Qualifying the Quantified Learner
Part of VTE’s mission is the monitoring of emerging trends bringing pedagogy and technology together. The “quantified learner” is such a trend, related to the broader theme of educational data explored at VTE. Those matters may impact teachers’ work and there are plenty of tricky issues to work through. People in Quebec’s Cegeps monitor this topic while colleges elsewhere in Canada provide training in this field.
The “Quantified Self” concept, which inspired the title for this article, is often linked to health and fitness data, as collected by the newly released wearable devices described in a previous article. By contrast, tools we already use are creating the “Quantified Learner”, whether or not we want to do so. We already have lots of data about students. From aggregate statistics about dropout rates to individual profiles and grade reports, information is plentiful and readily available. What can we do with such material? Are we transforming learners in quantitative versions of their complex selves?
These questions are specialized versions of inquisitive discourse about such topics as Open Data, Big Data, Surveillance Society, Cloud Computing, and Online Privacy. Education provides a useful context for such enquiries. The Marketplace radio programme pairs the quantified student with “the NSA revelations and the massive retailer data breaches”, giving their reporting an ominous tone. What we, as teachers, can bring to the issue? Why should we care? How are we involved?
Infographic about the Quantified Student: A day in the data-driven life of the most measured and monitored students in the history of education (Source: Marketplace)
Whether we keep an online gradebook on Lea, fight plagiarism with TurnItIn, use Google services to edit a document with students, or monitor student activity on Moodle, we are in effect contributing to learner data. In some cases, as in Moodle or Lea, we control much of the process. In other cases, third parties may gain valuable insight about our students. Even if we focus on the information we collect for our own purposes, we may ask ourselves hard questions about the stakes for our students and for society as a whole.
One of the thorniest issues around learners’ data concerns the use and appropriation of such information. As Audrey Watters asks, “Whose Learning Is It Anyway?” Practitioners are advocating for a code of practice while well-known educational researcher Stephen Downes dismisses the impact of such a code, favouring first party ownership instead. Calling the issue of data ownership a “land mine”, EDUCAUSE contributors recently proposed a fiduciary model, merging institutional interests with personal ones.
Student success provides the ultimate goal, many may argue. However, as we all know, the multifaceted nature of learning makes it difficult to assess. Even “retention”, a related but more manageable part of student management, revolves around such difficult-to-measure factors such as “[h]ow a student integrates into the social fabric, the formation of friendships and support groups, [and] the adjustment into student housing”. Some social scientists would be quick to point out that, “the formation of friendships” is itself a tricky issue, affected by diverse factors. Apart from nursing teachers and directors
of information services, who wants to delve into learners’ friendship networks?
Learners themselves have a clear stake in their education. The move to empower students pairs well with the use of learning data. As with the Quantified Self, engagement and motivation may come when people gain a measure of control over their own statistics. When learners track their own progress, they learn more than the content at hand.
How about you? How are you involved in data-driven education? Do you perceive a shift in the discourse about student information? Which tools would you use to help learners achieve their own goals?