The reframe is meant to fit the solution you’ve described and your supporting arguments so that there is clarity on what you’re trying to accomplish and subsequent discussion and iteration can be understood in that reframed context.
I say this because I believe that the definition of learning is much simpler yet much broader than what you’ve described here. For example,
You can model learning as consisting of 6 factors—Content, Knowledge Representation, Navigation, Debugging, Emotional Regulation, and Consolidation.
Does not hold true if you were to hold it up to the representation of learning that we base much of our work off of at Brainly. Our definition is very simple—learning is the process of connecting information not known, to information that is known. We can present the same information to many different individuals and get many different “things” learned based on what they already know.
However, it does hold true when we think about applying a delivery of information for the learner with a specific goal in mind for what that learner should learn. We call that teaching and it requires having clarity on outcomes so they can be assessed and gaps in the learner’s knowledge filled in to ensure the goal is met.
At the end of the day, I am probably being a bit too philosophical about this for a comments section but I hope this perspective is helpful in some way in shaping your own views about the topic.
I think I agree this might be more a matter of semantics than underlying world model. Specifically:
Bill.learning = “process of connecting information not known, to information that is known”
Shoshannah.learning = “model [...] consisting of 6 factors—Content, Knowledge Representation, Navigation, Debugging, Emotional Regulation, and Consolidation.” (note, I’m considering a 7th factor at the moment: which is transfer learning. This factor may actually bridge are two models.)
Bill.teaching = “applying a delivery of information for the learner with a specific goal in mind for what that learner should learn”
Shoshannah.teaching = [undefined so far], but actually “Another human facilitating steps in the learning process of a given human”
---
With those as our word-concept mappings, I’m mostly wondering what “learning” bottoms out to in your model? Like, how does one learn?
One way to conceptualize my model is as: Data → encoding → mapping → solution search → attention regulation → training runs
And the additional factor would be “transfer learning” or I guess fine-tuning (yourself) by noticing how what you learn applies to other areas as well.
And a teacher would facilitate this process by stepping in an providing content/support/debugging for each step that needs it.
I’m not sure why you are conceptualizing the learning goal as being part of the teacher and not the learner? I think they both hold goals, and I think learning can happen goal-driven or ‘free’, which I think is analoguous with the “play” versus “game” distinction in ludology—and slightly less tightly analoguous to exploration versus exploitation behavior.
The reframe is meant to fit the solution you’ve described and your supporting arguments so that there is clarity on what you’re trying to accomplish and subsequent discussion and iteration can be understood in that reframed context.
I say this because I believe that the definition of learning is much simpler yet much broader than what you’ve described here. For example,
Does not hold true if you were to hold it up to the representation of learning that we base much of our work off of at Brainly. Our definition is very simple—learning is the process of connecting information not known, to information that is known. We can present the same information to many different individuals and get many different “things” learned based on what they already know.
However, it does hold true when we think about applying a delivery of information for the learner with a specific goal in mind for what that learner should learn. We call that teaching and it requires having clarity on outcomes so they can be assessed and gaps in the learner’s knowledge filled in to ensure the goal is met.
At the end of the day, I am probably being a bit too philosophical about this for a comments section but I hope this perspective is helpful in some way in shaping your own views about the topic.
Thank you for the clarification!
I think I agree this might be more a matter of semantics than underlying world model. Specifically:
Bill.learning = “process of connecting information not known, to information that is known”
Shoshannah.learning = “model [...] consisting of 6 factors—Content, Knowledge Representation, Navigation, Debugging, Emotional Regulation, and Consolidation.” (note, I’m considering a 7th factor at the moment: which is transfer learning. This factor may actually bridge are two models.)
Bill.teaching = “applying a delivery of information for the learner with a specific goal in mind for what that learner should learn”
Shoshannah.teaching = [undefined so far], but actually “Another human facilitating steps in the learning process of a given human”
---
With those as our word-concept mappings, I’m mostly wondering what “learning” bottoms out to in your model? Like, how does one learn?
One way to conceptualize my model is as:
Data → encoding → mapping → solution search → attention regulation → training runs
And the additional factor would be “transfer learning” or I guess fine-tuning (yourself) by noticing how what you learn applies to other areas as well.
And a teacher would facilitate this process by stepping in an providing content/support/debugging for each step that needs it.
I’m not sure why you are conceptualizing the learning goal as being part of the teacher and not the learner? I think they both hold goals, and I think learning can happen goal-driven or ‘free’, which I think is analoguous with the “play” versus “game” distinction in ludology—and slightly less tightly analoguous to exploration versus exploitation behavior.
I’m curious if you agree with the above.