Support for Language Learners by Designing a Personalized Voice Assistant
Date of Award
9-21-2023
Degree Type
Thesis
Degree Name
Master of Fine Arts (MFA)
Department
Design
Advisor(s)
Don Carr
Keywords
Enjoyment;Foreign Language;Human Computer Interaction;User Experience;Voice Assistant
Abstract
This study analyzes the learning experience of studying foreign languages (FLs) and designs a personal voice assistant to support users. Learning FL is a big challenge. The challenge of learning a new language including how language is used is ‘influenced by’ or is a direct result of the context in which communication takes place. The author's self-experience as an international student informs this study and provides access to a broad range of peers at the institution who have similar experiences. On the other hand, by utilizing voice assistant (VA), users build a relationship with VA and learners can understand multiple language backgrounds and cultures. Through in-depth interviews, participants—recruited from campus—were asked questions about why one wants to learn FL, how one learns FL, which tools one used to support learning, the challenges one meets with this experience, etc. This research asks about one’s learning experience and shares the researcher idea with VA utilizing it in supporting learning FL. This study does two sets of interviews with same group participants in order to collect interviewees’ experiences and feedback through the design process. In a sample size of 18 participants, this research understands how culture, background and environment influence FL learners’ experiences during studying a new language. Some interviewees live in foreign places and feel anxious using FL to communicate with native speakers. Some interviewees live in native and want to know more about FL’s different cultures locally. With this study, this author designs a personal voice assistant and supports learners with learning foreign languages.
Access
Open Access
Recommended Citation
Cheng, Ai-Ni, "Support for Language Learners by Designing a Personalized Voice Assistant" (2023). Theses - ALL. 735.
https://surface.syr.edu/thesis/735