Abstract: The innovative development of AI technology provides new possibilities and new solutions to the problems that we are facing in modern society. Student well-being status has been a major concern in well-being care, especially in the post-pandemic era. The availability and quality of well-being support have limited the accessibility of well-being resources to students. Using conversational agents (CA) or chatbots to empower student well-being care is a promising solution for universities, considering the availability and cost of implementation. This research aims to explore how CAs assist students with possible well-being concerns. We invited 96 participants to fill out surveys with their demographic information and 11 short answer questions concerning their well-being and their acceptance and expectations of CAs. The results suggested the participants accepted the use of well-being CAs with ethical concerns. Upon user acceptance, the participants expressed expectations on design features such as facial expression recognition, translation, images, personalized long-term memory, etc. Based on the results this work presents a conceptual framework and chat flows for the design of a student well-being chatbot, which provides a user-centered design example for UX designers of wellbeing. Further research will introduce detailed design discoveries and a high-fidelity CA prototype to shed light on student well-being support applications. Implementing the CA will enhance the accessibility and quality of student well-being services, fostering a healthier campus environment.

Jieyu Wang, Li Zhang, Dingfang Kang and Katherina G. Pattit, “Designing Conversational Agents for Student Wellbeing” International Journal of Advanced Computer Science and Applications(IJACSA), 15(10), 2024. http://dx.doi.org/10.14569/IJACSA.2024.0151006

@article{Wang2024,
title = {Designing Conversational Agents for Student Wellbeing},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0151006},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0151006},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {10},
author = {Jieyu Wang and Li Zhang and Dingfang Kang and Katherina G. Pattit}
}