Reading this week:

Bailey, J., Carter, S. C., Schneider, C., & Vander Ark, T. (2012). Data Backpacks: Digital learning now!.

U.S. Department of Education. (2012). Enhancing Teaching and Learning Through Educational Data Mining and Learning Analytics: An Issue Brief.

Hill, P. T. (n.d.). Finance in the Digital-Learning Era. Creating Sound Policy for Digital Learning: A Working Paper Series from the Thomas B. Fordham Institute.

What problems are we trying to solve?

• “The current way student records and transcripts are managed is insufficient to meet the evolving needs of teachers, students, and parents” (Bailey et al.).
• “Our system doesn’t fund schools, and certainly doesn’t fund students” (Hill).
• Policymakers and administrators need to understand “how analytics and data mining have been—and can be—applied for educational improvement” (Data Mining and Learning Analytics).

What vision of education are we working towards?

• “Each student’s account would, in a sense, constitute a ‘backpack’ of funding that the student would carry with her to any eligible school or instructional programs in which she enrolls. The contents of the backpack would be flexible dollars, not coupons whose use is restricted to a particular course or service” (Hill).
• “The most important [adantage] is individualization and rapid adaptation to what a student is learning, leading to the possibility of more rapid and consistent student growth” (Bailey et al.).
• “Making visible students’ learning and assessment activities opens up the possibility for students to develop skills in monitoring their own learning and to see directly how their effort improves their success” (Data Mining and Learning Analytics).
• “A study contrasting the performance of students randomly assigned to the OLI statistics course with those in conventional classroom instruction found that the former achieved better learning outcomes in half the time (Lovett, Meyer, and Thille 2008)” (Data Mining and Learning Analytics).

What limitations might there be or what questions should we ask?

• Who are the designers of the platforms and how are their biases in them? This is not a new question for educational materials, but still one worth considering.
• “What children learn would then depend on the quality of their parents’ choices” (Hill). How would kids fare whose parents were not able, for various reasons, to keep up with choices?
• Programs could be prevented from use “only after some children had been demonstrably hurt by them” (Hill).
• “All such investments are meant to benefit children but they also benefit private parties—the teachers who use new skills to make higher salaries, the vendors who sell professional devel-opment services, etc.” (Bailey et al.).
• “Unlike educational data mining, learning analytics generally does not emphasize reducing learning into components but instead seeks to understand entire systems and to support human decision making” (Data Mining and Learning Analytics).

How might the changes in personalization, finance, and data foster a participatory culture of learning?

I recently watched and blogged about Audrey Watters’ keynote from the C-Alt conference, titled Ed-Tech, Frankenstein’s Monsters, and Teacher Machines. She talked about how ed-tech is full of behaviorist technologies, citing notifications, nudges, gamification, which is built in to many of the platforms written about in this week’s readings. She tells the story of Alan Turing asking if a computer could think, but that he really meant asking whether a computer could exhibit behaviors that could fool a human into thinking it was human “enough.” I see learning more from a constructivist point of view, where students build their knowledge on what they already know, as we read about in “How People Learn.” Are behaviorism and constructivism at odds in a learning ecosystem or could they coexist for building different skills? I see a participatory culture as being fundamentally constructivist, where learners’ own interests and experiences drive affiliations and personal expressions. Does a system based on behavioralism preclude authentic participation?

The idea of authenticity also brought me to questions of identity. This infographic compares “team transparency,” led by Mark Zuckerberg, and “team anonymity,” led by Christopher “Moot” Poole, founder of 4chan. How does having your identity (or a notion of a fixed identity) as a learner tracked from birth affect a person’s own identity formation? How does the platform reward or require a certain identity? (Kimmons, 2014) In working with middle schoolers, I saw the importance of kids trying on different identities as a way to understand their world. A learner profile that follows them year to year and school to school may smooth learning opportunties but it may also lock kids into always being “that kid.” Furthermore, if we have take a post-modern understanding of identity as one that is never fixed but is created in relation to others and situations, what impact (good or bad) will this big data mediated, educational enviroment mean? How will the designers be training certain identities? How will this impact divergent thinking? Will these redesigns mean more creative thinkers? These are geniune questions, not meant to be particularly optimistic or pessimistic, though I think people will see them in one way or the other based on their own inclinations.

Kimmons, R. (2014). Social Networking Sites, Literacy, and the Authentic Identity Problem. TechTrends, 58(2), 93–98.