Understanding Factors that Shape Children’s Long Term Engagement with an In-Home Learning Companion Robot

Jun 1, 2022·
Bengisu Cagiltay
,
Nathan Thomas White
Rabia Ibtasar
Rabia Ibtasar
,
Bilge Mutlu
,
Joseph Michaelis
· 0 min read
Abstract
Social robots are emerging as learning companions for children, and research shows that they facilitate the development of interest and learning even through brief interactions. However, little is known about how such technologies might support these goals in authentic environments over long-term periods of use and interaction. We designed a learning companion robot capable of supporting children reading popular-science books by expressing social and informational commentaries. We deployed the robot in homes of 14 families with children aged 10–12 for four weeks during the summer. Our analysis revealed critical factors that affected children’s long-term engagement and adoption of the robot, including external factors such as vacations, family visits, and extracurricular activities; family/parental involvement; and children’s individual interests. We present four in-depth cases that illustrate these factors and demonstrate their impact on children’s reading experiences and discuss the implications of our findings for robot design.
Type
Publication
Proceedings of the 21st Annual ACM Interaction Design and Children Conference
publications
Rabia Ibtasar
Authors
Rabia Ibtasar
Learning Sciences & Human-Computer Interaction Researcher

My research goal is to design, build, and evaluate technology-facilitated learning environments. My work brings together learning sciences, human–computer interaction, computing education, and social robotics.

I completed my Ph.D. in Learning Sciences at the University of Illinois Chicago in May 2026, advised by Dr. Joseph E. Michaelis. I also hold a master’s degree in Computer and Information Science from the University of Pennsylvania and a Bachelor of Science in Computer Science from Lahore University of Management Sciences.

My dissertation, “Broadening Participation of Girls in Computing: An Integrated Approach to Supporting Interest in CS,” examined how technological and social scaffolds support girls’ interest in computing. Through the MyTurn project, I designed a web-based pre-coding tool and studied its use alongside peer collaboration and mentorship during social robotics activities.

My broader research includes in-home robot learning companions and teacher-facing tools for designing robot-assisted learning experiences. I use iterative design and mixed methods to understand learners’ experiences and inform technology design.

My future research vision builds on my previous work to investigate the design of AI-enabled technologies that can adapt to learners’ evolving needs and complement social scaffolds embedded within authentic learning contexts to support learning and interest.

Illustration of collaborative learning with interactive technologies and a social robot

AI-generated illustration representing my research.