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Educational chatbots (EC) have shown their promise in providing instructional support. However, limited studies directly explored the impact of EC on learners’ emotional responses. This study investigated the induced emotions from interacting with micro-learning EC and how they impact learning motivation. In this context, the EC interactions encompassed greetings, biology learning content delivery, self-evaluation, and feedback. This study employed a between-subject experimental design involving 62 college students. Participants were randomly assigned to either the Metacognitive EC group, receiving metacognitive feedback, or the Neutral EC group, receiving neutral feedback. The results of T-tests demonstrated significant differences in specific induced emotions between the two groups while some similarities exist. Importantly, it unveiled that both Metacognitive EC and Neutral EC interactions evoked a spectrum of positive, negative, and ambivalent emotions, in which positive emotions surpassed the induced negative emotions. In general, metacognitive feedback induced fewer negative emotions than neutral feedback. PLS analysis supported the relationships between induced emotions and intrinsic motivation, with positive emotion, ambivalent emotions, and negative emotions influencing interest motivation, which, in turn, shaped other motivational components, including perceived competence, perceived value, and perceived pressure. However, the influence of positive emotion on interest was weaker in the Metacognitive than in the Neutral EC. In conclusion, the study revealed how induced emotions impact motivations and showed that the presence of metacognitive feedback reduced negative emotions and promoted motivation. These findings highlight the need for positive emotion element design and appropriate feedback that will impact learning motivations during educational chatbot interactions.
Educational chatbots (EC) have shown their promise in providing instructional support. However, limited studies directly explored the impact of EC on learners’ emotional responses. This study investigated the induced emotions from interacting with micro-learning EC and how they impact learning motivation. In this context, the EC interactions encompassed greetings, biology learning content delivery, self-evaluation, and feedback. This study employed a between-subject experimental design involving 62 college students. Participants were randomly assigned to either the Metacognitive EC group, receiving metacognitive feedback, or the Neutral EC group, receiving neutral feedback. The results of T-tests demonstrated significant differences in specific induced emotions between the two groups while some similarities exist. Importantly, it unveiled that both Metacognitive EC and Neutral EC interactions evoked a spectrum of positive, negative, and ambivalent emotions, in which positive emotions surpassed the induced negative emotions. In general, metacognitive feedback induced fewer negative emotions than neutral feedback. PLS analysis supported the relationships between induced emotions and intrinsic motivation, with positive emotion, ambivalent emotions, and negative emotions influencing interest motivation, which, in turn, shaped other motivational components, including perceived competence, perceived value, and perceived pressure. However, the influence of positive emotion on interest was weaker in the Metacognitive than in the Neutral EC. In conclusion, the study revealed how induced emotions impact motivations and showed that the presence of metacognitive feedback reduced negative emotions and promoted motivation. These findings highlight the need for positive emotion element design and appropriate feedback that will impact learning motivations during educational chatbot interactions.
Emotional feeling is a phase of neurobiological activity that plays an important role in cognitive thinking and learning, although largely overlooked in complex tutoring fields like Mathematics. This paper introduces an innovative e-learning Mathematics course integrating emojis as a feedback mechanism to express students’ emotional responses towards mathematical challenges. By providing a platform for intuitive emotional expression, this approach aims to strengthen engagement and comprehension. Through empirical investigation, emotional reactions of online mathematics students are explored, with attention to gender-related differences in emoji usage. A survey administered to 100 students prompts them to select emojis conveying their sentiments towards mathematical problems. Statistical analyses reveal that emojis effectively capture students’ emotions, with an emphasis on gender-based variations in selection. These insights illuminate the dynamics of emotional expression and hold implications for fostering comprehensive learning environments that mitigate negative emotions such as mathematical anxiety. By empowering educators to monitor students’ emotional reactions and adapt teaching strategies accordingly, this approach has the potential to cultivate confident and proficient learners essential for STEM (Science, Technology, Engineering, Mathematics) advancement.
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