Evaluating the AI dialogue system's intercultural, humorous, and empathetic dimensions in English language learning: A case study

The rise of artificial intelligence (AI) technologies has been notable in supporting English as an Additional Language (EAL) learners, particularly in offering interactive assessments. AI-driven dialogue systems that produce culturally relevant humor and empathy, bridging the native language and the target language, have been employed to engage EAL learners more effectively and boost their learning results. However, there is a noticeable gap in research concerning the effects of humor, empathy, and intercultural dimensions in language learning. To address this research gap, this case study examines the effectiveness of an AI dialogue system, termed the Multidimensional Approach Culture, Humor, and Empathy Bot (MACHE-Bot). By integrating these dimensions, MACHE-Bot aims to provide a more engaging and effective learning environment for EAL learners. The study evaluates the system's impact on learners' language proficiency, engagement, and cultural understanding, offering insights into how effective such innovative approaches can be utilized to improve EAL outcomes. Using convenience sampling, 37 individuals were selected from an English language learning group on Facebook. Following a two-week trial, semi-structured interviews were conducted. The results revealed that MACHE-Bot adeptly initiated and reciprocated with humor, empathy, and cultural nuances in a manner well-received by participants. Additionally, the study identified five pivotal factors in EAL learning with MACHE-Bot: (1) intercultural dimensions, which include culturally humorous interaction and culturally empathetic support; (2) user trust comprising both affective and cognitive elements; (3) anthropomorphism; (4) reciprocal self-disclosure; and (5) higher engagement and motivation. These five factors collectively contribute to creating an engaging, relatable, and supportive learning environment, facilitating a more natural learning process, and fostering a deeper learner-bot connection, thereby potentially enhancing motivation and investment in the learning process.