Busting students using facial recognition software.
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I always walk around the classroom when I teach.
Couple of reasons: it burns off some nervous energy and it lets me peek at students’ computer screens.
The latter is the the acid test of attentiveness.
If I see one or two students checking email or sports scores, I figure it’s their problem and they move to the front of the queue for cold call questions.
If I see a lot of students “digitally distracted”, I figure that it’s my problem and I’ve got to adjust … e.g. shift out of lecture mode and into discussion mode.
That’s pretty straightforward in the classroom.
But, how to know if students are paying attention when they’re being beamed material online?
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According to The Verge …
ESG, a business school in Paris, will soon begin using artificial intelligence and facial analysis to determine whether students are paying attention during online classes.
The software – called Nestor — uses students’ webcams to analyze eye movements and facial expressions and determine whether students are paying attention to a video lecture.
The information is summarized for professors so that they can determine whether the periods of inattentiveness are isolated to a handful of students or spread across most of the class.
If the latter, the profs have the opportunity to tune-up their material or their pedagogical approach.
What about the students who are just digital slackers?
Nestor is able to use the data to individualize quizzes and tests.
English translation: The software is able to skew test questions towards the material that was covered “during moments of student inattentiveness.”
Boom: problem solved.
That is, unless the students put tape over their laptop’s camera.
Gee, isn’t technology great?
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