The Effects of Physical Form and Embodied Action in a Teachable Robot for Geometry Learning

Erin Walker, Victor Girotto, Younsu Kim, Kasia Muldner

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

A teachable agent is a learning companion that students teach about a domain they are trying to master. While most teachable agents have been virtual, there may be advantages to having students teach an agent with a physical form (i.e., a robot). The robot may better engage students in the learning activity, and if students take embodied action in order to instruct the robot, they may develop deeper knowledge. In this paper, we investigate these two hypotheses using the rTAG system, a teachable robot for geometry learning. In a study with 37 4th-6th grade participants, we compare rTAG to two other conditions, one where students use embodied action to teach a virtual agent, and one where students teach a virtual agent on a personal computer. We find that while there are no significant learning differences between conditions, students' perceptions of the agent are influenced by condition and prior knowledge.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE 16th International Conference on Advanced Learning Technologies, ICALT 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages381-385
Number of pages5
ISBN (Electronic)9781467390415
DOIs
StatePublished - Nov 28 2016
Externally publishedYes
Event16th IEEE International Conference on Advanced Learning Technologies, ICALT 2016 - Austin, United States
Duration: Jul 25 2016Jul 28 2016

Other

Other16th IEEE International Conference on Advanced Learning Technologies, ICALT 2016
CountryUnited States
CityAustin
Period7/25/167/28/16

Fingerprint

robot
mathematics
Robots
Students
Geometry
learning
student
PC
Personal computers
school grade
knowledge

Keywords

  • Personalized learning
  • Robotic learning environment
  • Teachable agent

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Education
  • Computer Networks and Communications
  • Computer Science Applications

Cite this

Walker, E., Girotto, V., Kim, Y., & Muldner, K. (2016). The Effects of Physical Form and Embodied Action in a Teachable Robot for Geometry Learning. In Proceedings - IEEE 16th International Conference on Advanced Learning Technologies, ICALT 2016 (pp. 381-385). [7757003] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICALT.2016.129

The Effects of Physical Form and Embodied Action in a Teachable Robot for Geometry Learning. / Walker, Erin; Girotto, Victor; Kim, Younsu; Muldner, Kasia.

Proceedings - IEEE 16th International Conference on Advanced Learning Technologies, ICALT 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 381-385 7757003.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Walker, E, Girotto, V, Kim, Y & Muldner, K 2016, The Effects of Physical Form and Embodied Action in a Teachable Robot for Geometry Learning. in Proceedings - IEEE 16th International Conference on Advanced Learning Technologies, ICALT 2016., 7757003, Institute of Electrical and Electronics Engineers Inc., pp. 381-385, 16th IEEE International Conference on Advanced Learning Technologies, ICALT 2016, Austin, United States, 7/25/16. https://doi.org/10.1109/ICALT.2016.129
Walker E, Girotto V, Kim Y, Muldner K. The Effects of Physical Form and Embodied Action in a Teachable Robot for Geometry Learning. In Proceedings - IEEE 16th International Conference on Advanced Learning Technologies, ICALT 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 381-385. 7757003 https://doi.org/10.1109/ICALT.2016.129
Walker, Erin ; Girotto, Victor ; Kim, Younsu ; Muldner, Kasia. / The Effects of Physical Form and Embodied Action in a Teachable Robot for Geometry Learning. Proceedings - IEEE 16th International Conference on Advanced Learning Technologies, ICALT 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 381-385
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