You guys, I think I have a model to show you.
This makes me extremely happy, because as I’ve explained (more than once), I’ve struggled mightily with the very concept of modeling. I’ve also struggled with representation. The purpose of designing this model is to show my take on the role of new technologies in educational environments. But articulating a theory, even a working theory, about the role of technologies has been such an insurmountable challenge for me–which technologies? for which students? and for what purpose?
But the elements for building this rudimentary model have been around me for some time. It just took time and reflection for me to be able to put the elements together.
Inspiration for this model
Design of the periphery: Multiple intelligences schools. A few years ago, I read the 25-anniversary edition of Howard Gardner’s Multiple Intelligences. Throughout the book, Gardner describes a variety of approaches to integrating his theory of multiple intelligences into learning environments, and one description–of the Key Learning Community in Indianapolis–has stuck with me. In this school, students work in “pods” that represent each type of intelligence outlined by Gardner; a founding principle of this school, he explains, “is the conviction that each child should have his or her multiple intelligences stimulated each day. Thus, every student at the school participates regularly in the activities of computing, music, and bodily-kinesthetics, in addition to mastering theme-centered curricula that embody standard literacies and subject matter.”
You don’t have to agree with this approach to appreciate its effort at offering a range of avenues for learning to happen. From time to time I think about those multiple intelligences schools and wonder what aspects might be applied to my current area of focus, the English / Language Arts classroom. Clearly, more avenues toward literacy is better than fewer avenues; and since we know that traditional literacy practices taught through traditional means are insufficient preparation for the types of literacy practices people are called upon to demonstrate in real life, we might think of “pods” for different groupings or categories of literacy learning.
Design of the center and periphery: A real life ELA classroom. I’ve had the unBELIEVABLE good luck to sit in on Becky Rupert’s ELA classroom at Aurora Alternative High School here in Bloomington, IN. Much of the design of this model is based on how she has arranged her class. To begin with, the main focus of the room is a square of tables where students meet at the beginning of each class. My model does not identify the teacher’s location; that’s because in Becky’s classroom, she sits at the table right alongside her students. She does this on purpose, and it works in service of developing a learning community.
Becky’s classroom is absolutely stuffed with books–you have to move books in order to get to other books. A new addition this year is a laptop cart, which sits against the far wall of the room.
Inclusion of design thinking: my work with SociaLens. For the last several months, I’ve been working with a new organization called SociaLens. The purpose of this organization is to consult with businesses and offer strategies for integrating new types of communications tools and ways of thinking into their organizational plans, with a particular eye toward social media technologies. Two key categories that we think make for highly adaptive, potentially highly successful organizations are new media literacies and design thinking.
Until I started working with SociaLens, I had not thought to consider the connection between these categories. I also hadn’t thought about what educational researchers can learn from corporate innovators and vice versa. But what has been seen cannot now be unseen. I’ve come to see design thinking as an essential element of literacy learning, and especially if you believe (as I do) that computational flexibility (which I’ll describe briefly below) is key to preparation for success in a new media age.
Inclusion of new media literacy, representational literacy, design thinking, & computational literacy “pods”: Some stuff I’ve read. I’ve been immersed in new media literacy research for a good chunk of years, and I drank that kool-aid long ago. If you believe in the value of teaching new media literacy practices in schools, then computational literacy kind of comes with the territory. These categories of literacy are similar in lots of respects: Both are better described as a set of proficiencies and attitudes–what Lankshear and Knobel call a combination of “technical stuff” and “ethos stuff”–than as concrete, teachable skills. Both require a kind of openness–a flexibility–to meet the quickly changing demands with emerging technologies. But new media literacies are the required skills to engage in collaborative knowledge-building or collective meaning-making or problem-solving activities, while computational literacy is, in my mind, linked to a kind of “hacker’s mentality.” It’s the act of simultaneously making use of and resisting the affordances of any technology; of knowing when and how to say “no” if a technology doesn’t meet your purposes; and of finding (or developing) a new technology that better meets your needs and interests.
Design thinking, as I mention above, comes out of my work with SociaLens and the (admittedly very surface-level) reading I’ve done about this approach to problem-solving. This type of thinking has also made an appearance in the recent work I’ve been reading about research in science and math instruction. Many researchers whose work focuses on supporting an inquiry-based focus in science instruction, in particular, emphasize the value of embracing the epistemological basis of science-as-inquiry. As William Sandoval and Brian Reiser explain in their 2004 piece, “Explanation-Driven Inquiry: Integrating Conceptual and Epistemic Scaffolds for Scientific Inquiry,” the epistemic elements of this approach include
knowledge of the kinds of questions that can be answered through inquiry, the kinds of methods that are accepted within disciplines for generating data, and standards for what count as legitimate interpretations of data, including explanations, models, and theories. Placing these epistemic aspects of scientific practice in the foreground of inquiry may help students to understand and better conduct inquiry, as well as provide a context to o
vertly examine the epistemological commitments underlying it.
Wilensky & Reisman, in their work with computer-based modeling, argue in support of what they call “the engineer’s dictum”: “If you can’t build it, then you don’t understand it.” They work with a modeling language called NetLogo, which is a loose descendant of Seymour Papert’s Logo program. The program requires students to solve problems by developing models of real-world processes like population fluctuation within predator-prey (wolf-sheep) communities and the phenomenon of fireflies synchronizing their flashes. The authors make a strong case that model-based thinking–or what we might also call “design thinking”–is key to students’ ability to engage in deep learning about a specific phenomenon and about scientific inquiry more broadly.
I included a pod for “representational literacy” in this model because of my own recent experience grappling with model-building. The ability to design, critique, and modify representational models is a set of skills with relevance across content areas, and we don’t typically think of it as extremely valuable in the literacy classroom. But it should be news to nobody that “literacy” is becoming an increasingly visual category of proficiencies, and that representational literacy is quickly becoming even more tightly bound up with traditional literacies than it ever was before.
What I haven’t yet noted is that these categories of literacy practices make up what we might call “literacy science.” I mean this term to hold the same place in the literacy classroom as “mathematician” or “scientist” or “historian” or “musician” hold in their respective classroom-based environments. As a culture, we haven’t spent enough time yet thinking about the purpose we hope the new literacy classroom to serve. Science class is supposed, ideally, to get students thinking like scientists; in math class you (ideally) learn to think like a mathematician; in history class you think like a historian; but in general English class has been designed as a sort of catch-all, a place where students can learn the basic reading and writing skills that enable them to think like historians, mathematicians, and so on.
What if we shifted the focus of the ELA classroom to more explicitly broach the notion of “literacy science”: A way of being in the (literate) world characterized by an ethos, a set of skills, and a set of norms and behaviors? What would it mean to turn the ELA classroom into a place where we support the growth of literacy scientists?
Inclusion of open space: a nod to the future work of literacy science. Howard Gardner’s list of multiple intelligences has grown over the years, and my model is designed to accommodate new categories of literacy practices. Filling up the entire classroom does nobody any good, especially since we know–we absolutely know–that new valued practices are emerging along with the breakneck speed of emergent technologies.
I should mention, too, that my model includes a safe filled with bundles of cash. This is a nod not only to the future work of literacy science but also to the current conditions of the typical public school. On top of the training required, every one of the pods in my model costs money, and it’s money that schools simply don’t have.
So that’s it: That’s my current model for the role of technologies in the literacy classroom. I would love to know your thoughts. Comments, questions, and suggestions are most welcome and will be read with great joy, thoughtfulness, and enthusiasm.
References: In case you’re interested in reading the work I identified above, here are the citations.