Teaching and Learning Faculty Publications and Presentations
Document Type
Article
Publication Date
2025
Abstract
This study explored graduate students’ perceptions of an AI-powered chatbot integrated into an online education course, guided by Moore’s (1997) Theory of Transactional Distance. A total of 47 students completed a survey assessing Dialogue, Structure, Learner Autonomy, Satisfaction, Perceived Achievement, and Intent to Continue Use. Regression analyses revealed that all three transactional distance dimensions significantly predicted student satisfaction, with Dialogue as the strongest predictor. Dialogue and Structure were significant predictors of perceived achievement, while Learner Autonomy significantly predicted students’ intention to use chatbots in future courses. Qualitative responses reinforced these findings, emphasizing the chatbot’s helpfulness and responsiveness. Overall, results suggest that AI chatbots can serve as effective tools to reduce transactional distance and enhance student engagement in online learning environments.
Recommended Citation
Corbeil, J. R., & Corbeil, M. E. (2025). Reducing transactional distance with AI: Examining the role of chatbots in online student satisfaction and achievement. Issues in Information Systems, 26(4), 195-208. https://doi.org/10.48009/4_iis_2025_117
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Publication Title
Issues in Information Systems
DOI
10.48009/4_iis_2025_117
Comments
Copyright the Authors. Licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.