The school could simply use RFiD cards for tracking attendance.
Why not use a fingerprint reader if automation is needed, or just place trust in the teacher to not cheat and give them a web page or app to enter absences?
Attendance is a safety thing (or viewed that way). If my 8 year old unexpectedly doesn’t show up to school, I would like to find that out at 8:30 rather than 15:00.
Yes, just like you and your friend can do a lot of other cheating in school. And the mechanism used to prevent that is severe punishments once caught by a teacher.
I don't see much difficulty in spotting an empty desk that should be occupied according to today's automatically generated seating chart.
On another note, I feel like I'd be more okay with facial recognition and other biometrics in the form of you going to a scanner and initiating a scan. But certainly not surveillance with recognition built on top. Article doesn't seem to specify what they used, though the image chosen implies surveillance.
They actually studied this as well as the facial recognition system. Two different classrooms over an 8 week period.
The biggest problem they found with the RFID system;
> During the first week of testing (week 41) 38% of pupils didn’t bring their tag at each lesson, while in the second week of testing (week 42) 47% forgot it. [1]
[1] - http://pages.tieto.com/rs/517-ITT-285/images/SummaryFutureCl...
So You could have a tracking on a map of a dot moving, but as soon as you associate that dot with a person in the same dataset - that causes dramalama. But you can have that dot associated with a person in a separate dataset held by somebody else and skirt around the fact that the same dataset is held, albeit obfuscated at a remedial level that placates the technothuds.
The dataset you are talking about is not just in/out but is a lot more comprehensive than that.
I did not say RFID or a mobile phone is biometric information!
I was saying that such datasets can be matched up to another dataset that holds individual information and as long as those datasets are seperated in the right way, you can skirt around this whole area and still have the same problem.
But people seem happy to allow that.