Effective Visualization of the Sutherland Hodgman Clipping Algorithm

Effective Visualization of the Sutherland Hodgman Clipping Algorithm Introduction There 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 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). Key aspects of visualization for developing a deep understanding of the algorithm Questions. Using JHAVÉ support for pop- Basic visualization. Our visualization supports step by step views of each major operation occurring within the algorithm. up questions, we developed a series of questions to accompany the visualization. Alejandro Carrasquilla Shawn Recker University of Wisconsin – Oshkosh Grove City College carraa 48@uwosh. edu reckerst 1@gcc. edu Correlation of Questions and Exercises to Bloom’s Taxonomy divides cognitive Deep learning into the following six Understanding categories [2]: Evaluation Synthesis Exercises Questions Exercises. In order to test a deeper understanding of the algorithm, we developed a series of Analysis Application Comprehension Recall of Data Basic Understanding exercises which require the user to enter polygons adhering to a specified constraint. Empirically Measuring Effectiveness In 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 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