Exploring student engagement and learning preferences: A comparative study between virtual- and robot-based tutors

摘要

The rapid integration of artificial intelligence (AI) in educational settings has opened new avenues for personalized and interactive learning experiences. This study investigates the comparative effectiveness of virtual- and robot-based tutors in enhancing student engagement and learning preferences. Utilizing advanced AI technologies, we conducted a comprehensive analysis to determine which tutoring modality offers a more effective and engaging learning experience. Through a methodological approach, we collected and analyzed data from participants who interacted with both tutoring systems. Employing k-means clustering and statistical analysis, we identified distinct clusters of learner preferences and engagement levels. Our findings reveal significant differences in the effectiveness of robot- and virtual-based tutors across different learner groups, highlighting the importance of personalized and adaptable AI tutoring systems. The implications of our research suggest a need for further exploration into personalized educational tools for diverse learning styles, thereby optimizing the learning experience in AI-enhanced educational environments.