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The Promise and Limits of 'Learning Analytics' (shar.es)

jyosim writes: College students always pay attention in class and do all the readings, right? Ok, they probably never did, but today's professors can actually find out how much each student pays attention in a lecture and how much time they spent on readings, thanks to so-called "learning analytics." Some colleges are experimenting with using the data to re-engineer courses hoping students will learn more and retention will improve. Professors get "dashboards" and sophisticated charts, changing their role in the classroom. MIT is an early adopter, assigning post-docs to help professors interpret this new data. As the article on the new Re:Learning project notes, though, "How much can big data actually reveal about something as personal and subjective as learning?"

2 of 57 comments (clear)

  1. "Social justice" made giving bad grades dangerous by Anonymous Coward · · Score: 2, Interesting

    You must have gone to college before the rise of "social justice".

    Things are very different now than they were even just a decade ago.

    It's extremely risky for a professor to give anything less than a high grade to a student.

    Suppose a student fails to study, and rightfully deserves an F or whatever the failing grade is.

    Also suppose that the professor goes ahead and gives the student this well-earned failing grade.

    If the student's skin color differs from the professor's, then all the student has to do is claim that the failing grade was given because the professor is "racist".

    If the student's gender differs from that of the professor's, then all the student has to do is claim that the failing grade was given because the professor is "sexist".

    If the student happens to be a homosexual and the professor isn't, then all the student has to do is claim that the failing grade was given because the professor is "homophobic".

    If the student happens to be a transsexual and the professor isn't, then all the student has to do is claim that the failing grade was given because the professor is "transphobic".

    If the student happens to have a different religion than the professor, then all the student has to do is claim that the failing grade was given because the professor is "intolerant".

    If none of those apply, then all the student has to do is claim that they were "raped" by the professor.

    Thanks to "social justice" and it's twisted philosophy where the "victim" cannot be questioned, and the alleged "perpetrator" is surely guilty without any sort of investigation being allowed, any professors giving bad grades are likely to lose their careers, if not much more.

    So the professors do the only sensible thing: they just give out A's and sometimes B's, even if the students deserve much lower grades.

    That makes it much harder for a student to come back with a false accusation that will be treated as fact.

  2. Re:"Social justice" made giving bad grades dangero by rgbatduke · · Score: 3, Interesting

    That's a beautiful, passionate, almost poetic response. Sadly, it is completely wrong. None of that stuff ever happens at any significant rate outside of your fantasy life. In fact, I can't recall having heard of any student who ever made any of those claims, although I'm sure that there must be some, somewhere, that have (personality disorders being as prevalent as they are in the general population).

    Actually, students have a pretty finely honed sense of fair play. If you flunk them and they deserve to flunk, you rarely get more than whimpering and sometimes begging. Ditto for most other grades, and grade boundaries. If you flunk them on a technicality, of course, they will be resentful -- and with some reason. But no, students do not in general argue over grades claiming that the professor is biased against them due to race, creed, color, etc, except possibly in the very rare cases where there is some reason to make the argument.

    As for learning analytics -- I have to say that it is (also sadly) mostly bullshit. I don't know about soft subjects, but in things like math and physics:

    a) It is painfully, oppressively difficult to find a good object instrument to measure "learning" at the college level. And I say this as somebody that has used what there is for upwards of a decade. The instruments themselves are badly flawed and it is impossible to prevent an instructor from teaching to the test if they so desire (indeed, it is difficult NOT to teach to the test if you know what is on it and what weight will be assigned to outcomes in terms of "ranking" teaching/learning performance in the course.

    b) There is nothing like standardization of the courses at the level required to build a uniform instrument that might be of some use. In Europe they have such a thing, supposedly, and too bad for them! If Joe gives a wussy, "physics lite" algebraic physics course but Suzie gives a tough, full calculus course covering exactly the same chapters, how do you even compare them. Now imagine comparing them and developing performance analytics when they don't even cover the same chapters from the same book in the same order and with the same basic understanding of the material they are teaching...

    Here's a single example of the problems we really do face. I give all of my entering physics students an assessment to determine how much they remember of basic math. A page of algebra. A page of simultaneous equations. A page of differential calculus. A page of integral calculus. A bit of vectors and trig. Nothing difficult as far as calculus goes -- one can manage a typical intro physics course with five -- that's right, only five -- integral/derivative rules on board, plus the chain rule/u-substitution, plus the product rule/integration by parts.

    Every student entering the class is supposed to have passed two full semester college calculus courses. Yet the mean score on the assessment is around 50%, with plenty of students scoring as low as 15 to 25%. And these are bright students at a very good university.

    Forget "analytics". The problem is deep, not shallow. It isn't going to be solved by improved statistics on more tests.

    rgb

    --
    Even when the experts all agree, they may well be mistaken. --- Bertrand Russell.