The use of virtual chatbots to support Chinese as a foreign language learners’ communication skills through scaffolded self-directed learning

This study investigated the use of virtual chatbots in a 3D multi-user virtual environment (3D MUVE) to enhance the communication skills of Chinese as a foreign language (CFL) learners. Several virtual chat agents, developed using pattern matching techniques and embedded in Second Life, created a blended learning environment in which CFL learners completed authentic language tasks through scaffolded self-directed learning (SDL). The chatbots were able to interact with the learners, answer their questions, and provide guidance as needed. A mixed methods approach was used to collect quantitative and qualitative data from 49 Chinese Studies students at an Australian university. Quantitative data was collected using a one-group post-test only design where learning outcomes were assessed using a Moodle post-test. Qualitative data included log data of students’ activities in Second Life. After a whole-class lesson, students logged into Second Life to complete assigned tasks supported by progress indicators and scaffolding for different activities. Results indicated that CFL learners improved their communication skills and reduced errors caused by their native language. The combination of virtual chat agents and a scaffolded SDL context seemed to effectively support CFL students’ interpersonal communication skills while reducing vocabulary and sentence structure errors.