Speaker
Description
This classroom-based practice uses AI-driven persona dialogue to enhance Japanese university students’ speaking skills while raising awareness of microaggressions. Students engage in realistic scenarios—such as workplaces, part-time jobs, clubs, and campus settings—responding to potentially problematic remarks from AI-generated personas. This approach allows low-anxiety rehearsal, reflection on language use, and reformulation of expressions. Preliminary observations suggest increased oral production, a deeper understanding of “intent versus impact,” and more empathetic communication in English.
Abstract
Microaggressions, subtle yet potentially harmful expressions of bias, can undermine inclusive learning environments (Sue, 2007; Nadal, 2011). In Japanese university classrooms, initial activities that invite students to share personal experiences of microaggressions, such as teasing related to regional dialects or hometown stereotypes, can raise basic awareness. However, such discussions often remain limited to culturally familiar and surface-level examples.
Building on a previous project presented at an international conference, this classroom-based practice introduces a new stage that incorporates AI chatbots to enhance the realism of speaking activities and deepen conceptual understanding. Drawing on documented narratives by scholars such as Chester Pierce (1970), who coined the term “microaggression,” Derald Wing Sue (2007), and Japanese educator Shimoji Lawrence Yoshitaka (2017), realistic conversational scenarios were developed using AI support.
The settings include workplaces, part-time jobs, university campuses, and extracurricular clubs, where hierarchical relationships and implicit role expectations frequently shape communication. Before engaging in in-class role-plays, students practice responding to these scenarios through spoken interaction with an AI chatbot. The chatbot functions as a low-anxiety conversational partner, allowing students to rehearse responses, reflect on how language choices may be perceived, and reformulate their utterances in more inclusive ways.
Preliminary observations and student reflections suggest that chatbot-mediated speaking practice increases oral production and encourages deeper reflection on the “intent versus impact” dynamic of microaggressions. By combining theory-informed scenarios with AI-supported dialogue practice, this approach moves students beyond superficial cultural examples and promotes more realistic, critical, and empathetic communication skills in EFL contexts.
Short summary
This classroom-based practice uses AI chatbots to enhance Japanese university students’ speaking skills while raising awareness of microaggressions. Students engage in realistic scenarios in workplaces, part-time jobs, clubs, and campus settings, responding to potentially problematic remarks. Chatbot-mediated practice allows low-anxiety rehearsal, reflection on language use, and reformulation of expressions. Preliminary observations suggest increased oral production, deeper understanding of “intent versus impact,” and more empathetic communication in English.
Keywords
Microaggressions
AI Chatbot
Speaking Practice
Inclusive Communication
References
Nadal, K. L. (2011). The SAGE encyclopedia of psychology and gender. SAGE.
Pierce, C. (1970). Offensive mechanisms. In F. B. Barbour (Ed.), The Black seventies (pp. 265–282). Porter Sargent.
Sue, D. W. (2007). Microaggressions in everyday life: Race, gender, and sexual orientation. Wiley.
| Scheduling preference | Anytime on Saturday or Sunday |
|---|---|
| Title | AI Chatbot–Mediated Speaking to Raise Awareness of Microaggressions |