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Teacher-mentor-AI collaboration as a distributed expertise system in AI technology creation

Design · All designs
Evidence · no claims cited

Description

The article conceptualizes workshop interactions among teachers, mentors, and AI as "a dynamically coordinated system of distributed expertise, grounded in distributed cognition theory". Evidence-based knowledge from mentors, practice-based knowledge from teachers, and generative knowledge from AI are integrated and reconfigured through interaction. AI is treated not merely as a tool but as a mediational artifact that shapes teachers' thinking, as teachers externalize tacit knowledge through prompt writing, prototype demonstration, and output review.

Design Implications

Context

Requirements

  • Mentors providing cognitive, skill, and affective support (explanation, walkthroughs, questioning, strategic and emotional support)

Constraints

  • Conceptualized from one small workshop context; mentor interactions dominated the coded activity

Target Learners

  • K-12 teachers
  • university faculty mentors

Learning Goals

  • Collaborative AI-powered learning technology design
  • Teacher professional learning

Claims

Examples

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Key Sources

  • Song, Y., Choi, S., Kim, J., Kim, Y., Weisberg, L., & Moon, J. (2026). A Guiding Framework for K-12 Teachers in Creating AI-powered Learning Technologies through Vibe Coding. https://x.com/karpathy/status/1886192184808149383
Page metadata
Field Value
type design
id distributed-expertise-teacher-mentor-ai-collaboration
title Teacher-mentor-AI collaboration as a distributed expertise system in AI technology creation
description The article conceptualizes workshop interactions among teachers, mentors, and AI as "a dynamically coordinated system of distributed expertise, grounded in distributed cognition theory".
status review
generated by process:settle-candidates on 2026-10-10
trust unverified — no one has confirmed this page's content
sources 1 — song-2026

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