Basically I see three main directions:
A) The natural conversational interface with callbacks to earlier in conversation sets up the precursor for widespread customised oral exams.
At least for serious learners, this is a genuine way to test skills despite AI cheating options, and harbours potential for skill upkeep too[1]. I have been predicting this for a long time now(2015+) and at recent tech conferences, it's became clear this is beginning to happen.
B) Personalised addressing of knowledge gaps and interest can both improve motivation and success for students. An AI tutor can now robustly head towards Blooms 2-sigma effect for learning (i.e. that private/small group learning is much more effective than class-wide learning, largely due to adaptivity). The larger potential is to do class-wide work which you identify wide misunderstandings (e.g. like Vertiasium' channels PhD dissertation on using videos with misconceptions to teach better), and enable students to tackle them together[2].
C) Use of AI to use a students understanding of one topic/area (such ideas from a game they love like Red Alert 2) to teach another one(like how cells interact with threats). Things like using comparisons, metaphors. This can be truly powerful for certain student groups.
An alternative here is using image generation AI to show certain concepts on a rolling, scroll-to-see kind of basis to try and loop into that human psychology. I was too early with this as I spent a lot of time with GANs/early Diffusion when the tech was a bit naff. I did win 2nd place on a Cohere Hackathon with "Learn Visually" which explored spatially-aligned AI generated images, but like said, that was before the real revolution, so the quality wasn't quite there.
[1] One of my controversial opinions is that most people are capable of 2-sigma+ performance on many skills, but fail to upkeep their knowledge or tackle problems regularly enough to ever obtain it, instead tackling problems repetitively or with cognitively-easy techniques, giving us a distorted view on human potential. Summer is particularly damaging.
[2] Because of social pressures to work and compete
At least for serious learners, this is a genuine way to test skills despite AI cheating options, and harbours potential for skill upkeep too[1]. I have been predicting this for a long time now(2015+) and at recent tech conferences, it's became clear this is beginning to happen.
B) Personalised addressing of knowledge gaps and interest can both improve motivation and success for students. An AI tutor can now robustly head towards Blooms 2-sigma effect for learning (i.e. that private/small group learning is much more effective than class-wide learning, largely due to adaptivity). The larger potential is to do class-wide work which you identify wide misunderstandings (e.g. like Vertiasium' channels PhD dissertation on using videos with misconceptions to teach better), and enable students to tackle them together[2].
C) Use of AI to use a students understanding of one topic/area (such ideas from a game they love like Red Alert 2) to teach another one(like how cells interact with threats). Things like using comparisons, metaphors. This can be truly powerful for certain student groups.
An alternative here is using image generation AI to show certain concepts on a rolling, scroll-to-see kind of basis to try and loop into that human psychology. I was too early with this as I spent a lot of time with GANs/early Diffusion when the tech was a bit naff. I did win 2nd place on a Cohere Hackathon with "Learn Visually" which explored spatially-aligned AI generated images, but like said, that was before the real revolution, so the quality wasn't quite there.
[1] One of my controversial opinions is that most people are capable of 2-sigma+ performance on many skills, but fail to upkeep their knowledge or tackle problems regularly enough to ever obtain it, instead tackling problems repetitively or with cognitively-easy techniques, giving us a distorted view on human potential. Summer is particularly damaging.
[2] Because of social pressures to work and compete