Investigating the impact of chatbot design features on affective variables: A mixed-methods study

Abstract

This study investigated how chatbots, designed with distinct personality traits (more engaging vs. less engaging) and feedback features (basic vs. enhanced) influenced L2 learners’ affective variables, such as anxiety, enjoyment, curiosity, and boredom, during their conversational interactions. Although second language acquisition research, including AI-based chatbot studies, has examined how learners’ emotions are shaped during L2 tasks, there has been insufficient focus on how variations in chatbot characteristics affect learners’ emotional experiences. To address this gap, we conducted a mixed-methods study of undergraduate EFL students, examining their interactions with three conversational agents, each featuring distinct combinations of personality traits and feedback features. Participants engaged in conventional tasks and completed a questionnaire to assess affective variables, which was supplemented with open-ended questions to gain further insights. Our findings revealed how L2 learners’ emotional experiences differ depending on the conversational agents’ characteristics. Based on these insights, we propose the pedagogical implications for the design and implementation of chatbots for L2 learning.