#metacognition — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #metacognition, aggregated by home.social.
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The more we try to understand what LLMs can and can’t do effectively, the more we’re forced to examine the cognitive processes we’ve traditionally taken for granted in ourselves.
Among many who embrace it, that's leading to greater metacognitive awareness... people becoming more conscious of how they reason, not just what conclusions they reach.
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The more we try to understand what LLMs can and can’t do effectively, the more we’re forced to examine the cognitive processes we’ve traditionally taken for granted in ourselves.
Among many who embrace it, that's leading to greater metacognitive awareness... people becoming more conscious of how they reason, not just what conclusions they reach.
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The more we try to understand what LLMs can and can’t do effectively, the more we’re forced to examine the cognitive processes we’ve traditionally taken for granted in ourselves.
Among many who embrace it, that's leading to greater metacognitive awareness... people becoming more conscious of how they reason, not just what conclusions they reach.
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The more we try to understand what LLMs can and can’t do effectively, the more we’re forced to examine the cognitive processes we’ve traditionally taken for granted in ourselves.
Among many who embrace it, that's leading to greater metacognitive awareness... people becoming more conscious of how they reason, not just what conclusions they reach.
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The more we try to understand what LLMs can and can’t do effectively, the more we’re forced to examine the cognitive processes we’ve traditionally taken for granted in ourselves.
Among many who embrace it, that's leading to greater metacognitive awareness... people becoming more conscious of how they reason, not just what conclusions they reach.
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Does routing to whichever model says it can answer lead to more success? 20 frontier models were asked on six benchmarks whether they could answer w/o help. They mostly agree about which questions are hard, but models saying yes don't necessarily answer more correctly. Counting hedge words in a model's own one-line explanation predicts whether it got the answer right better than its own yes or no does, on half the benchmarks.
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Does routing to whichever model says it can answer lead to more success? 20 frontier models were asked on six benchmarks whether they could answer w/o help. They mostly agree about which questions are hard, but models saying yes don't necessarily answer more correctly. Counting hedge words in a model's own one-line explanation predicts whether it got the answer right better than its own yes or no does, on half the benchmarks.
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Does routing to whichever model says it can answer lead to more success? 20 frontier models were asked on six benchmarks whether they could answer w/o help. They mostly agree about which questions are hard, but models saying yes don't necessarily answer more correctly. Counting hedge words in a model's own one-line explanation predicts whether it got the answer right better than its own yes or no does, on half the benchmarks.
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Does routing to whichever model says it can answer lead to more success? 20 frontier models were asked on six benchmarks whether they could answer w/o help. They mostly agree about which questions are hard, but models saying yes don't necessarily answer more correctly. Counting hedge words in a model's own one-line explanation predicts whether it got the answer right better than its own yes or no does, on half the benchmarks.
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Does routing to whichever model says it can answer lead to more success? 20 frontier models were asked on six benchmarks whether they could answer w/o help. They mostly agree about which questions are hard, but models saying yes don't necessarily answer more correctly. Counting hedge words in a model's own one-line explanation predicts whether it got the answer right better than its own yes or no does, on half the benchmarks.
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L’esprit critique, ça s’apprend ? 2/4, avec Christophe Adourian — SHOCKING #32
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L’esprit critique, ça s’apprend ? 2/4, avec Christophe Adourian — SHOCKING #32
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Podcast News, le média de l’industrie francophone du podcast, s’est fait l’écho de mon appel du week-end dernier pour sauver Méta de Choc, suite à la chute dramatique des dons que subit le podcast depuis le début de cette année 2026 (voir liens en fin de thread). 1/5
#métadechoc #dons #soutien #podcastfr #EspritCritique #scepticisme #métacognition #PenséeCritique
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Podcast News, le média de l’industrie francophone du podcast, s’est fait l’écho de mon appel du week-end dernier pour sauver Méta de Choc, suite à la chute dramatique des dons que subit le podcast depuis le début de cette année 2026 (voir liens en fin de thread). 1/5
#métadechoc #dons #soutien #podcastfr #EspritCritique #scepticisme #métacognition #PenséeCritique
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Podcast News, le média de l’industrie francophone du podcast, s’est fait l’écho de mon appel du week-end dernier pour sauver Méta de Choc, suite à la chute dramatique des dons que subit le podcast depuis le début de cette année 2026 (voir liens en fin de thread). 1/5
#métadechoc #dons #soutien #podcastfr #EspritCritique #scepticisme #métacognition #PenséeCritique
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Podcast News, le média de l’industrie francophone du podcast, s’est fait l’écho de mon appel du week-end dernier pour sauver Méta de Choc, suite à la chute dramatique des dons que subit le podcast depuis le début de cette année 2026 (voir liens en fin de thread). 1/5
#métadechoc #dons #soutien #podcastfr #EspritCritique #scepticisme #métacognition #PenséeCritique
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Méta de Choc survivra-t-il à 2026 ?
