Andrew Feenberg has taken issue with the “neo-liberal agenda” that is currently guiding how far too many universities both conceptualize and use “educational technology.” In this article, I expand the scope of his critical discussion to include analysis of contemporary higher education initiatives that capitalize on big data.
Tools developed in-house and by a slew of companies now give administrators digital dashboards that can code students red or green to highlight who may be in academic trouble. Handsome “heat maps” — some powered by apps that update four times a day — can alert professors to students who may be cramming rather than keeping up. As part of a broader effort to measure the “campus engagement” of its students, Ball State University in Indiana goes so far as to monitor whether students are swiping in with their ID cards to campus-sponsored parties at the student center on Saturday nights.
Nudging opens up risks on opposite extremes linked to data and how data is used. The first risk is the danger of ignoring variances in data. Valuable data elements that may impact our understanding of the underlying phenomenon and the design of the intervention — elements such as diverse information that is difficult to capture — can be overlooked. Second, on the other extreme, academia may be flirting with discrimination by using group attributes to generalize patterns across individuals who might have features connecting them to one or more categories. Algorithms pick out data points that make up a small (e.g., high school GPA, major, hometown, residence, financial aid status) or large (e.g., race, socioeconomic status, marital status, gender) portion of an individual’s experience, but should these data points become a factor in the types of nudges used?
Under pressure to prove the value of sky-high tuition fees, many colleges are getting tough on classroom attendance. The Wall Street Journal recently reportedon a series of new measures colleges are trying, including tagging students electronically, secret filming of lecture halls, and—the most draconian of all—rules requiring attendance.
Now researchers at the Missouri University of Science and Technology have another idea to keep students in line: an app that replaces the dull process of roll-calling. It could make attendance-tracking easier and free up more time for learning.
Here’s how it would work. Using facial recognition software called EngageSense, computers would apply algorithms to what the cameras have recorded during a lecture or discussion to interpret how engaged the students have been. Were the kids’ eyes focused on the teacher? Or were they looking everywhere but the front of the class? Were they smiling or frowning? Or did they just seem confused? Or bored?
Teachers would be provided a report that, based on facial analysis, would tell them when student interest was highest or lowest. Says SensorStar co-founder Sean Montgomery, himself a former teacher: “By looking at maybe just a couple of high points and a couple of low points, you get enough takeaway. The next day you can try to do more of the good stuff and less of the less-good stuff.”
Students download the ClassCheck app to check-in to classes.
After initial setup, administrators are able to monitor check-ins in the online ClassCheck system.
“They are undercutting my reputation in some ways and actually inflating my reputation in other ways,” he said. “It’s all intellectually dishonest.”
The data come from Academic Analytics, a company that measures scholarly productivity. It adds up professors’ journal articles, citations, books, research grants, and awards, and compares those numbers with national benchmarks. At the moment, the database includes more than 270,000 faculty members.
Achievements was developed by a Ball State team led by Kay Bales, vice president for student affairs and dean of students, who said the app was successful in its first year by engaging about 400 Pell Grants recipients.
“Early research shows that users earned more credit hours in this past academic year and had higher grade point averages than nonusers,” she said. “One thing we know to be certain: Students look at their phone countless times a day. This app puts campus resources at their fingertips, and we have incentivized students to take advantage of important resources.”
Areas across campus offer Achievements — or activities — for students to complete. Participants include University College, Recreation Services, Student Life, Multicultural Center, Late Nite and Career Center.
Bales said Pell recipients from 2013-14 may continue using Achievements next year and the university plans to launch the next round of recruitment of Pell freshmen and sophomores in the fall.
Faculty members at Our Lady of the Lake University recently noticed some newcomers in their courses: administrators and staffers, including their department chairs and program directors.
Without notifying the faculty or asking for permission, professors say, the university has given administrators the ability to add themselves to courses in Blackboard Learn, the university’s learning management system. The faculty members only discovered the monitoring after a professor noticed the new names on the course roster while composing an email. Word then spread to other faculty members, who noticed the same in their own courses.
One faculty member, who is on the tenure track and spoke on condition of anonymity, expressed concern that administrators would read emails intended for students in the class — schedule changes, canceled class sessions and so on — without the context of what goes on in the classroom.
Student data, as part of the education record from each student’s school experience, is most importantly a tool for that student to reflect their achievements, and inform their future decisions. In addition, however, data across students and over time enables insights for teachers, administrators, districts, and states to identify trends, show patterns, and evaluate the success of educational changes to ensure that new programs or services achieve the desired results.
This paper identifies 19 studies – a relatively small sample – where data was successfully used to evaluate a program, create a new strategy, or delve into equity and bias issues. The appropriate protection and responsible use of student data in such studies is a fundamental value. But the power of data to shed light on current student and educational system outcomes and improve the opportunity for individual success is overwhelming.