I’m trying to be a little more deliberate about my learning. That’s why I’ve recently completed Barbara Oakley’s Learning How to Learn course on Coursera. I heard about it a while back. I’ve only now come around to doing it as I’m having to learn a lot, fast, to ensure that Subset keeps making progress.
The course is short, sweet and offers some simple to leverage (and easy to overlook) ideas. One of those is a recommendation to impose lightweight recall and reflection structures after a learning session and after a larger learning milestone. So, I’ve created a basic retro template to use after I complete a learning milestone. This is that.
- Summary
- Effective learning is the habitualised, process-orientated practice of chunk creation over time. It uses rapid behavioural cycles (focus, understand, recall, practice) and mutable habits (cues, routines, rewards, beliefs), is built atop a structured undulation between focused and diffuse modes of attention at both the macro and micro level, and leverages human being’s inherent embodiment to optimise storage and retrieval within our dynamic first brain apparatus.
- Key takeaways
- Effective learning is the accumulation of chunks; chunks are compressed, dense info units.
- Cycle through tight loops of focus, understanding, recall and practice to build chunks.
- Habits are made up of cues, routines, rewards and beliefs, all of which are mutable.
- We are embodied and learning performance is boosted when we leverage our embodiment.
- Creativity and expertise is akin to storage and retrieval of multi-disciplinary chunks over time.
- Index on the process of learning, not the outcome, at the micro level.
- Switch between focus and diffuse modes of attention in a structured way at the macro level.
- Applications
- Brings attention to the necessity of structures and processes that support learning.
- Provides pragmatic recommendations for using these structures sustainably over time.
- Questions and gaps
- How does effective learning for first brains interop with second brain structures and emerging AI technologies?
- How does one implement double loop learning—monitoring of system/loop effectiveness itself—to any implemented learning structures and processes?
- Next steps
- DONE: Create a retro template for use upon the completion of salient learning outcomes.
- TODO: Utilise Learning How to Learn approaches whilst engaged in daily reading.
- Reflection
- Rate understanding of topic from 1-5 (least to most)
- 4/5
- Describe in 2-3 sentences how this learning connects to existing knowledge
- It provides a simple and lightweight way for me to enhance a bunch of my existing activities and realise additional value over time. The most obvious and immediate areas of application are for reading, Brazilian jiu-jitsu and Subset—all things that require me to learn a lot, fast.
- Rate understanding of topic from 1-5 (least to most)
- Log
- DONE: Post retro to Swell & Cut.
- TODO: Add learning unit to msweet.net.
Here’s the current template at the time of this post, in case you’d like to use or fork it.
- Summary
- Insert 2-3 sentence compression / distillation
- Key takeaways
- Add 5-7 key points or insights
- Applications
- Specify 1-2 ways that learnings can be leveraged
- Questions and gaps
- Note questions that arose and gaps noticed whilst learning
- Next steps
- Capture 1-2 actions that reinforce / expand the learnings
- Reflection
- Rate understanding of topic from 1-5 (least to most)
- Describe in 2-3 sentences how this learning connects to existing knowledge
- Log
- Post retro to *insert relevant blog/feed/channel*
- Add learning unit to *insert relevant portfolio or artefacts*
Alongside the retro, I’m also capturing a link to the learning unit itself, a short description, and loosely structured date-timed notes for each session or engagement.
Swell & Cut 