Comparative Analysis of Dialogic Patterns between Human and AI Tutors in Online Learning Contexts

• In Event: Human–AI Collaboration in Learning: Dialogue, Inquiry, and Facilitation Patterns

Abstract

The present study investigates how adult learners engage in interactive dialogue with human versus AI tutors in online learning environments. In this non-face-to-face context, we examine 1,000 online tutoring encounters to explore how learners initiate conversation, participate in interaction, co-construct meaning, and, importantly, attempt to establish relationships with their tutors (or not). Grounded in sociocultural learning theory and discourse analysis, our findings highlight clear differences in responsiveness, emotional expression, scaffolding strategies, and learner agency. Human tutors foster rapport through adaptive questioning, affective presence, and conversational flexibility. In contrast, AI tutors display high-speed, structured interactions that promote self-regulation. These contrasts underscore the need to revisit human-computer interaction in AI-mediated environments to better support values of equity, emotional connection, and learner autonomy.

Authors

• So-Yeon Ahn, KAIST

• Suin Kim, Elice

• Jieun Han, Korea Advanced Institute of Science and Technology

• Junyeong Park, Korea Advanced Institute of Science and Technology

• Alice Oh, Korea Advanced Institute of Science and Technology