How pedagogical agents communicate with students: A two-phase systematic review

Technological advancements have improved the capabilities of pedagogical agents to communicate with students. However, an increased use of pedagogical agents in learning environments calls for a deeper understanding of student–agent communication to assess the effectiveness of pedagogical agents in learning. This study is a two-phase systematic review of scientific papers on pedagogical agent communication research published between 2010 and 2020, including review papers and original research papers. In the first phase, this study analyses literature reviews and meta-analyses to find the status and research gaps. The findings indicate that pedagogical agents' characteristics and impact on learning have been reviewed, but pedagogical agent communication and its relation to learning have not. In the second phase, the empirical studies of pedagogical agent communication are reviewed and classified into three categories that describe how pedagogical agent communication facilitates students' learning through (1) students' intrapersonal communication processes, (2) interpersonal communication between students and a pedagogical agent, and (3) by facilitating learning in a group. The findings show that pedagogical agent communication can enhance learning through intrapersonal communication of motivation, self-regulation, self-efficacy, and metacognition. At the interpersonal level, pedagogical agents aim to scaffold learning by giving feedback, prompts, and hints from learning processes and learning results. Pedagogical agents also support learning in a group by facilitating discussions and directing students' collaboration. Despite rapid technological advancements, pedagogical agents are not on the level to communicate fluently and human-like, which is likely to reduce their effectiveness and usability in learning. The review concludes that pedagogical agents’ communication needs to be developed toward adaptive, adequate, relational, and logical communication, which requires a multidisciplinary theoretical approach, the use of artificial intelligence, affective computing, and psychometric assessments. Recommendations for future research addressing the gaps identified in this systematic review are discussed.