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Engagement is critical to learning, yet current research rarely explores its underlying contextual influences, such as differences across modalities and tasks. Accordingly we examine how patterns of behavioral engagement manifest in a diverse group of ten middle school girls participating in a synchronous virtual computer science camp. We form multimodal measures of behavioral engagement from learner chats and speech. We found that the function of modalities varies, and chats are useful for short responses, whereas speech is better for elaboration. We discuss implications of our work for the design of intelligent systems that support online educational experiences. 

Pedagogical agents have the potential to provide not only cognitive support to learners but socio-emotional support through social behavior. Socioemotional support can be a critical element to a learner’s success, influencing their self-efficacy and motivation. Several social behaviors have been explored with pedagogical agents including facial expressions, movement, and social dialogue; social dialogue has especially been shown to positively influence interactions. In this work, we explore the role of paraverbal social behavior or social behavior in the form of paraverbal cues such as tone of voice and intensity. To do this, we focus on the phenomenon of entrainment, where individuals adapt their paraverbal features of speech to one another. Paraverbal entrainment in human-human studies has been found to be correlated with rapport and learning. In a study with 72 middle school students, we evaluate the effects of entrainment with a teachable robot, a pedagogical agent that learners teach how to solve ratio problems. We explore how a teachable robot which entrains and introduces social dialogue influences rapport and learning; we compare with two baseline conditions: a social condition, in which the robot speaks socially, and a non-social condition, in which the robot neither entrains nor speaks socially. We find that a robot that does entrain and speaks socially results in significantly more learning. 

Teachable robots are a form of social robot for education, where learners engage in conversation to teach the robot like they would a peer. Part of the popularity of social robots is their ability to utilize social channels of communication to foster productive social experiences, interactions which help individuals grow and develop. Teachable robots have potential to utilize social channels of communication to create social experiences which can help learners develop self-efficacy, an individual’s belief in their ability to succeed. In this paper, we present a fully autonomous robot for middle school math; we iterate through three design phases and analyze responses to identify how to better foster productive social experiences for self efficacy. We report six design recommendations; for example, for low self-efficacy individuals, an ideal design should incorporate problem-solving statements and positivity to foster social experiences of mastery and social persuasion.