La question s’impose malheureusement.
Il y a 7 ans, j’ai décidé de lancer ce podcast indépendant, gratuit et sans pub, exclusivement financé par ses auditeur•ices. Simple, n’est-ce pas ? Et pour me rendre la tâche encore plus facile, j’ai choisi un sujet ultra-mainstream : la métacognition. 1/9
#podcast #SansPub #scepticisme #métacognition #EspritCritique #don
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Méta de Choc survivra-t-il à 2026 ?
La question s’impose malheureusement.
Il y a 7 ans, j’ai décidé de lancer ce podcast indépendant, gratuit et sans pub, exclusivement financé par ses auditeur•ices. Simple, n’est-ce pas ? Et pour me rendre la tâche encore plus facile, j’ai choisi un sujet ultra-mainstream : la métacognition. 1/9
#podcast #SansPub #scepticisme #métacognition #EspritCritique #don
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Méta de Choc survivra-t-il à 2026 ?
La question s’impose malheureusement.
Il y a 7 ans, j’ai décidé de lancer ce podcast indépendant, gratuit et sans pub, exclusivement financé par ses auditeur•ices. Simple, n’est-ce pas ? Et pour me rendre la tâche encore plus facile, j’ai choisi un sujet ultra-mainstream : la métacognition. 1/9
#podcast #SansPub #scepticisme #métacognition #EspritCritique #don
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Méta de Choc survivra-t-il à 2026 ?
La question s’impose malheureusement.
Il y a 7 ans, j’ai décidé de lancer ce podcast indépendant, gratuit et sans pub, exclusivement financé par ses auditeur•ices. Simple, n’est-ce pas ? Et pour me rendre la tâche encore plus facile, j’ai choisi un sujet ultra-mainstream : la métacognition. 1/9
#podcast #SansPub #scepticisme #métacognition #EspritCritique #don
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Méta de Choc survivra-t-il à 2026 ?
La question s’impose malheureusement.
Il y a 7 ans, j’ai décidé de lancer ce podcast indépendant, gratuit et sans pub, exclusivement financé par ses auditeur•ices. Simple, n’est-ce pas ? Et pour me rendre la tâche encore plus facile, j’ai choisi un sujet ultra-mainstream : la métacognition. 1/9
#podcast #SansPub #scepticisme #métacognition #EspritCritique #don
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Socrates worried that writing would damage our memories. We only know about his concern because somebody wrote it down.
Every generation runs this argument. But "people have always worried" is not the same as "there is nothing to worry about". Generative AI can now produce the work itself, not just store it.
The question worth asking is which cognitive work you want to keep doing: https://www.ctnet.co.uk/cognitive-debt-ai-offloading/
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Socrates worried that writing would damage our memories. We only know about his concern because somebody wrote it down.
Every generation runs this argument. But "people have always worried" is not the same as "there is nothing to worry about". Generative AI can now produce the work itself, not just store it.
The question worth asking is which cognitive work you want to keep doing: https://www.ctnet.co.uk/cognitive-debt-ai-offloading/
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Socrates worried that writing would damage our memories. We only know about his concern because somebody wrote it down.
Every generation runs this argument. But "people have always worried" is not the same as "there is nothing to worry about". Generative AI can now produce the work itself, not just store it.
