Wow, there was a lot of great stuff this week relevant to a lot of what we’ve been talking about with modeling, especially defending the model, and revising the model as appropriate. Before I get into the readings, I think I ought to point out that this approach is only possible in an environment where the students are comfortable with being wrong. The Sampson reading said it more explicitly, but both articles realize that we will lose students if they are so concerned with being right that they don’t participate. And with that, on to the readings.
Sampson & Glein: This article promotes a specific model of teaching science using guided argument driven inquiry (ADI, their term). This method, they argue, has the benefits of helping students learn the material effectively with the added bonuses of teaching them how to evaluate their own and others’ arguments and present them effectively both verbally and in writing.
- This system has students essentially develop a model in groups to explain a dataset they have been given. After developing their model, they defend it to the class in a low-pressure environment. Then, they present a written defense of their model which undergoes peer reviewed revisions.
Reiser, Berland, & Kenyon: This article is similar to the other; however, it focuses more on constructing the explanation from evidence rather than the defense of said argument.
- The focus is on the evidence and getting students to support a claim, not because they believe it to be “the right answer”, but because it is supported by the data.
- Like in the other article, it points out that having students defend their arguments helps them refine both their arguments and their understanding of the concepts.
I love this system of learning through explanation and argumentation for several reasons. First of all, it is not uncommon in research for there to be multiple hypotheses to explain data, especially if that data appears to contradict itself. Teaching through this method may help students realize that the answer is often far more complicated than it may appear at first glance. Secondly, the interdisciplinary nature of this method, if applied broadly, will hopefully spare the next generation of scientists from having to read very poorly written papers. I’m not even joking, some are painful to read. More on topic, though, effective writing skills may be applied to any career the student chooses. Finally, it can help students to critically examine their own ideas, theories, and belief systems and tweak or discard them as necessary. Hopefully, if our students have been taught in this method, none of them will become anti-vaxxers.
On this last point, I think an interesting idea to try might be to give students data and ask them to create a model using that data. Then, after they have created, revised, and defended their models, give them new data that appears to contradict the original data at first glance and see how they adjust their models to fit that data. For example, the theory of evolution is predicated upon slow accumulation of changes due to mutations (original model). This tends to mean that we don’t see new features pop up all of a sudden. However, we can observe in the fossil record that sometimes large changes occur quite suddenly, such as the appearance of feathers on some dinosaurs, despite the fact that scales do not appear to have much in common with feathers (new data). The reconciliation came when it was discovered that the same gene, activated at different points in the embryonic stage, controls whether scales or feathers develop. Having students work through this process could be valuable.