Traditional classroom teaching often does not provide students with practical applications to engage their interest. Laboratory work can fill that gap, but may not be easy to set up in the conventional classroom. To address this, researchers at New York University (NYU) have enlisted the help of an "adorable" robot with which students love to interact, which teaches by learning lessons from the students.
The idea is to first teach a classroom principle the old fashion way—with diagrams, lectures, and chalk/markers on black/white boards. Once students have the basic principles in mind, they teach them to the robot, which "acts them out," in the process reinforcing them in the student's memory.
A paper on this "learning by teaching" methodology for geometry presented at ACM's Conference on Human Factors in Computing Systems (CHI 2016) "focuses on two things: the virtues of engaging learners with 'teachable agents,' namely, computational devices that students imbue with their own understanding; and how teachers incorporate an embodied, teachable robot into their instructional goals," said Fred Martin, Board Chair of the Computer Science Teachers Association (CSTA) and professor in the computer science department of the University of Massachusetts Lowell.
Martin said the researchers "establish in their literature review that it is an innovative and effective pedagogical approach to have kids teach an agent their own understandings. The agent then enacts the knowledge-rules given to it by the learners. This allows the students to then validate the veracity and completeness of their understandings by seeing what the agent does."
The robot introduced by the researchers, "Quinn," is "an effective example of this approach," Martin says, "because it is a physical device; 'embodied,' in the field's parlance. This allows students to use their own bodies to interact with it—the approach called 'body-syntonic' by Seymour Papert, the seminal researcher whom the authors cite as having inspired their work. Further, the researchers and the teachers they worked with highlight the value of the social interactions among the children that are facilitated by the fact that Quinn is physically embodied."
Quinn is an iPod Touch mounted atop a mobile base using LEGO components. Instead of using the iPod for "windows, icons, menus, and pointing" (the WIMP approach), Quinn uses what NYU’s Winslow Burleson, principal investigator on the study, calls the "robo-Tangible Activities for Geometry" (rTAG) methodology. The result is a mobile robot that provides a tangible learning environment by engaging students in collaborative activities.
Daniel Tillman, director of the Educational Technology Research Laboratory in the College of Education at the University of Texas at El Paso, said the research "is part of a line of inquiry that is striving to make classroom learning less rote, and instead more engaging, for students. This is the primary task facing 21st century education and educators, and unless students are better stimulated by the curriculum, we will continue to see a decline in the competitiveness of U.S. graduates compared to their international counterparts."
David Claveau, professor at California State University Channel Islands, observed that interactive robots are not commonplace in the classroom. "The authors describe an affordable and easily deployed interactive robotic system that can improve student engagement by having the students ‘help’ the robot to solve geometry problems. It represents a step towards teachable and affective robots that can truly help teachers.
"Learning is about mutual understanding and that involves emotion. We need robots that can both recognize and communicate emotion."
To compare the efficacy of the rTAG system with WIMP methodologies, the team developed a virtual-TAG (vTAG) system with all the same features, but which used a conventional computer to perform all the functions. The vTAG software version placed a Quinn icon on the computer screen along with an on-screen command entry area where the exact same lessons could be taught and tested right down to the same "Check Answer" conclusion, which triggered the same visual and audio response from the on-screen Quinn.
The researchers testing the rTAG and vTAG versions of the computer-assisted learning environments for a week in a California public school system, with eight third-grade to fifth-grade classes of 25 to 40 students each from four different schools. Each classroom was equipped with three vTAG stations and a single rTAG station. Each teacher prepared their own lesson plan for the systems, with the only significant difference being suggested angles and coordinates supplied by some teachers. The only instruction given to the students was about how the vTAG system worked, then the students were divided up into groups which rotated among the four stations.
The results were almost identical among all the groups: the groups teaching geometry to the physical robot were more engaged with both the learning process and with each other. The three groups using the vTAG systems tended to have a single student "drive" the on-screen simulation, while others looked on or wandered off. The rTAG group was attentive, took turns "driving" by touching the robot, and passed around the iPod Touch controller, resulting in more productive learning (the teachers said the group using the robot did not even realize they were learning).
Said Chuck Thorpe, senior vice president and provost of Clarkson University, "We roboticists are sometimes so enchanted with the technology that we forget to watch how people use it. It is gratifying, but not surprising, to see how engaged the students were with the robot."
Thorpe, former director of the Robotics Institute at Carnegie Mellon University, a past White House Fellow, and assistant director for advanced manufacturing and robotics in the Office of Science and Technology Policy of the Executive Office of the President, added, "What's missing is a real measure of what the students learned. A week later, or a month later, did the students who used the robot learn and retain more about geometry than the students who didn't use the robot? Or were they just excited about the robot, but hadn't learned any more concepts? "
After the formal testing, Burleson and his colleagues evaluated student performance and the barriers facing teachers using the TAG systems. All agreed student engagement was one of rTAG's strongest assets. The Quinn robot was cited by the teachers as rTAG's biggest draw, as students were eager to get the robot to the proper spot indicating it (and they) had learned the right lesson.
The teachers recommended targeting multiple learning objectives, emphasizing cooperation to achieve goals, optimizing for training, and more innovative new uses of the rTAG system. The barriers noted by the teachers included the need for more set-up time, better training for teachers, and fewer students per station. A few students were intimidated by the rTAG system, which the teachers suggested could be cured by better training and demonstrations. However, the use of iPods, with which the students were already familiar, helped to reduce the training load and intimidation factors, according to the teachers.
"Technology that increases student engagement is worth exploring," said Veronica Ahumada Newhart, a researcher in the University of California, Irvine, School of Education, where students are permitted to use telepresence robots to attend school virtually from home. "Our research is centered on telepresence robots, and we have seen in our research where a student controlling the robot allows other students to relate to the robot. There is a parallel here where the robot is not acting on its own but is controlled by the students, and relating to the robot may increase student persistence to get Quinn where he’s supposed to go."
R. Colin Johnson is a Kyoto Prize Fellow who has worked as a technology journalist for two decades.
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