The question worth asking is which cognitive work you want to keep doing: https://www.ctnet.co.uk/cognitive-debt-ai-offloading/
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Socrates worried that writing would damage our memories. We only know about his concern because somebody wrote it down.
Every generation runs this argument. But "people have always worried" is not the same as "there is nothing to worry about". Generative AI can now produce the work itself, not just store it.
The question worth asking is which cognitive work you want to keep doing: https://www.ctnet.co.uk/cognitive-debt-ai-offloading/
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Socrates worried that writing would damage our memories. We only know about his concern because somebody wrote it down.
Every generation runs this argument. But "people have always worried" is not the same as "there is nothing to worry about". Generative AI can now produce the work itself, not just store it.
The question worth asking is which cognitive work you want to keep doing: https://www.ctnet.co.uk/cognitive-debt-ai-offloading/
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Technical debt is a shortcut taken now and paid for later, usually with interest. Cognitive debt works the same way, except the thing you are borrowing against is your own ability to think.
Socrates worried about writing. Maths teachers worried about calculators. Now we are having the argument again about AI, and this time the machine can generate the work for us.
New post: https://www.ctnet.co.uk/cognitive-debt-ai-offloading/
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Technical debt is a shortcut taken now and paid for later, usually with interest. Cognitive debt works the same way, except the thing you are borrowing against is your own ability to think.
Socrates worried about writing. Maths teachers worried about calculators. Now we are having the argument again about AI, and this time the machine can generate the work for us.
New post: https://www.ctnet.co.uk/cognitive-debt-ai-offloading/
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Practice what you teach. Because teachings don't function as symbols or metaphors…they are incarnations of what they advocate.
https://www.conferencesthatwork.com/index.php/learning/2017/05/practice-what-you-teach
#learning #teaching #practice #RecursivePractice #MetaCognition
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Practice what you teach. Because teachings don't function as symbols or metaphors…they are incarnations of what they advocate.
https://www.conferencesthatwork.com/index.php/learning/2017/05/practice-what-you-teach
#learning #teaching #practice #RecursivePractice #MetaCognition
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Practice what you teach. Because teachings don't function as symbols or metaphors…they are incarnations of what they advocate.
https://www.conferencesthatwork.com/index.php/learning/2017/05/practice-what-you-teach
#learning #teaching #practice #RecursivePractice #MetaCognition
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Practice what you teach. Because teachings don't function as symbols or metaphors…they are incarnations of what they advocate.
https://www.conferencesthatwork.com/index.php/learning/2017/05/practice-what-you-teach
#learning #teaching #practice #RecursivePractice #MetaCognition
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Practice what you teach. Because teachings don't function as symbols or metaphors…they are incarnations of what they advocate.
https://www.conferencesthatwork.com/index.php/learning/2017/05/practice-what-you-teach
#learning #teaching #practice #RecursivePractice #MetaCognition
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A line from my latest post that I keep coming back to: AI's neural network is fixed once trained - ours isn't. We evolved to adapt and learn throughout life, it's still one of the few edges we have left.
Full post: https://www.ctnet.co.uk/protect-cognitive-abilities-ai-age/
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A line from my latest post that I keep coming back to: AI's neural network is fixed once trained - ours isn't. We evolved to adapt and learn throughout life, it's still one of the few edges we have left.
Full post: https://www.ctnet.co.uk/protect-cognitive-abilities-ai-age/
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A line from my latest post that I keep coming back to: AI's neural network is fixed once trained - ours isn't. We evolved to adapt and learn throughout life, it's still one of the few edges we have left.
Full post: https://www.ctnet.co.uk/protect-cognitive-abilities-ai-age/
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A line from my latest post that I keep coming back to: AI's neural network is fixed once trained - ours isn't. We evolved to adapt and learn throughout life, it's still one of the few edges we have left.
Full post: https://www.ctnet.co.uk/protect-cognitive-abilities-ai-age/
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A line from my latest post that I keep coming back to: AI's neural network is fixed once trained - ours isn't. We evolved to adapt and learn throughout life, it's still one of the few edges we have left.
