Eliciting curiosity — the intrinsic desire to explore and to find new information — enhances learning, promotes information-seeking and improves memory. Understanding how to elicit and maintain curiosity in students could help us design educational robots that stimulate interest, engagement and a quest for knowledge.
“We’re conducting a number of studies that examine human–robot interaction, in particular if a robot peer expresses curiosity does its inquisitiveness spark curiosity in students,” said Edith Law, a Professor at the Cheriton School of Computer Science and a member of its Human-Computer Interaction lab.
To explore the role of curiosity in learning, Professor Law and her research team conducted an experiment using a cooperative rock-classification game that a participant and an educational robot play together. Its goal was to see if curiosity could be fostered in participants through the verbal behaviour of a social robot.
“We created a matching game called LinkIt! to help teach how to categorize rocks,” said Jessy Ceha, a PhD student at the Cheriton School of Computer Science who is supervised by Dr. Law. “In front of a participant is a row of rocks, each with a card so the participant can see the rock’s type or features. The robot across from the participant also has a row of rocks with cards. The human player can see the robot’s rocks but not its cards.”
Between the players is a stack of cards placed face down that describes a feature or type of rock. For example, the card could show sedimentary rock — a type of rock formed by the accumulation of mineral or organic particles, or igneous rock — a type of rock that forms when magma cools and solidifies. The human player turns the top card over and tries to identify which rock on the robot’s side has the feature described in the card. Then the robot does the same while looking at the rocks on the human’s side. When rocks with the feature are identified correctly and linked up, they are put aside. The game continues until all rocks have been correctly matched.
“The rock classification game is just the context in which we’re exploring human–robot interaction,” said Nalin Chhibber, a recent master’s graduate from the School of Computer Science. “Our study varied the extent to which the robot expresses verbal curiosity.”
“To examine this, our study had three test conditions,” Jessy added. “One was called neutral and in that condition the robot did not express any verbal curiosity. The second condition was called curious and there the robot expressed curiosity through on-topic question-asking behaviour — the robot was actively searching for new knowledge by asking questions about rocks and wanting to know more about them. The third condition we called curious plus reveal, and here the robot expressed curiosity through on-topic question asking, just as in the curious condition, but it also revealed to the participant why it was curious.”
“In the neutral condition the robot could say, ‘Some rocks have a really glassy surface. They probably cooled too quickly to form any crystals,’” Nalin said. “In the curious condition the robot could say, ‘I am curious why some rocks have a glassy surface. Could they have cooled too quickly to form any crystals?’ And in the curious plus reveal condition the robot could say, ‘A glassy surface is new to me. I am curious why some rocks have that. Could they have cooled too quickly to form any crystals?’”
“By revealing its internal model — the robot giving some insight into what it could be thinking — might affect how curious participants are,” Jessy said.
Thirty participants at the University of Waterloo volunteered to take part in the study and they were randomly assigned to one of the three conditions. Ten participants played the rock-matching game with the robot in the neutral condition, ten with the robot in the curious condition, and ten with the robot in the curious plus reveal condition. Regardless of which group a participant was in, LinkIt! was played one-on-one — a single human player with the educational robot in one of the three conditions.
“We found that participants who interacted with the robot in the two curious conditions — curious and curious plus reveal — perceived the robot to be significantly more curious than participants who interacted with the neutral robot,” Jessy said. “This shows that we designed a robot that behaved in a way that was considered curious by participants. Most said that it was the on-topic question-asking that indicated to them the robot was curious.”
“We found that the robot’s expression of curiosity led to an increase in emotional curiosity — a significant increase in the state of feeling curious,” she added. “We also saw an increase in the behavioural expression of curiosity — a significant increase in on-topic question-asking and more verbal curiosity — in participants.”
Professor Law explains that they are interested in curiosity’s applications in many areas, not just in education.
“We want students to become curious about a subject because their interest leads to learning and the desire to find out more,” Professor Law said. “But there are many other applications of curiosity. If you have a new product and you want people to use it regularly — for example, a health-tracking app you want people to use so they report data to their doctor — understanding how to elicit and maintain curiosity are critical in keeping people interested. By designing curiosity into apps and devices the people who use them become and stay engaged.”
To learn more about the research on which this feature article is based, please see —
Jessy Ceha, Nalin Chhibber, Joslin Goh, Corina McDonald, Pierre-Yves Oudeyer, Dana Kulić, Edith Law. Expression of Curiosity in Social Robots: Design, Perception, and Effects on Behaviour. CHI '19: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, May 2019. https://doi.org/10.1145/3290605.3300636
This research was funded by the Natural Sciences and Engineering Research Council of Canada, Discovery Grant RGPIN-2015-0454.