Promoting academically productive talk with conversational agent interventions in collaborative learning settings

Research on computer-supported collaborative learning (CSCL) and conversational pedagogical agents has strongly emphasized the value of providing dynamic dialogue support for learners working together to accomplish a certain task. Recently, on the basis of the classroom discourse framework of Academically Productive Talk (APT), a flexible form of conversational agent support has emerged employing APT-based intervention methods so as to stimulate pedagogically beneficial conversational interactions among learning partners. This paper investigates the impact of an APT-based Linking Contributions (LC) intervention mode implemented by a conversational agent in the context of a collaborative activity in higher education. This type of agent interventions encourages students to explicitly externalize their reasoning on important domain concepts building upon the contributions of their partners. Forty-three (43) students collaborated in small groups using a prototype CSCL system to accomplish three different tasks in the domain of Multimedia Learning. Groups were randomly assigned to the treatment or the control condition. In the treatment condition, a conversational agent participated in students' dialogues making LC mode interventions. In the control condition, students discussed without the agent intervening. The results of the study illustrated that the students in the treatment condition engaged in a more productive dialogue demonstrating increased explicit reasoning throughout the collaborative activity. Furthermore, it was shown that the students in the treatment condition outperformed the control students in various measures on knowledge acquisition. Evidence also suggests that students' enhanced learning performance was mediated by the positive effect of the agent intervention mode on students' argumentation. Overall, this study provides insights into how the use of a configurable conversational agent displaying unsolicited LC interventions during students' discourse can be beneficial to collaborative learning. We investigated the impact of a Linking Contributions (LC) intervention mode implemented by a conversational agent.Our results indicated that the LC agent intervention mode amplified student explicit reasoning.The LC agent interventions also improved domain-learning outcomes.The enhancement of student learning was mediated by the impact of agent interventions on student explicit argumentation.