Full post: https://www.ctnet.co.uk/protect-cognitive-abilities-ai-age/
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A tip from my latest post: metacognition (thinking about your own thinking) is a meta-skill worth building deliberately.
Three ways in: self-testing, self-explanation, and concept mapping. None of them are complicated, they just need doing consistently.
More here: https://www.ctnet.co.uk/protect-cognitive-abilities-ai-age/
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A tip from my latest post: metacognition (thinking about your own thinking) is a meta-skill worth building deliberately.
Three ways in: self-testing, self-explanation, and concept mapping. None of them are complicated, they just need doing consistently.
More here: https://www.ctnet.co.uk/protect-cognitive-abilities-ai-age/
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A tip from my latest post: metacognition (thinking about your own thinking) is a meta-skill worth building deliberately.
Three ways in: self-testing, self-explanation, and concept mapping. None of them are complicated, they just need doing consistently.
More here: https://www.ctnet.co.uk/protect-cognitive-abilities-ai-age/
-
A tip from my latest post: metacognition (thinking about your own thinking) is a meta-skill worth building deliberately.
Three ways in: self-testing, self-explanation, and concept mapping. None of them are complicated, they just need doing consistently.
More here: https://www.ctnet.co.uk/protect-cognitive-abilities-ai-age/
-
A tip from my latest post: metacognition (thinking about your own thinking) is a meta-skill worth building deliberately.
Three ways in: self-testing, self-explanation, and concept mapping. None of them are complicated, they just need doing consistently.
More here: https://www.ctnet.co.uk/protect-cognitive-abilities-ai-age/
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The final post in my "Why Technology Is Outpacing Society" series is live.
After four posts on why the gap between tech and us keeps widening, I didn't want to end on doom. So this one's about what's actually within our control: protecting our own cognitive abilities.
Read it here: https://www.ctnet.co.uk/protect-cognitive-abilities-ai-age/
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The final post in my "Why Technology Is Outpacing Society" series is live.
After four posts on why the gap between tech and us keeps widening, I didn't want to end on doom. So this one's about what's actually within our control: protecting our own cognitive abilities.
Read it here: https://www.ctnet.co.uk/protect-cognitive-abilities-ai-age/
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The final post in my "Why Technology Is Outpacing Society" series is live.
After four posts on why the gap between tech and us keeps widening, I didn't want to end on doom. So this one's about what's actually within our control: protecting our own cognitive abilities.
Read it here: https://www.ctnet.co.uk/protect-cognitive-abilities-ai-age/
-
The final post in my "Why Technology Is Outpacing Society" series is live.
After four posts on why the gap between tech and us keeps widening, I didn't want to end on doom. So this one's about what's actually within our control: protecting our own cognitive abilities.
Read it here: https://www.ctnet.co.uk/protect-cognitive-abilities-ai-age/
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Détective privée : en quête de vérité 1/3, avec Margaux Duquesne — SHOCKING #29
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Détective privée : en quête de vérité 1/3, avec Margaux Duquesne — SHOCKING #29
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Détective privée : en quête de vérité 1/3, avec Margaux Duquesne — SHOCKING #29
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Des nouvelles du futur - SCOOP #2
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Healing Trauma!
Unlock the secrets to healing trauma! Explore how emotional coherence and metacognition can help you process difficult experiences and transform your identity. Learn how long to feel emotions and when to move forward.
#traumahealing #emotionalhealing #personalgrowth #metacognition #mindfulness #mentalhealth #selfhelp #NeuroFeedback #Neuropathy #NeuroSurgeon #NeuroDiversidade #NeuroPsychology #NeuroSciences #Neurologie #NeuroCoaching #NeuroRehab #wellbeing #innerpeace
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Healing Trauma!
Unlock the secrets to healing trauma! Explore how emotional coherence and metacognition can help you process difficult experiences and transform your identity. Learn how long to feel emotions and when to move forward.
