Designing Teaching Agents for Human‐
AI
Collaborative Classrooms: A Design‐Based Study of Students' Sense of Presence and Learning Engagement
Mengmeng Qi, Bing Liu, Hongtao Huang, Jixin Wang, Lin Yu, Bowen Liu ABSTRACT
Background
Generative artificial intelligence has expanded the possibilities for teaching agents to provide instructional explanations and feedback. However, limited research has examined how such support can be integrated into teacher‐guided classroom instruction and how students experience and engage with this form of teaching.
Objectives
This study aimed to iteratively design and refine teaching agents within a teacher‐guided undergraduate classroom and to examine changes in students' sense of presence and learning engagement across three design iterations.
Methods
A single‐group design‐based research study was conducted in a 10‐week Introduction to Educational Technology course. 36 first‐year undergraduate students majoring in educational technology participated in three design iterations: gesture‐supported presentation, teacher‐mediated real‐time Q&A, and individualized text‐based Q&A. Data were collected through questionnaires, classroom observations, student feedback, question records, and discussion texts. Repeated‐measures analyses were used to examine changes in students' sense of presence and learning engagement, and epistemic network analysis was used to examine changes in co‐occurrence patterns among presence‐related codes in students' post‐class reflections.
Results and Conclusions
The findings show that students' sense of presence significantly increased across the three iterations, whereas learning engagement did not show a statistically significant change, although the descriptive means showed a small upward pattern. Epistemic network analysis identified changes in co‐occurrence patterns among presence‐related codes in students' post‐class reflections. The strongest connections involved direct instruction, affective expression, and resolution in the first iteration, and affective expression with direct instruction, exploration, and integration in the third iteration. Given the single‐group sequential design, these findings should be interpreted as observed changes during the iterative implementation process rather than causal evidence for the independent effects of specific design strategies. The study contributes process‐oriented evidence and design considerations for integrating teaching agents into teacher‐orchestrated human‐AI collaborative classrooms.