One finding of the recent SCALE Initiative at Stanford University report in AI in K12 education was that “most discussions about AI in education focus on new tools, predictions about the future, or opinions about what schools should do next”.
Further they found most studies look at
❌ “short-term outcomes rather than long-term learning”
and that
❌ “fewer studies examine how educators use AI in their work“.
Into that context, I offer my paper on teaching and learning with AI:
Full article: The Bubble and Burner model of AI-infusion: a framework for teaching and learning
Published this week via National Institute of Education, Singapore‘s journal Learning: Research and Practice and Taylor & Francis Group, it draws upon CLT, the Dreyfus Skill Model, and the Brain-To-LLM findings of MIT Media Lab‘s team led by Nataliya Kosmyna, Ph.D.
Disrupted History 