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

TL;DR

This study explores teachers' design behaviors and cognitive factors in creating multi-agent instructional workflows, revealing diverse archetypes and the complex emergence of AI-TPACK integration.

Contribution

It identifies distinct teacher archetypes and highlights the dynamic interplay of systems thinking, beliefs, and self-efficacy in AI-TPACK development.

Findings

Three archetypes of teachers: Systematic Optimizers, Prolific Creators, Passive Observers.

AI-TPACK integration results from interplay of systems thinking, beliefs, and self-efficacy.

Differentiated scaffolding needed for diverse cognitive-behavioral profiles.

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.