Learning desk

MultiAgent EDU StackGather good sources. Teach what matters.
T5TauricResearch/TradingAgentsT5A Man Who Invented Modern AI (Before Everyone Else) – Jürgen Schmidhuber [video]T5GPT-4 finished training four years ago todayT5AI Settles a 25 Year-Old Problem We Left BehindT5What it was like working on LLMs and security at Meta (2022-2026)T5Ask HN: How do you go from writing code to deploying with agents?T5What Happened: OpenAI and HuggingFaceT5Apple says Mac users in China can connect to Alibaba's Qwen AI serviceT5Show HN: Try Benzi – A coding harness/agent beating Claude Code itself on SonnetT5The AI Apocalypse Is HereT3Auto mode is now the default in Claude Code for Pro, Max, and Team plansT5Show HN: Tura – Build agent that uses 80% less token and delivers better resultsT5TauricResearch/TradingAgentsT5A Man Who Invented Modern AI (Before Everyone Else) – Jürgen Schmidhuber [video]T5GPT-4 finished training four years ago todayT5AI Settles a 25 Year-Old Problem We Left BehindT5What it was like working on LLMs and security at Meta (2022-2026)T5Ask HN: How do you go from writing code to deploying with agents?T5What Happened: OpenAI and HuggingFaceT5Apple says Mac users in China can connect to Alibaba's Qwen AI serviceT5Show HN: Try Benzi – A coding harness/agent beating Claude Code itself on SonnetT5The AI Apocalypse Is HereT3Auto mode is now the default in Claude Code for Pro, Max, and Team plansT5Show HN: Tura – Build agent that uses 80% less token and delivers better results
← Dispatches

The LEARN framework for responsible use of generative AI in education: a neuroscience-informed model for problem-based learning

Primary research

#1116

T1new
Topic
unassigned (set during synthesis)
First seen
2026-08-01 07:16:00
Last seen
2026-08-01 07:16:00

Source raw items (1)

  • Semantic Scholar2026-08-01 07:15:27
    The LEARN framework for responsible use of generative AI in education: a neuroscience-informed model for problem-based learning

    In an era of rapid generative artificial intelligence (GAI) integration into education, students are increasingly using these tools not merely as learning aids but as their primary means for completing assessments. This shift raises significant concerns regarding academic integrity, cognitive offloading, and the erosion of critical thinking. To address these challenges, this paper advances a conceptual, neuroscience-informed framework, the Lifelong Learning, Engagement, Active Processing, Reflection, and Neuro-based Design (LEARN) model, for the ethical and pedagogically grounded integration of GAI into assessment contexts. Grounded in over two decades of experience with problem-based learning (PBL), the framework emphasises learner autonomy, adaptability, and sustained cognitive engagement. The LEARN framework synthesises principles from cognitive and educational neuroscience with constructivist learning theory to explain how learning processes such as neuroplasticity, effortful cognition, metacognitive regulation, and socio-emotional engagement can be intentionally supported in AI-mediated environments. Each component positions GAI as a cognitive scaffold rather than as a cognitive substitute, encouraging critical evaluation, reflective judgement, and ethical self-regulation. By integrating neuroscience-informed learning design, PBL pedagogy, and responsible AI use, the LEARN framework contributes a theoretically grounded model for redesigning assessment practices that sustain deep, self-directed, and reflective learning in the context of generative AI.