InBloom, a data repository currently in development, would
collect information on school students and their academic performance all
throughout their years of grade school. The
data of previous school performance would then assist teachers in how to better
instruct their students, either by shaping lesson plans accordingly or creating
a seating chart which would spread out the “good” and “bad” students. While this development has admirable
aspirations, it runs the risk of creating negative self-fulfilling
prophecies. When a student is labeled as
a “good” or “bad” student from the start of each year, the student may end up carrying
this self-identity throughout grade school. Moreover, if teachers see students in “green,”
“yellow,” or “red” (as inBloom labels them), the teachers may help reinforce
the identity, good or bad. When Albert
Einstein underperformed in his first years of school, would it have been
beneficial to label him as a “RED” student?
I could see this working, if the implemented system kept the students and teachers out of the loop. For example have someone else come up with the seating chart. I guess the teachers wouldn't be able to fully utilize the system then.
ReplyDeleteI agree with this post! I think that way too often, we label people and then they perform according to what that label says about them.
ReplyDeleteOnce there is a large enough data set, InBloom's data will be very valuable...even for those outside of the education industry.
ReplyDelete