Jul 2019
22 Mon
23 Tue
24 Wed
25 Thu 09:15 AM – 05:45 PM IST
26 Fri 09:20 AM – 05:30 PM IST
27 Sat
28 Sun
Nilesh Trivedi
I have been actively learning new things (beyond what was required for my formal education) since I was a teenager. A few things I have learned in this time are: mathematics, engineering, economics, philosophy, public speaking, a dozen or so musical instruments, a dozen or so programming languages). But the list of things I am yet to learn is not getting any shorter. I realized that I had to get better at learning itself, and started reading about research from cognitive science. I started exploring mathematics with my toddler which forced me to think deeply about how we learn and how we can get better at it.
After almost a decade of doing this, I started building a personalized system for learning anything in the optimal manner. This involves ideas like spaced repetition systems, chunking, meta-cognition. This system heavily relies on data (in particular, links to good pedagogical content) and the relationships between them (i.e. taxonomy & concept graph). I incorporated ideas from psychology (gamification, learning styles) and data science (summarization, recommendation) so that this knowledge discovery platform allows you to understand any topic through most efficient paths.
In this talk, I will explain the architecture of this personalized learning platform.
I have been learning things deeply and making things for almost 15 years now. I completed dozens of hard MOOCs in mathematics, computer science, economics, psychology etc. I have used this knowledge to build useful things - be it music, apps, electronic/robotic appliances (like automatic portable roti making machine) or DIY-furniture. I have also been exploring mathematics with my 5-year old child, which forced me to think deeply about how people learn and how we can get better at it.
https://docs.google.com/presentation/d/1n-tkTbF1k96wAiAsIl1Tk7B6Co83lSHMV-X9tjry_Nw/edit?usp=sharing
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