While one-on-one human tutors are considered the gold standard of learning paradigms, why is it easier to seek help from computer tutors? Evaluation anxiety increases with heightened social presence and social role of the tutor, and in this experiment I investigate the impact social role (teacher or helper) and social presence (human or robot tutor) impacts help seeking in a lab experiment.
I completed this work as part of an internship at the Advanced Telecommunications Research Institute International, in which over a period of twelve weeks I brainstormed, planned, and implemented the entire lab experiment with the help of my mentor, a post-doctoral researcher, and an administrative assistant. The results of my data analysis were published in the Proceedings of the 2014 Human-Robot Interaction conference.
In order to explore the unique social positioning of pedagogical robots, I designed a 2X2 experiment crossing social presence (robots vs. humans) and social role (teacher vs. helper). Our hypotheses indicated that due to the reduced evaluation anxiety induced by robot tutors (less anxiety than human tutors), and helpers (less anxiety than teachers), participants would seek the most help from Robot Helpers and the least from Human Teachers. Results showed that participants learned significantly less from Human Teachers and that they asked marginally less questions from Human Teachers. Our hypotheses were mostly supported. While there was this distinction made between Human Helpers and Human Teachers, no such distinction was identifiable between Robot Helpers and Robot Teachers.
Future work involves investigating these issues of evaluation anxiety and how they influence learning and help seeking in other situations with technologically mediated communication and learning. Methodology and further details and analysis of this work are available in the documentation below.
Howley, I., Kanda, T., Hayashi, K., & Rose, C. (2014, March). Effects of social presence and social role on help-seeking and learning. In Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction (pp. 415-422). ACM.