A number of students have asked me for suggestions about how to go about reading more effectively (faster, with more understanding). I prepared the above presentation as a way to illustrate a number of key ideas while also linking them to the theoretical frameworks that we have been covering in p544: Applied Cognition and Learning Strategies. There are certainly different ways this could be analyzed, and we will cover a number of them throughout the semester. As with the majority of my presentations, this was the backdrop and spark for intense and productive discussion and debate. Therefore, read it individually at your own peril.

For this representation to make any sense, you will definitely want to click on the image and see it enlarged.

This week we read about digital storytelling (Hull and Katz, 2006), fanfiction (Black, 2006), and some of the tensions with applying Web 2.0 practices in education (Dohn, 2009). While there are a number of incredibly important issues being raised by each of these authors, there were three big ideas that struck me that I wanted to include in this response: 1) the role of these various tools in helping individuals to express and shape their identity; 2) the relative absence of discussion of specific tools; and 3) the different relationships with other individuals that were suggested by each of these. In looking at these, I have intentionally simplified the 3 models in ways that some viewers may take issue with (if so, I hope you will comment!). I have also made some potentially contentious choices about when to give individuals complex identities or not. Those choices reflect what I perceived as the relative importance of discussing those identities in the various papers, not a belief on anyone’s part that individuals in certain contexts lose or flatten their identities.

More than ever, given this week’s theme, I hope you will all post comments, suggestions, and critiques below.

• Black, R. W. (2006). Language, Culture, and Identity in Online Fanfiction. E-Learning, 3(2), 170-170.
• Dohn, N. B. (2009). Web 2.0: Inherent tensions and evident challenges for education. International Journal of Computer-Supported Collaborative Learning, 4(3), 343–363.
• Hull, G. A., & Katz, M.-L. (2006). Creating an Agentive Self: Case Studies of Digital Storytelling. Research in the Teaching of English, 41(1), 43-81.

This week we talked about Virtual Worlds. The content of this image is related primarily to a paper about the spread of the WhyPox outbreak in Whyville (you can see a host of Whyville-related research at http://kafai-whyville.blogspot.com). However, I think that all of the papers that we read this and in the previous unit on games discuss both the power of virtual experiences to situate learning, and also raise a question about how and when that learning moves out of the virtual world.

I’m struggling this week with how to make the full range and scope of a literacy visible to students in the context of computational literacy as inspired by diSessa’s (2000) book, Changing Minds. It seems that most people either “get it” and therefore don’t need a description, or would need quite a bit of exposure to truly grasp the implications. It feels similar to trying to explain to a 5 year-old why literacy is so much more powerful than their understanding the storybook in front of them, long before they have even begun to appreciate all of the powerful ways that the ability to read and write can transform their daily life. This drawing, therefore, attempts to sidestep the issue by focusing on some of the underlying assumptions of what it might mean to reach a point where computational literacy is accessible to all, as Wing (2008) and diSessa (2000) would encourage us to strive for.

This post is in response to the chapter on Cognitive Information Processing (CIP) theories of learning. There were many directions this could have gone, but a lot of the forum discussions this year seem to be about memory with a focus on encoding and recall. That inspired the library theme. The references to radiation and General are a nod to the famous Glick and Holyoak transfer study. For some reason, they came to mind when I was trying to think about a topic to search for in memory. If you are wondering why… ask the librarian!

This dtg is a response to:
Colella, V. (2000). Participatory simulations: Building collaborative understanding through immersive dynamic modeling. Journal of the Learning Sciences, 9(4), 471-500.

This was inspired by several of this week’s readings that all focused on how various kinds of computational software can make complex science concepts more accessible to students of all ages. Notably:

White, B., & Frederiksen, J. R. (2000). Technological tools and instructional approaches for making scientific inquiry accessible to all. In M. J. Jacobson & R. B. Kozma (Eds.), Innovations in science and mathematics education. Mahwah, NJ: Lawrence Erlbaum Assoc.

Wilensky, U., & Reisman, K. (2006). Thinking Like a Wolf, a Sheep, or a Firefly: Learning Biology Through Constructing and Testing Computational Theories—An Embodied Modeling Approach. Cognition and Instruction, 24(2), 171-209.

Sandoval, W. A., & Reiser, B. J. (2004). Explanation-Driven Inquiry: Integrating Conceptual and Epistemic Scaffolds for Scientific Inquiry. Science Education, 88(3).

Note: the formula on the whiteboard came from the Wikipedia page for Kepler’s laws of planetary motion.

Just saw this video linked on Michael Wesch’s Digital Ethnography Blog which includes a brief discussion of its origins as a class project in Lynn Schofield Clark’s Innovation in Mass Communications class at the University of Denver, and some of the benefits of doing such a project. It’s a really nice framing of a few of the common problems that arise when people try to integrate technology in the classroom, and even has the Office theme song which is always a bonus.

The dtg this week was designed for two purposes. First, I was responding to Koedinger & Corbett (2006) and Schwartz, Biswas, Leelawong & Davis (2007). These two book chapters discuss technologies that were modeled in very different but interesting ways on the success of human tutors and interactions, as well as a rich understanding of the content domain. Second, we have been drawing and refining models of how technology can support educational ecosystems in class. This is my attempt to infer a general model from the two readings so that we can discuss the limitations of my inference and the underlying models in class. My goal is that this will serve as the center for an interesting conversation about both the readings and the modeling process in general.

[Update]

Just a quick note to say that from my perspective this class exercise was an absolute success. My choice to be intentionally vague in the model led the students to some really productive discussions about what nuances were missing as they revisited the readings to critique the models.

Koedinger, K. R., & Corbett, A. (2006). Cognitive Tutors: Technology Bringing Learning Sciences to the Classroom. In K. Sawyer (Ed.), The Cambridge Handbook of the Learning Sciences (pp. 61-78). New York, NY: Cambridge University Press.

Schwartz, D. L., Biswas, K. P. B. G., Leelawong, K., & Davis, J. (2007). Animations of thought: Interactivity in the teachable agent paradigm. In R. Lowe & W. Schnotz (EDS.), Learning.