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arXiv · 2605.13906

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

Yimeng Sun·Haiyang Xin·Shuang Li·Qiannan Niu·Ching Sing Chai·Lingyun Huang·Gaowei Chen
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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.

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Yimeng Sun, Haiyang Xin, Shuang Li, Qiannan Niu, Ching Sing Chai, Lingyun Huang, Gaowei Chen. 2026-05-13. Modeling AI-TPACK in Practice Insights from Teachers Multi-Agent Workflow Design. https://arxiv.org/abs/2605.13906

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