#traumahealing #emotionalhealing #personalgrowth #metacognition #mindfulness #mentalhealth #selfhelp #NeuroFeedback #Neuropathy #NeuroSurgeon #NeuroDiversidade #NeuroPsychology #NeuroSciences #Neurologie #NeuroCoaching #NeuroRehab #wellbeing #innerpeace
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Healing Trauma!
Unlock the secrets to healing trauma! Explore how emotional coherence and metacognition can help you process difficult experiences and transform your identity. Learn how long to feel emotions and when to move forward.
#traumahealing #emotionalhealing #personalgrowth #metacognition #mindfulness #mentalhealth #selfhelp #NeuroFeedback #Neuropathy #NeuroSurgeon #NeuroDiversidade #NeuroPsychology #NeuroSciences #Neurologie #NeuroCoaching #NeuroRehab #wellbeing #innerpeace
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Healing Trauma!
Unlock the secrets to healing trauma! Explore how emotional coherence and metacognition can help you process difficult experiences and transform your identity. Learn how long to feel emotions and when to move forward.
#traumahealing #emotionalhealing #personalgrowth #metacognition #mindfulness #mentalhealth #selfhelp #NeuroFeedback #Neuropathy #NeuroSurgeon #NeuroDiversidade #NeuroPsychology #NeuroSciences #Neurologie #NeuroCoaching #NeuroRehab #wellbeing #innerpeace
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Healing Trauma!
Unlock the secrets to healing trauma! Explore how emotional coherence and metacognition can help you process difficult experiences and transform your identity. Learn how long to feel emotions and when to move forward.
#traumahealing #emotionalhealing #personalgrowth #metacognition #mindfulness #mentalhealth #selfhelp #NeuroFeedback #Neuropathy #NeuroSurgeon #NeuroDiversidade #NeuroPsychology #NeuroSciences #Neurologie #NeuroCoaching #NeuroRehab #wellbeing #innerpeace
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Chatbots vs inline automation and their respective implications for students
In Generative AI for Academics I drew the distinction between conversational agents and templated responses. In the former you interact in natural language with a chatbot through a dialogue, whereas in the latter you select buttons to enact pre-defined transformations to text. This is how I talked about it in a webinar a couple of years ago:
https://youtu.be/GTjd9eLd9cw?si=bGt1KVk2CXKVpQv1&t=2859
Kim et al draw a similar distinction: “Two interaction techniques currently dominate: dialogue (e.g., OpenAI’s ChatGPT and Google’s Gemini) and predictive text completion (e.g., GitHub Copilot)”. I’d suggest that inline automation as found in Microsoft Copilot 365 or Gemini in Google Docs is a development of predictive text completion, in the sense that a user can complete a transformation of text by pushing a button. In both cases the system produces content with the difference being how this production happens: with chatbots it happens through dialogue and with inline automation it happens through pressing a button. If you’re a confident writer who uses chatbots in a purely dialogical way, it’s easy to forget how much chatbot use can be geared towards the production of content. I’d say it’s better educationally in the sense that some articulation is necessary to produce anything from a chatbot. But it’s still outsourcing a task to the machine in a radical way.
The approach developed by Kim et al tries for a third approach which “motivates users to reflect on their text with LLM-generated summaries, questions, and advice on writing (which we refer to as LLM views), helping them discover opportunities for improvement or elaboration”. They offer a useful definition of two stages involved in this process (my emphasis):
Revision means critically examining and evaluating, which we refer to as reflection, and identifying any opportunities for improvement or further development, which we refer to as discovery, and then making the appropriate changes. This can occur at any stage of the writing journey
https://hai-gen.github.io/2024/papers/9904-Kim.pdfThe purpose of their interface is to offer perspectives on the text which scaffold reflection and discovery while avoiding the language model merely producing text directly for the user. They identified three outgrowths in their pilot of the project which are educationally relevant: (1) discovering underdeveloped ideas, (2) catering to their audience, and (3) identifying opportunities to improve clarity.
