Newsletter 001: The Learning Engine
This is the inaugural issue of the Learning Engine’s newsletter!
(I may or may not continue to post on Medium; if you want to subscribe through your email, visit this link.)
As an introduction, I want to discuss a Model for Learning. I created this model in 2023, using many different sources from 10+ years of study. As with any model, my first goal was to strike the right balance between too much and not enough detail; there are both simpler and more complex models for learning, but this is my best (current) attempt at a model that finds the balance.
In addition to finding the right balance of complexity, I come from a background of teaching high school science — specifically basic and advanced physics courses. Scientific models are best understood as “models for,” giving both explanations and predictions for a given topic. The second goal of the Model for Learning is to be both explanatory and predictive, helping you understand the details for the process of learning AND how to apply those details.
Belcher’s Model for Learning
Take a little time and review the model, answering some questions:
- What makes sense?
- What is challenging?
- What is missing?
- How could this be simplified?
