something was true. Instead, I was told, teachers created the circumstances that would inspire students to ask questions and construct their own understanding. In a nutshell: textbooks = bad; lecture = bad; hands-on = good; collaboration = good.

In my experience, though, it is much more nuanced. I’ve come to believe that all modes of knowledge acquisition are valid. Sometimes you need your students to play with lab supplies in order to generate testable predictions. Sometimes you need them to collect and analyze their own data. Sometimes you need them to read and digest a textbook chapter or scientific article. And sometimes you need to stand up in front and deliver a lecture.

So, how do we decide when to use each of these teaching strategies? My answer: it depends on who your students are and what you need them to learn. But of course that statement is too general to be useful, so I sketched out the framework I use. (A note: as with everything I write, my goal is to fill gaps in our collective understanding. If something like this exists already, please tell me in the comments. I aim to augment the discourse, not to re-create it.)

Before you keep reading, think about a learning experience you recently had or led (ideally in something science-y). Write down what you DID and what you LEARNED.

Now, look at the framework below. In which quadrant would you locate the learning experience you just documented?

Think about a particular learning experience. Where would it go on this map?

It’s a useful exercise to think about the quadrant you gravitate to as a learner and as a teacher. Do you value direct observation over authoritative sources, or the other way around? Do you feel more comfortable in a qualitative/conceptual domain or in a quantitative/analytical one? When you teach others, do they feel the same way?

More context on where this framework came from: I’ve been engaged in equity-driven STEM and indigenous science. I’ve been looking for the “most” culturally responsive way to teach science, reading about project-based learning and the modeling approach to instruction. I’ve been thinking about how my students’ home cultures emphasize different ways of acquiring and applying scientific knowledge. And I identified two relevant dimensions:

1. Direct observation versus the wisdom of others. I’ve read claims that ALL students learn best in a fully hands-on environment, where everything they learn is experienced firsthand. Certainly in the academic literature there’s a bias towards direct observation, implying that students need to do each experiment for themselves in order to believe its results. Indeed guided hands-on activities can indeed foster deep learning, but authoritative wisdom is important too. All societies build on the accepted theories of their day, refining and augmenting them until a theoretical overhaul becomes necessary. If we allow our students to gain scientific knowledge only by personally redoing every possible experiment, then our students won’t cover much ground. It is more efficient to take in knowledge from authoritative sources than from meandering play. Understanding the discoveries of others gives students a foundation to build new knowledge to move society forward.

2. Qualitative/conceptual versus quantitative/analytical. At face this dimension seems less contentious: most teachers would agree that both types of engagement are important for learning science. However, in practice I find that modern schooling over-emphasizes the quantitative element. As a science-y person in the Western World, I always felt that you can’t claim the world works a certain way until you can prove it. For years, when students told me, “I can sense the answer but I can’t explain it,” I would reply that this means they probably don’t yet really understand it. However, reading Blackfoot Physics helped me appreciate the roles of intuition and the ephemeral in forming a gestalt of how things work. There’s art to science. I’ll never forget the moment in my college research lab when the machine wasn’t working, and we were all just playing around with the various knobs, and I suddenly instinctively knew that we needed to turn a particular dial counterclockwise — and it worked. My analytical training tells me that either it was coincidence or my brain did some complex calculations below the level of my awareness. I certainly wouldn’t publish a scientific paper based on these non-replicable moments, but I do want to build and celebrate students’ intuitive conceptualizations of things — in addition to (of course) their quantitative analysis.

Example of a lessons sequence mapped against this framework.

How could a lesson sequence map to this framework? This diagram is my attempt to map a learning progression for freefall and air resistance, using this framework. I don’t think that every learning sequence needs to start or end in a particular quadrant, but it’s a good idea to cover as many quadrants as possible. Some tips: Be deliberate about which quadrant is appropriate for a given learning experience. Think about your students’ backgrounds and strengths. For example, if students are more comfortable with hands-on activities, then you can give them challenging labs and invigorating authoritative texts. On the other hand, if your students need to hear an “expert” say it for them to believe it, you can show them how hands-on activities deepen the understanding they acquire whenreading textbooks and research articles. (And don’t forget: computer simulations count as authoritative sources, NOT direct observation. Read more here.)

In the end, it all goes back to knowing your students and how they learn. A given topic in science can be taught in any single quadrant of this framework or any combination thereof. Particular types of activities will usually land in certain places, as you see in the image below. For example: reading a textbook is generally a more conceptual activity, which leans more heavily on authoritative sources and less heavily on direct observation. This is why textbooks appear in the top-right quadrant. I’m sure there are exceptions and caveats, but if you think something is materially mis-placed in the diagram below, please let me know in the comments. (Also: thanks to Jenna Peet for suggesting I add “problem sets” to this diagram.)

Particular tools for knowledge acquisition mapped against this framework.
Particular tools for knowledge acquisition mapped against this framework.
Particular tools for knowledge acquisition mapped against this framework.

As a parting gift, I have an exercise for the reader. Where in this framework (left or right, top or bottom, or all over) would you place:

1. Your own high school science experience?

2. The high school science experience you wish you had?

3. A class that follows the Next Generation Science Standards?

4. An online learning system like Khan Academy?

5. The way you teach your toddler?

Please use the “comment” feature to share your thoughts on this topic. Every time I revisit this framework, it evolves. I’d love to continue developing the framework with more minds in conversation. Speaking of collaboration, I want to specifically thank Tegan Morton for helping co-develop an initial version of this framework 2 years ago, as well as my STEMteachersNYC CRT workshop co-leaders: Allison Mayle, Leah Liberman, and Jenny Shen.

I teach physics and computer science in East Harlem, New York. I aim to engage.