Spaced repetition works great for me. Especially because it binds well with a pragmatic approach of professional learning : if I encounter a problem multiple times it is worth it to learn the solution to have it quickly. If I only encounter it once I don't need to.
My process is usually this one :
- Understand learning space ontology. Once I am able to visualize the concepts associated with the field and their relationships, I stop digging the theory and go to practice.
- Start practice: try to solve a simple problem in this learning space. Maximally use all information sources available to solve problems as we go (articles, youtube, wikipedia, blogs, anything). If I get confused I recognize that I missed some theory and go back to square one.
- Solve real use case, go back to step 2 if I get confused or blocked.
I usually get where I need in less than 6 steps. I use this in Software Engineering, Physics and Mathematics.
When I encounter a problem in an Ontolongy space I already encountered, I go directly to step 3.
My process is usually this one :
- Understand learning space ontology. Once I am able to visualize the concepts associated with the field and their relationships, I stop digging the theory and go to practice.
- Start practice: try to solve a simple problem in this learning space. Maximally use all information sources available to solve problems as we go (articles, youtube, wikipedia, blogs, anything). If I get confused I recognize that I missed some theory and go back to square one.
- Solve real use case, go back to step 2 if I get confused or blocked.
I usually get where I need in less than 6 steps. I use this in Software Engineering, Physics and Mathematics.
When I encounter a problem in an Ontolongy space I already encountered, I go directly to step 3.