Foreign language acquisition via artificial intelligence and extended reality: design and evaluation
Rahul R. Divekar, Jaimie Drozdal, Samuel R. V. Chabot, Yalun Zhou, Hui Su, Yue Chen, Houming Zhu, James Hendler, Jonas Braasch · Computer Assisted Language Learning · 2021
Artificial Intelligence (AI) and Extended Reality (XR) have been employed in several foreign language education applications to increase the availability of experiential learning methods akin to international immersion programs. However, research in multi-modal spoken dialogue in L2 combined with immersive technologies and collaborative learning is thin, limiting students’ experiences to solo interactions focused mostly on vocabulary and grammar in such settings. We intend to fill this gap as we present the Cognitive Immersive Language Learning Environment (CILLE). The AI in CILLE can hear, see, and understand its users and can engage with them in non-dyadic multimodal conversations. The XR offers students a feeling of being somewhere else without the use of intrusive devices and supports multi-party, multi-modal interactions. Together, AI and XR create naturalistic conversational interactions targeted towards comprehensive foreign language acquisition. We evaluate CILLE as a Chinese-as-a-foreign-language (CFL) education tool through a seven-week, mixed-methods study with university students (N = 10). Results display statistical significance and retained improvement in CFL vocabulary, comprehension, and conversation skills. Coupled with an analysis of student feedback and researcher observations, we show how CILLE is designed and experienced by students to learn CFL.