If we’re going to be using inline automation with students, this suggests how we can do it in a pedagogically responsible way. The purpose is to offer perspectives, taking advantage of how the model is embedded in the office software, rather than predictive text completion. Copilot offers these perspectives which present themselves for educational use. The problem is that (1) they are integrated seamlessly into an interface which is built around inline automation (2) they are not fine tuned for the specific domain so their advice can often be questionable.
But they are nonetheless there, which offers pedagogical opportunities. The key I think is to encourage students to gravitate towards dialogue (using the prompt windows where they are available) and perspectives (using the reflection tools built in) while discouraging them from using the push-button forms of automation. Where these are used, they need to be engaged with thoughtfully: to reflect on why you are selecting this button and to review the consequences of pressing it. The challenge is introducing moments of friction and reflection into software which is fundamentally designed to be frictionless, but it’s not insurmountable I think. Engaging with it educationally in this way though presupposes a lot of critical AI literacy in general and familiarity with Copilot 365 in particular.
#conversationalAgents #copilot #inlineAutomation #metacognition #pedagogy #reflection #teaching -
Chatbots vs inline automation and their respective implications for students
In Generative AI for Academics I drew the distinction between conversational agents and templated responses. In the former you interact in natural language with a chatbot through a dialogue, whereas in the latter you select buttons to enact pre-defined transformations to text. This is how I talked about it in a webinar a couple of years ago:
https://youtu.be/GTjd9eLd9cw?si=bGt1KVk2CXKVpQv1&t=2859
Kim et al draw a similar distinction: “Two interaction techniques currently dominate: dialogue (e.g., OpenAI’s ChatGPT and Google’s Gemini) and predictive text completion (e.g., GitHub Copilot)”. I’d suggest that inline automation as found in Microsoft Copilot 365 or Gemini in Google Docs is a development of predictive text completion, in the sense that a user can complete a transformation of text by pushing a button. In both cases the system produces content with the difference being how this production happens: with chatbots it happens through dialogue and with inline automation it happens through pressing a button. If you’re a confident writer who uses chatbots in a purely dialogical way, it’s easy to forget how much chatbot use can be geared towards the production of content. I’d say it’s better educationally in the sense that some articulation is necessary to produce anything from a chatbot. But it’s still outsourcing a task to the machine in a radical way.
The approach developed by Kim et al tries for a third approach which “motivates users to reflect on their text with LLM-generated summaries, questions, and advice on writing (which we refer to as LLM views), helping them discover opportunities for improvement or elaboration”. They offer a useful definition of two stages involved in this process (my emphasis):
Revision means critically examining and evaluating, which we refer to as reflection, and identifying any opportunities for improvement or further development, which we refer to as discovery, and then making the appropriate changes. This can occur at any stage of the writing journey
https://hai-gen.github.io/2024/papers/9904-Kim.pdfThe purpose of their interface is to offer perspectives on the text which scaffold reflection and discovery while avoiding the language model merely producing text directly for the user. They identified three outgrowths in their pilot of the project which are educationally relevant: (1) discovering underdeveloped ideas, (2) catering to their audience, and (3) identifying opportunities to improve clarity.
If we’re going to be using inline automation with students, this suggests how we can do it in a pedagogically responsible way. The purpose is to offer perspectives, taking advantage of how the model is embedded in the office software, rather than predictive text completion. Copilot offers these perspectives which present themselves for educational use. The problem is that (1) they are integrated seamlessly into an interface which is built around inline automation (2) they are not fine tuned for the specific domain so their advice can often be questionable.
But they are nonetheless there, which offers pedagogical opportunities. The key I think is to encourage students to gravitate towards dialogue (using the prompt windows where they are available) and perspectives (using the reflection tools built in) while discouraging them from using the push-button forms of automation. Where these are used, they need to be engaged with thoughtfully: to reflect on why you are selecting this button and to review the consequences of pressing it. The challenge is introducing moments of friction and reflection into software which is fundamentally designed to be frictionless, but it’s not insurmountable I think. Engaging with it educationally in this way though presupposes a lot of critical AI literacy in general and familiarity with Copilot 365 in particular.
#conversationalAgents #copilot #inlineAutomation #metacognition #pedagogy #reflection #teaching
