Effective Visualization of the Sutherland Hodgman Clipping Algorithm

1
Effective Visualization of the Sutherland Hodgman
Clipping Algorithm
Shawn Recker Grove City College reckerst1_at_gcc.edu
Alejandro Carrasquilla University of Wisconsin
Oshkosh carraa48_at_uwosh.edu
Introduction There are a few crucial algorithms
in computer graphics used by many image synthesis
techniques. Polygon clipping is one such
algorithm. An effective method for
two-dimensional polygon clipping was described by
Sutherland and Hodgman in 1974 1. In order to
help students achieve an understanding of this
algorithm, we developed a visualization using the
Java Hosted Algorithm Visualization Environment
(JHAVÉ).
Correlation of Questions and Exercises to Blooms
Taxonomy Blooms Taxonomy divides cognitive
learning into the following six categories 2
Deep Understanding
Exercises
Questions
Basic Understanding

• Empirically Measuring EffectivenessIn order to
  demonstrate the effectiveness of our
  visualization, we will conduct an empirical study
  consisting of the following
• Pre-test computer science students prior to
  exposure of algorithm
• One group will have access to the visualization
• The other group will have access only to text
  book materials
• A post-test will be conducted and statistical
  comparisons made
• We expect the students exposed to the
  visualization to perform better on the final test.

References 1 I. E. Sutherland and G. W.
Hodgman. Reentrant polygon clipping. Commun. ACM,
17(1)32-42, 1974. 2 T. Scott. Bloom's taxonomy
applied to testing in computer science classes.
J. Comput. Small Coll.,19(1)267-274, 2003.
Acknowledgements Funded by NSF Award Number
0851569 Thanks to mentors Dr. Thomas Naps, Dr.
David Furcy, and Dr. George Thomas