Generative AI: “Tutor” for everyone?

I came across this:

One AI Tutor Per Child: Personalized learning is finally here | by Sai Gaddam | Mar, 2023 | Medium

We are creating map memorizers, when the world needs explorers.

This is not a recent realization [2]. We’d obviously love for all learners to high five each other at the summit. But translating these ideals into daily practice is tough. Great teachers are just good at this sort of thing. They can assess where a particular student’s interests and knowledge gaps are and artfully construct bridges to steer their understanding. Unfortunately, great teachers do not scale.

To add to this, this mode of active learning is devilishly difficult with large student-teacher ratios. This calls for small sizes where empowered teachers are able to actively engage one-on-one in small group settings. This in turn means it cannot be replicated easily without greatly increasing costs.

The author is pushing his concept of teaching:

Consider this example: How do we teach kids about place value notation? We take something that took humanity over 40,000 years to invent and decide that a first grader should learn this highly abstract idea in about a month!

Attempting to teach this abstraction without anchoring it in any context will inevitably lead to the rote learning basement of the pyramid.

What if, instead, we could make it more playful?

First, realise that these are classical pitches. Establish your bonafides. Give a historical context; better still, ideas around “evolution” and “humanity”. Then sprinkle more “research-fairy dust”. Boom! You have a medium post to define the “product”.

Once you have applied the reductionist principles, understand that traditional methods of teaching have some “measurable outcomes”. Generative learning (or defining pedagogical outcomes) is incredibly complex. Language skills, working as part of the teams, and creating some sense of curiosity are all required with the basic approach. Humans tend to follow others only if there is credibility to the process.

Generative AI (even using “playful” methods or through “tech-start-ups”) requires careful deliberation. Psychology, itself, is an inexact science, and neuroscience borders on abstractive domain that will inherently sound plausible each time you read it.

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