Precise Education = Model Rationalization -> Experience and Process Engineering ->Adaptive Personalized Instruction -> Effective Learning.
1) Modern education having been created by humans for centuries is an extremely complex and ill-defined system. It is inevitably irrational, underpinned with soft empiric Learning Sciences, interpreted, and used by millions of researchers, professors, and teachers by fighting the ubiquitous uncertainty with their subjective improvisations and guesswork in practice. It cannot reliably provide consistent learning outcomes and form common grounds for effective communication, understanding, and cooperation of people. Organizations and learners try to compensate for it on their own.
2) Old good hope that emerging technologies will solve the educational problems appeared to be always wrong. Technologies can improve presentation, interactivity, delivery, … that is true. But they also can scale up very poor instruction. We all are tired of it.
3) New hope that Learning Engineering will solve all the problems is also wrong. Hard engineering based on soft empiric Learning Sciences, uncertainties, guesswork, and subjective improvisations (as it is happening in e-Learning) may only reinforce them.
4) The latest hope that AI and ML (Machine Learning) is the right solution is wrong as well. They are only tools, not a solution. ML-based models of human instruction are not readable, interpretable, and understandable by humans. That is why they can be easily used by bad guys for cheating customers and faking instructional processes. It is already happening.
5) What is required is the Rationalization of Education with readable and interpretable formal models understandable by humans first and used by computers for operations under human control.
6) Rationalization should create a solid foundation for Precise Education by the synergy of hard Sciences and soft Learning Sciences, minimizing uncertainty, improvisations, and guesswork in educational practice. It should empower Human Intelligence (Intelligence Augmentation), not replace it with AI and ML, which is out of control.
7) Namely Rationalization allowed us, at iTutorSoft, to simplify, clarify, unify, formalize, algorithmize, code, integrate, and scale up the most effective Adaptive Learning with our latest AWS cloud-based Platform and Services.
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