Before taking this course, I considered scientific literacy as a person's ability to analyze scientific information. I was thinking in terms of the relationship between the general population and expert scientists; how does someone interpret and make sense of the knowledge that scientists produce in their everyday experience? I thought of scientific literacy as it related to someone's decision to receive a vaccination, to the debate over teaching evolution and/or intelligent design in schools, and to appointing members of Congress to the House Committee on Science, Space, and Technology. But while I could name tons of ways I hoped scientific literacy could inform people's decisions, I hadn't given much thought to how I expected them to develop this literacy. What skills would they need? What experiences would develop those skills? What could science teachers in the US do? - These questions weren't regularly on my mind.
I still think my original idea of scientific literacy is valid, but my current understanding is much broader. In the simplest terms, scientific literacy is the ability to navigate the mangle/tangle of the production of scientific knowledge. It includes the ability to understand vocabulary of the discipline, ask testable questions, conduct experiments and observations systematically, generate varied representations, and to share and critique ideas. Modeling and media use are ways to cultivate these skills within the classroom community. They push science learning beyond memorization of vocabulary, facts, and formulas, to their very creation in a problem space that is authentic to the learners. Plus, they require that learners have a tangible product (like a simulation or a whiteboard), which means students must be thoughtful of the ways they represent their understanding and how they critique the products of their peers.
As I prepare to enter the PhD program at Vanderbilt I've been thinking about how modeling and scientific literacy will be a part of my future work with SURGE Symbolic. In this game players manipulate an avatar's movement across obstacles by changing graphical representations of the movement. Players must transition between multiple representations (motion graphs, dot-traces, verbal descriptions), creating rich layers of understanding across the different levels of interpretation at work. This is a literacy-developing process. Over the next several weeks, I'll be looking at the literature related to graph learning (how people interpret graphs), with my own hope of finding ways that SURGE Symbolic's design can be improved to better support learning and scientific literacy.
I have a similar definition of scientific literacy, and I like how you describe it as 'navigating' science knowledge and production. Science is useless unless you apply it and use the knowledge somehow, and the hard part is that part. Students are going to have to have a basic understanding of how to critically think of how science is used if they want to be able to make informed decisions and be successful outside of school. Graphs is just one representation of scientific information. I wonder if we will receive more information/training on how to teach graph analyzation. I suppose having students learn how to make graphs can help them understand what to look for when they have to analyze a graph.
ReplyDelete