Making Chatbots More Inclusive: Addressing Challenges of Non-Native English Speakers With New Technology in MOOCs

• In Event: Addressing Issues of Access and Accessibility With Online Learning Technologies

Abstract

This study examines interaction processes between non-native English-speaking students and a chatbot for MOOCs based on the chatbot log data and self-reported open-ended responses. Operating a multimodal computer-mediated communication and interactional sociolinguistics approach with positioning theory, this study investigates precise language uses and constructional practices that emerged from student-bot interactions to fill the research gap lacking qualitative investigations with chatbots. Most importantly, this study centers on the experience of non-native English students' experience with a newly adopted technology such as chatbots reflecting the fact that while this group represents the majority of MOOCs users, there is less attention paid towards the challenges they face with new technology. The findings produce chatbot response design strategies supporting this group of students better.

Authors

• Songhee Han, University of Texas at Austin

• Min Liu, University of Texas at Austin

• Zilong Pan, Lehigh University

• Ying Cai, University of Texas at Austin

• Peixia Shao, University of Texas at Austin