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Effective Visualization of the Sutherland Hodgman Clipping Algorithm

Effective Visualization of the Sutherland Hodgman Clipping Algorithm. Alejandro Carrasquilla University of Wisconsin – Oshkosh carraa48@uwosh.edu. Shawn Recker Grove City College reckerst1@gcc.edu. Introduction

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Effective Visualization of the Sutherland Hodgman Clipping Algorithm

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  1. Effective Visualization of the Sutherland Hodgman Clipping Algorithm Alejandro Carrasquilla University of Wisconsin – Oshkosh carraa48@uwosh.edu Shawn Recker Grove City College reckerst1@gcc.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 Bloom’s Taxonomy Bloom’s Taxonomy divides cognitive learning into the following six categories [2]: Key aspects of visualization for developing a deep understanding of the algorithm Deep Understanding Questions. Using JHAVÉ support for pop-up questions, we developed a series of questions to accompany the visualization. Basic visualization. Our visualization supports step by step views of each major operation occurring within the algorithm. Exercises Questions Exercises. In order to test a deeper understanding of the algorithm, we developed a series of exercises which require the user to enter polygons adhering to a specified constraint. 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

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