"Look, it's turning!" Factors Affecting Structural and Functional Knowledge Acquistion in an Elementary School Robotics Classroom
PROCEEDINGS
Margaret Chan, John Black, In Sook Han, Jonathan Vitale, Qing Xia, Mathangi Subramanian, Minghua Du, Seokmin Kang, Teachers College, Columbia University, United States
EdMedia + Innovate Learning, in Vancouver, Canada ISBN 978-1-880094-62-4 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC
Abstract
The paper presents a study investigating how novices make transitions in understanding and developing appropriate mental models of robotics systems. In the course of a 9-week, after-school robotics club, 13 third and fourth grade students had the opportunity to view, construct, and program robots using Lego robotics. Students' drawings and videotaped responses to discussion questions were used to assess their knowledge of robotics. By comparing students' work from various sessions throughout the course, it was possible to recognize improvements in structural and functional knowledge among students who were highly engaged in programming. Evidence suggested that the process of programming facilitated the integration of various forms of knowledge -imagistic, declarative, and procedural – into working mental models, better enabling these students to design realistic robots, and make analyses and predictions of robot behavior. These findings provide insight into methods for guiding and assessing student development in the robot building process.
Citation
Chan, M., Black, J., Han, I.S., Vitale, J., Xia, Q., Subramanian, M., Du, M. & Kang, S. (2007). "Look, it's turning!" Factors Affecting Structural and Functional Knowledge Acquistion in an Elementary School Robotics Classroom. In C. Montgomerie & J. Seale (Eds.), Proceedings of ED-MEDIA 2007--World Conference on Educational Multimedia, Hypermedia & Telecommunications (pp. 1626-1631). Vancouver, Canada: Association for the Advancement of Computing in Education (AACE). Retrieved March 19, 2024 from https://www.learntechlib.org/primary/p/25589/.
© 2007 Association for the Advancement of Computing in Education (AACE)
Keywords
References
View References & Citations Map- Black, J.B. (1992). Types of Knowledge Representation (CCT Report NO. 92-3). New York: Teachers College, Columbia University.
- Chan, M.S. & Black, J.B. (2006). Learning Newtonian mechanics with an animation game. Paper presented at the Annual Meeting of the American Educational Research Association, San Francisco, April, 2006.
- Chan, M.S., & Black, J.B. (2006). Direct-Manipulation Animation: Incorporating the haptic channel in the learning process to support middle school students in science learning. Proceedings of the International Conference of the Learning Sciences, Mahwah, NJ: Lawrence Erlbaum.
- Johnson-Laird, P.N. (2005). Mental Models and Thought. In K. Holyoak and R.G. Morrison (Eds.), The Cambridge Handbook of Thinking and Reasoning (pp. 185-208). Cambridge University Press: New York.
- Mauch, E. (2001). Using Technological Innovation to Improve the Problem-Solving Skills of Middle School Students Educators' Experiences with the LEGO Mindstorms Robotic Invention System. The ClearingHouse. 74(4): 211-214.
- Papert, S. (1990). Mindstroms: Children, computers, and powerful ideas. New York: Bacis Books. Schank, Roger C. (1996) Goal-Based Scenarios: Case-Based Reasoning Meets LearningbyDoing. In: David Leake (Ed.) Case-Based Reasoning: Experiences, Lessons& Future Directions (pp. 295-347). AAAI
- Vanado, T. (2000). Robotics Across the Curriculum. TechDirections. 23:23-25.
- Wagner, S.R. (1998). Robotics and Children: Science Achievement and Problem Solving. Journal of Computing in Childhood Education. 9(2):149-92.
- Wilensky, U. (2001). Emergent Entities and Emergent Processes: Constructing Emergence through Multi-Agent Programming. Paper presented at the Annual Conference of the American Educational Research Association, Seattle, WA: April 13, 2001.
These references have been extracted automatically and may have some errors. Signed in users can suggest corrections to these mistakes.
Suggest Corrections to ReferencesCited By
View References & Citations Map-
An Embodied Approach to the Instruction of Conditional Logic in Video Game Programming
Cameron L. Fadjo, Chun-Hao Chang, JeeHye Hong & John B. Black, Teachers College, Columbia University, United States
EdMedia + Innovate Learning 2010 (Jun 29, 2010) pp. 2672–2679
These links are based on references which have been extracted automatically and may have some errors. If you see a mistake, please contact info@learntechlib.org.