English

Modeling AI-TPACK in Practice Insights from Teachers Multi-Agent Workflow Design

Computers and Society 2026-05-15 v1

Abstract

This study investigates teachers design behaviors and cognitive underpinnings when designing multi-agent instructional workflows. Analyzing behavioral logs (N=61), cluster and Markov analyses identified three archetypes: Systematic Optimizers iteratively refining complex architectures; Prolific Creators rapidly prototyping pragmatic tools via scaffolding; and Passive Observers exhibiting polarized expert-novice profiles. Subsequent artifact (n=15) and interview (n=12) analyses reveal AI-TPACK integration emerges from a dynamic interplay of systems thinking, pedagogical beliefs, and self-efficacy, not merely from the possession of discrete knowledge. These findings call for differentiated scaffolding responsive to teachers cognitive-behavioral diversity.

Keywords

Cite

@article{arxiv.2605.13906,
  title  = {Modeling AI-TPACK in Practice Insights from Teachers Multi-Agent Workflow Design},
  author = {Yimeng Sun and Haiyang Xin and Shuang Li and Qiannan Niu and Ching Sing Chai and Lingyun Huang and Gaowei Chen},
  journal= {arXiv preprint arXiv:2605.13906},
  year   = {2026}
}
R2 v1 2026-07-22T07:10:50.972Z