Major Measuring

The Chronicle of Higher Education reports that universities are experimenting with a new metric machine not only to help students pick their next classes but possibly their major. Or in the thinking of most people trying to graduate from college, their life path.

The model for this new student advising tool is Netflix.

The Netflix model of gathering information from the subscriber, finding similar films, and locating favored genres works most of the time as a metric for helping you pick a movie.

I have rated over 5000 movies & television shows at Netflix. At this point, it recommends dvd’s that in fact are something I like watching. But then again, it is working from a fairly huge data set. Most of my friends, even the ones that are movie buffs, have only rated a few hundred films if they even have an account.

Those concerned about the Future of the University should take note then as the Netflix metrics machine makes its way into the academy beyond the bored sophomore rating movies on the library computer between study sessions.

The Netflix Effect: When Software Suggests Students’ Courses

This entry was posted in Future of the University, Metrics, TechnoScience & Technoscientism. Bookmark the permalink.

2 Responses to Major Measuring

  1. Kelli Barr says:

    This comment struck me as particularly apt:

    When I read “It even predicted she would get a good grade” I cringed. I’ve already had more than one student tell me, “I am a 4.0 student and it would be unacceptable to get less than a good grade in your course.” Why in the world would I want the robo-advisor to reinforce that attitude?

    I cringed when I read that line of the article as well. I have no problem with this kind of thing being used as a tool to help inform and streamline the advising process. Academic advisors are often not completely informed as to the course listings in other departments, but if given particular course descriptions, they can judge whether those courses would complement or add nuance to the student’s projected educational path.

    But advertising the thing as a predictor of your academic success is technically inaccurate (i.e. the database cannot possibly accomplish that based on the proper, holistic sense of success) and morally wrong, no doubt; it caters to some students’ interests in only getting the grades, nevermind the quality or depth of the experience, and simplifies that experience to a process of receiving information and regurgitating it for the purposes of a single, final judgment of competence. The shortcoming of an analytic approach to the education process undermines the goal of the educated individual amounting to more than the sum of it’s constituent parts; the educated individual is qualitatively different from (read: more valuable than) the individual + the sum total of knowledge from all of their classes.

    What I worry about is the problem with any kind of technology meant to supplement human judgment – it often becomes conflated with replacing human judgment. The onus, then, lies on advisors and university employees to constantly be aware of the power of this kind of commensuration and its proper role in the advising process. A machine can challenge and inform academic expertise, but it cannot, and more importantly should not, replace it.

  2. Keith Brown says:

    You are getting to the core of what machine means. Nothing more than an expedient, certainly not a replacement for human judgment and communication.

    I think there is also a danger, as the software becomes even more refined, that administrators feeling budgetary pressures from governor appointed regents and legislative accountability die hards will recognize the advisor as redundant. Who needs to a payroll line for a human advisor when a software machine can do the “same” thing for one big lump sum?

Leave a Reply

Your email address will not be published. Required fields are marked *

*

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <strike> <strong>