3/30 Jenna - Sense-making through models and argumentation

In McClain et al.'s "Supporting Students' Ways of Reasoning about Data," the researchers designed a unit that would lead students to develop a "single, multifaceted notion... of distribution" (2000). Over the course of several inquiries - about battery life, traffic flow, and medical treatment - the students relied upon their intuitive ideas about data to construct knowledge about statistics and data analysis. The researchers designed two computational tools (capable of manipulating data and sets in different ways) to support this process. The data analyses enabled students to make arguments that lead to recommendations for decision-making. 

I found the authors' argument for statistical literacy to be a convincing one. I was especially impressed that the students had so much agency in what they could do with the data to form their argument and that their questions predicted their need for new tools and interpretive strategies to make sense of the data. I couldn't help but think of two of Harlow's pedagogical resources: that children are creative and that guiding students is less certain than telling; I thought bought were applied superbly by the researches in this context. Not only did the students come up with rich interpretations of their data, but they also appropriated the computational tools for use in ways that the researchers had not intended! These are the outcomes that every teacher hopes for. Furthermore, it seems likely that students will transfer this learning successfully to other classes and topics.

I did have some lingering questions after reading this article. Mainly, I wonder how successful this program was and its potential for generalization. I would have liked to see some quantitative data accompany the authors' narrative about the participants, about how the desired outcomes were defined, and how many students achieved these outcomes. Only six students are given by name in the narrative and no information is given about the size or context of the class. 

In relation to this course, I think that this article fits in nicely with the argument-driven inquiry readings from last week as another example of classroom activities that engage students in scientific practices. The unit described in this article in a way illustrates how I interpreted the recent announcement about Finland's interdisciplinary teaching; the designed unit could be enlarged to included inquiries about the topic of the data and thus integrate more scientific knowledge with the mathematical practices of statistics. I also think this article enriches our conversations on modeling by raising questions about how students use models to generate data as well as how they construct models from data.