An early investigation of collaborative problem solving in conversational AI-mediated learning environments

Sinem Aslan, Nese Alyüz, Belle Li, Lenitra Megail Durham, Meng Shi, Sangita Sharma, Lama Nachman

Abstract: Collaborative problem solving (CPS) encourages children to communicate effectively and fosters creativity and critical thinking. New digital technologies can potentially provide opportunities for innovative ways to promote CPS at an early age. However, one key challenge of such technologies is to be engaging and effective while also pedagogically adapting to developmental needs of young learners. In this paper, we propose that a multimodal conversational AI system, Kid Space, providing interactive learning experiences could enrich CPS and promote positive educational outcomes. Kid Space combines multimodal classroom sensing with a projected 3D virtual environment and an animated conversational agent to engage with children via spoken dialogue and physical interactions. Within an exploratory case study, we formatively evaluated CPS behaviors of a set of children engaged with Kid Space to inform design modifications for the type of CPS learning analytics educators could benefit from and improved support of CPS behaviors in conversational AI-mediated learning environments. Our quantitative results indicate that there were significant correlations between CPS behaviors and (1) joint engagement of students working together and (2) pedagogical interventions provided by the instructional assistant facilitating the learning experience. The results imply that, with necessary design augmentations, Kid Space could potentially play a valuable role in supporting CPS processes of young learners.

External IDs:dblp:journals/caeai/AslanALDSSN25