Abstract Online education has been growing in demand over the years. However, online learners frequently experience social isolation, which negatively impacts their learning experience and outcome. In this chapter, we investigate the design space of social matching systems to help foster social connections among online learners. Specifically, we seek to answer three core design questions: (1) What data should be collected? (2) How to design technology to support students’ interactions with one another? (3) What are students’ concerns about the ethics of AI-mediated social matching? We begin by exploring the feasibility, design, and concerns of AI-mediated social interactions through existing literature. We then present our ongoing work on the design and use of AI conversational agents as social matching systems in the online learning context. Finally, we outline future directions for research on designing human-centered social matching systems in online learning.
Citation
Wang, Q. , Camacho, I. & Goel, A.K. ( 2021). Examining the Design Space of AI-Mediated
Social Matching Among Online Learners. To appear in Social and Emotional Learning- An Inclusive Learning Analytics Perspective, edited by Elle Wang et al, Springer 2021.
