4 Matching Annotations
  1. Last 7 days
    1. Interesting. I suspect it depends on how you use it. Students with a high level of metacognitive capacity could use this to their advantage. Teaching (particularly the Whole-Part-Whole Reteaching technique) is a very useful technique for active recall (don't forget expanding gap spacing and interleaving); it forces you to use all aspects of your cognitive schemas to provide a clear and understandable explanation of what you know to have others understand it. When you struggle to explain it to others or they ask questions and you cannot answer it (or explain it in different ways) you have identified knowledge gaps.These recall techniques serve not only to strengthen the neural connections between concepts in the cognitive schemata (Hebbian plasticity; re-encoding benefits) but, perhaps more importantly, also to identify knowledge gaps making you know what to focus on when improving your knowledge mastery (maybe even what information to drill, depending on the information type).
  2. Jul 2024
    1. Nishant says: 2x Output for 1x input...

      His formula for mastery: 1. Learn (input -- focus, singletasking) 2. Reflect (output, pause... what is the main takeaway, how to use?) 3. Implement (output, apply) 4. Share (output, teach the material)

      These principles are great... Obviously they are not comprehensive as they do not necessarily reflect higher order learning. See Bloom's and Solo's, nor take foundation of Cognitive Load Theory for example... It's understandable though since you can't mention everything in a 20 minute talk XD.

      The argument I'd make is that the 3 subsequent steps are a part of learning. So the first step should not be called learn but rather encode, since that is literally the process of forming the initial cognitive schemas and putting them into long-term memory...

  3. May 2024
    1. ***Deep Processing***-> It's important in learning. It's when our brain constructs meaning and says, "Ah, I get it, this makes sense." -> It's when new knowledge establishes connections to your pre-existing knowledge.-> When done well, It's what makes the knowledge easily retrievable when you need it. How do we achieve deep processing in learning? 👉🏽 STORIES, EXPLANATIONS, EXAMPLES, ANALOGIES and more - they all promote deep meaningful processing. 🤔BUT, it's not always easy to come up with stories and examples. It's also time-consuming. You can ask you AI buddies to help with that. We have it now, let's leverage it. Here's a microlesson developed on 7taps Microlearning about this topic.

      Reply to Nidhi Sachdeva: I agree mostly, but I would advice against using AI for this. If your brain is not doing the work (the AI is coming up with the story/analogy) it is much less effective. Dr. Sönke Ahrens already said: "He who does the effort, does the learning."

      I would bet that Cognitive Load Theory also would show that there is much less optimized intrinsic cognitive load (load stemming from the building or automation of cognitive schemas) when another person, or the AI, is thinking of the analogies.


    1. Perhaps the best method would be to take notes—not excerpts, but condensed reformulations of what has been read. The re-description of what has already been described leads almost automatically to a training of paying attention to “frames,” or schemata of observation, or even to noticing conditions which lead the text to offer some descriptions but not others.

      Summarization. Building of cognitive schemas.