AI in Education (and its Ethics) | Solomon Ray | 8 Min Read

February 9, 2023 (This article is republished from ET Magazine, Volume 1, Issue 2)

The mention of technology and the classroom evokes pandemic-era remote learning, disengaged human interaction and unequal access to hardware and software tools. What belies this is the growing trend of AI in education. As with previously mentioned technologies, AI is an agnostic tool whose impact greatly depends on policies and implementations surrounding it.

Artificial Intelligence is the ability of machines to work and think like the human brain. Within AI, Machine Learning is the study of algorithms that learn from examples and experiences. As data becomes more complex, Machine Learning is able to identify patterns and apply them to future predictions. Furthermore, Deep Learning is a sub-field of machine learning that uses different layers to learn from data. In Deep Learning, the learning phase is done through a neural network, an architecture where the layers are stacked on top of each other.

Functionally, AI excels in reducing repetitive tasks incredibly fast but is no replacement for the human brain, which learns and adapts from native cognitive processes. In education, there are known methods that improve natural learning.

  • Individualized learning: More attention paid to a student will better understand his or her learning needs. A curriculum can be tailored to that learning style.
  • Immediate feedback: Understanding why a question is right or wrong reinforces specific concepts. Students benefit greatly from targeted improvements.
  • Making connections: Teaching methods incorporating students’ experiences give deeper and more meaningful lessons. Real-life connections not only make learning interesting and relevant, but also give students the opportunity to ponder the actual implications of an idea or concept.

Fortunately, AI supports each of these educational methods with some very common applications:

Personalization: In industries such as retail, healthcare and high-tech, personalization delivers relevant product recommendations, the correct medications based on one’s medical history, and the right streaming movie at the right time. Similarly, personalization in education could adapt to each student’s learning style and needs. While it is overwhelmingly for one teacher to understand all his or her students deeply, AI can personalize learning based on data points such as a student’s grades, strengths, weaknesses, interests, and hobbies.

Adaptive learning: AI algorithms are only as good as the data fed into them. Not only can AI identify concepts where an individual student is struggling based on his or her performance,…

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ET Magazine column

(ET) Magazine is dedicated to providing the information and context necessary to advance the efficacy of technology used in education. Our articles are carefully selected by our editorial advisory board and are written by the finest minds in the world of EdTech. Staff members have been assembled from the fields of education and publishing (and in most cases, both) and represent decades of unassailable dedication.