My main goal is to use cognitive modeling to evaluate the efficacy of interventions and inform the personalized "minimum effective dose" for a particular learner. Academically, this is well-trodden territory [0-2] but these results haven't found there way into practice. This is critically important because we know that ~30% of children will learn to read regardless of method, ~50% require explicit, systematic instruction, ~15% require prolonged explicit and systematic instruction, and up to 6% have severe cognitive impairments that make acquiring reading skills extremely difficult [3]. Yet, how much is enough?
To make this more concrete, imagine you are learning a foreign language with Duolingo. How much effort per day is necessary to achieve that? Many people have long streaks and are no closer to fluency (I learned nearly nothing despite a 400 day streak). Similarly, many reading interventions are once-a-week and, predictably, don't meaningfully affect the learning outcomes for those students.
BTW, this ML portion is part of a much larger effort (e.g., our team is a Phase II finalist in the Learning Engineering Tools Competition). If anyone is interested in collaborating, please feel free to reach out to me.
[3] Education Advisory Board. (2019). Narrowing the Third-grade Reading Gap: Embracing the Science of Reading, District Leadership Forum: Research briefing
Don’t get me wrong I think your work is really cool and a worthy cause, but surely the literacy crisis is a socio-economic problem not a technological one.
> surely the literacy crisis is a socio-economic problem not a technological one.
Yes and no. It is, of course, not strictly a technological one, but the argument that it is a socio-economic one is, at best, an oversimplification. If you are interested in a more complete understanding, I highly recommend checking out APM's documentaries on this issue (https://features.apmreports.org/reading/).
From my research, the underlying causes of the literacy crisis are:
1. The mistaken belief that reading, like speaking, is biologically natural. This belief manifests as guidance to surround your child with books and read to them. Unfortunately, this isn't sufficient for the majority of children.
2. The majority of teachers lack the content knowledge to teach children to read. For example, imagine helping a child to sound out the word "father". What is the sound of the second letter? It isn't a short 'a' nor a long 'a'.
3. Many popular programs used in schools are completely debunked by science (e.g., cueing theory), but as a teacher it is difficult to identify that your approach is faulty. (If ~30% of children learn regardless of method, it is too easy to offer excuses for why the other children don't learn).
4. Helping a struggling child is "rich man's game". If you are high SES and your child is struggling, you will pay a tutor to rectify the problem. That isn't an option for the vast majority of families.
In other words, this is a highly complex puzzle and it is completely understandable why society is seemingly no closer to solving it :). Consequently, the majority of our effort is directed at understanding these root causes and identifying how to overcome them (FWIW, we have made significant progress here). The cognitive modeling portion is a small but plausibly important part of the larger landscape.
It depends how far down the rabbit hole you want to go :). I highly recommend checking out APM's documentaries on this issue (https://features.apmreports.org/reading/). These are in-depth and accessible.
If you want to go further, you can read Moat's Speech to Print, Seidenberg's Language at the Speed of Sight, and many others. If you want to go even deeper, then welcome to the firehose that is educational research :D.
My main goal is to use cognitive modeling to evaluate the efficacy of interventions and inform the personalized "minimum effective dose" for a particular learner. Academically, this is well-trodden territory [0-2] but these results haven't found there way into practice. This is critically important because we know that ~30% of children will learn to read regardless of method, ~50% require explicit, systematic instruction, ~15% require prolonged explicit and systematic instruction, and up to 6% have severe cognitive impairments that make acquiring reading skills extremely difficult [3]. Yet, how much is enough?
To make this more concrete, imagine you are learning a foreign language with Duolingo. How much effort per day is necessary to achieve that? Many people have long streaks and are no closer to fluency (I learned nearly nothing despite a 400 day streak). Similarly, many reading interventions are once-a-week and, predictably, don't meaningfully affect the learning outcomes for those students.
BTW, this ML portion is part of a much larger effort (e.g., our team is a Phase II finalist in the Learning Engineering Tools Competition). If anyone is interested in collaborating, please feel free to reach out to me.
[0] Phonology, reading acquisition, and dyslexia: insights from connectionist models (https://pubmed.ncbi.nlm.nih.gov/10467896/)
[1] Modeling the successes and failures of interventions for disabled readers. (https://www.researchgate.net/publication/243777699_Modeling_...)
[2] Learning to Read through Machine Teaching (https://arxiv.org/abs/2006.16470)
[3] Education Advisory Board. (2019). Narrowing the Third-grade Reading Gap: Embracing the Science of Reading, District Leadership Forum: Research briefing