Hostname: page-component-7c8c6479df-ws8qp Total loading time: 0 Render date: 2024-03-29T07:16:07.662Z Has data issue: false hasContentIssue false

Intelligent critiquing and tutoring of spatial reasoning skills

Published online by Cambridge University Press:  27 February 2009

Ole Jakob Mengshoel
Affiliation:
Department of Computer Science
Sanjeev Chauhan
Affiliation:
Department of General Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801-2996, U.S.A.
Yong Se Kim
Affiliation:
Department of General Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801-2996, U.S.A.

Abstract

The ability to reason spatially is an important skill required for engineers, particularly in engineering design and construction. One aspect of spatial reasoning is visualizing and constructing three-dimensional (3D) solid objects from two-dimensional (2D) projections. To assist in teaching this to engineering students, an instructional software system is being developed at the University of Illinois. This instructional software system is comprised of the Visual Sweeper and the Visual Teacher. The Visual Sweeper is a geometric framework for solving missing view problems. In missing view problems, students create 3D solid objects from two 2D projections by applying operations inverse to orthographic projection. The Visual Teacher, which is the focus of this article, is an intelligent critiquing and tutoring module that gives feedback to the student regarding partial solutions to missing view problems. The Visual Teacher is comprised of a Recognizer and a Critiquer. The Recognizer identifies which solution solid the student's partial solution is closest to. Based on the solution solid and a student's partial solution, the Criti-quer gives critique and advice to the student. The Recognizer is based on an algorithm for bipartite graph matching, while the Critiquer uses a rule-based approach. This paper describes the Visual Teacher, gives examples of how it can be used, presents preliminary evaluation results, and discusses the system's assumptions and limitations.

Type
Articles
Copyright
Copyright © Cambridge University Press 1996

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Agogino, A., Sheppard, S., & Oladipupo, A. (1992). Making engineering connections in the first two years. In Frontiers in Education To ward 2000 (Grayson, L.P., Ed.), pp. 563569. IEEE, New York.Google Scholar
Barr, R.E., & Juricic, D. (1994). From drafting to modern design representation: The evolution of engineering design graphics. J. Eng. Educ. 83 (3), 263270.CrossRefGoogle Scholar
Cormen, T.H., Leiserson, C.H., & Rivest, R.L. (1992). Introduction to algorithms. MIT Press, Cambridge, MA.Google Scholar
Giarratano, J., & Riley, G. (1994). Expert systems: Principles and programming (2nd ed.). PWS Publishing Company, Boston, MA.Google Scholar
Kim, Y.S., Astley, M., Pariente, F., & Zhao, H. (1994). Instructional software development for visual reasoning: The first phase. Proc. 6th Int. Conf. Eng. Comput. Graphics Descriptive Geometry.Google Scholar
Knuth, D.E. (1993). The Stanford GraphBase: A platform for combinatorial computing (1994 ed.). ACM Press, New York.Google Scholar
Littman, D., & Soloway, E. (1988). Evaluating ITSs: The cognitive science perspective. In Foundations of Intelligent Tutoring Systems (Poison, M.C., and Richardson, J.J., Eds.), pp. 209242. Lawrence Erlbaum Associates, Hillsdale, NJ.Google Scholar
Mantyla, M. (1988). An introduction to solid modeling. Computer Science Press, Rockville, MD.Google Scholar
McKim, R. (1972). Experiences in visual thinking. Brooks/Cole Publishing, Monterey, CA.Google Scholar
Mengshoel, O.J. (1993). Knowledge validation–Principles and practice. IEEE Expert 8 (3), 6268.CrossRefGoogle Scholar
Nagendra, I.V., & Gujar, U.G. (1988). 3-D objects from 2-D orthographic views–A survey. Comput. Graphics 12 (1), 111114.CrossRefGoogle Scholar
Osborn, J.R., & Agogino, A.M. (1992). An interface for interactive spatial reasoning and visualization. Proc. Conf. Hum. Factors in Com put. Syst., pp. 7582.Google Scholar
Poison, M.C., & Richardson, J.J., Eds. (1988). Foundations of intelligent tutoring systems. Lawrence Erlbaum Associates, Hillsdale, NJ.Google Scholar
Srinivas, Y., & Outta, D. (1991). A solution to the missing-view problem for polyhedral solids. Proc. Am. Soc. Mech. Eng. Design Automat. Conf.CrossRefGoogle Scholar
Wenger, E. (1987). Artificial intelligence and tutoring systems. Morgan Kaufman Publishers, Los Altos, CA.Google Scholar
Wilde, D.J. (1991). The geometry of spatial visualization: Two problems. Proc. 8th IFTOM World Congress.Google Scholar
Zhao, H., & Kim, Y.S. (1994). A computer aided visual reasoning tool for missing view problem. Proc. Am. Soc. Mech. Design Automat Conf.CrossRefGoogle Scholar