Could Algorithms Replace Teachers? | eLearningInside News

Teachers are far from perfect. Ask any parent with school-age children, and they will soon start to share stories about unfair and inaccurate grading, negligence, and poor communication. Most students, even those in elementary school, are also happy to share stories about teachers who fail to meet the grade. Human teachers, it seems, are the target of a great deal of criticism, and this means that the idea of replacing them with algorithms naturally has at least some widespread support. After all, if we could replace human teachers, would we not also eliminate their errors, subjective biases, and oversights and better yet, find a way to tailor each educational experience to ensure that every child is getting exactly what he or she needs to excel?

Theoretically, this is true, but there is one problem. For every awful teacher, there are many teachers who are inspiring, supportive, and transformative. Yes, we all have memories of teachers we despised but also teachers who touched our lives in lasting ways. The future of teaching, then, appears to rest on the ability to harness new technologies in a manner that will permit teachers to spend more time doing what they do best and less time doing what they sometimes don’t do very well at all.

As a variety of robust learning management systems have already shown, there are things that algorithms can do that teachers cannot. For example, compare a university professor to the Canvas learning management system. For years, university professors have struggled to police whether or not students are doing their assigned readings, and they have relied on various methods from quizzes to probing in-class questions to weekly summaries to do so. Then, Canvas arrived. If a professor posts readings on the platform, it is possible to not only see which students have opened up the reading and when (yes, anyone who now opens the readings only three minutes before the start of class is now fully exposed) but also how long…

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