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Current Trends in Ed Tech

As a final requirement for a teaching certification, I am doing two things this semester: 1. taking a class (AL 883 - Practicum in Blended and Online Learning) and 2. as a part of this class and the certification, creating and maintaining a teaching portfolio.

For our first official assignment for the teaching portfolio, we were asked to go to a website like the Chronicle of Higher Education or Educause Learning Initiative. From there, we were to choose an article about a current trend in digital learning/educational technology and write a short reflection about it about how it may 1. fit with our teaching 2. affect our discipline and 3. otherwise impact our work.

Of course, any discussion about current trends in ed tech requires a stock image of a laptop

I chose an article from Educause Learning Initiative called Big Data Analysis in Higher Education: Promises and Pitfalls. The authors, Chris Dede and Andrew Ho, grapple with how big data's practical applications in higher education have not been fully explored. However, there are a multitude of issues with "big data" still: 1. there is no agreed upon definition of what "big data" is 2. the use of data to make decisions that significantly impacts people's lives is a moral gray area and 3. data, algorithms, and other machine-based decision making systems have been shown to exhibit the biases and prejudices of their creators. Meaning that despite it's innocuous surface, data and the way that it is collected is an expression of hegemonic power (see Bowker and Star's book Sorting Things Out: Classification and its Consequences).

When I first opened the article, I was hoping for a more critical approach to the use of MOOCs in collecting student data and instead, it was an article celebrating data to measure student performance, student interaction, and how MOOCs give researchers the opportunity to collect "fine-grained data about the actions of an individual student," (Dede and Ho). Further, the authors highlight how longitudinal data about students can be collected to assess their learning outcomes, their trajectory towards completion, and others. I was, quite frankly, deeply disappointed in the article and the lack of critical engagement of how "big data" and its use of analyzing students as research subjects for the use of prediction and "learning" is deeply rife with issues of not just privacy, but of learning based outcomes based on prediction models of success. Further, these students in the MOOCs may or may not be privy to the fact that every online activity they're doing is being tracked and used to understand their behavior.

I don't know if data is going to "enrich" the way that teaching occurs, and am not even totally on board with the idea of MOOCs in general. Although online classes have been a regular part of my educational experience in higher ed, I can't say that I learned any more or less from this environment but the fact that MOOCs aren't necessarily being celebrated (in this article) for their access but rather for the "intimate data" that they will create about individual students is disturbing and is indicative of how much power we have given to big data as being epistemological and without bias. In fact, data holds a lot of bias based on what was chosen to be collected, and more reflection on how educators persistently reproduce hegemonic power under the smokescreen of "big data" is necessary.

In my own discipline, there are a faction of people who critically approach these kinds of online and data-based learning initiatives (and big data in general), but unfortunately the reality of the academic institution is that more and more classes are going online. The answer, still, is not that these online classes will provide us more data about students but rather that they come with a catch-22: indeed, more people have access to higher education because of the convenience and ease of online classes but online courses still tend to mirror the negative parts of face-to-face instruction: lectures, videos, and PowerPoints are still frequently used; assessment is usually boiled down to examinations, and some are even challenging whether online learning is even that beneficial. Either way, my opinion is that I find it horrifying that the authors consider the behavior of students in MOOCs as rich data sources and that in higher ed, MOOCs and "big data" are not going to solve persistent issues in education.

© 2018 by Julia DeCook.