Author Information
Ivy Chia, Singapore University of Social Sciences, SingaporeJune Tay, Singapore University of Social Sciences, Singapore
Ma Nang Laik, Singapore University of Social Sciences, Singapore
Abstract
This exploratory study examined the usability and pedagogical potential of STEP-AI, a text- based chatbot designed to scaffold student learning. Initial findings reveal consistently positive ratings for the chatbot in terms of accessibility, communication clarity, and educational support. STEP-AI also demonstrated alignment with key educational principles. These include structured progression, tailored feedback, active engagement and progressed learning. However, areas such as privacy communication and contextual adaptability are areas which could be strengthened for improvement. Limitations of the study include a small sample size, use of a pilot version, and the absence of multimedia features. As development continues, future research should include broader testing with diverse learners across authentic educational settings to evaluate STEP-AI's effectiveness, scalability, and relevance to evolving educational needs.
Paper Information
Conference: PCE2025Stream: Design
This paper is part of the PCE2025 Conference Proceedings (View)
Full Paper
View / Download the full paper in a new tab/window
To cite this article:
Chia I., Tay J., & Laik M. (2025) Elevating Postgrad Learning: A New Chatbot Instructional Model ISSN: 2758-0962 The Paris Conference on Education 2025: Official Conference Proceedings (pp. 569-579) https://doi.org/10.22492/issn.2758-0962.2025.43
To link to this article: https://doi.org/10.22492/issn.2758-0962.2025.43
Comments
Powered by WP LinkPress