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Intelligent Tutoring Goes To School in the Big City




Kenneth R. Koedinger
Human-Computer Interaction Institute
School of Computer Science
Carnegie Mellon University
Pittsburgh, PA 15213 USA
ken.koedinger@cs.cmu.edu
http://act.psy.cmu.edu/ACT/people/koedinger.html
John R. Anderson
William H. Hadley
Mary A. Mark
Department of Psychology
Carnegie Mellon University
Pittsburgh, PA 15213
USA


        

Abstract . This paper reports on a large-scale experiment introducing and evaluating intelligent tutoring in an urban High School setting. Critical to the success of this project has been a client-centered design approach that has matched our client's expertise in curricular objectives and classroom teaching with our expertise in artificial intelligence and cognitive psychology. The Pittsburgh Urban Mathematics Project (PUMP) has produced an algebra curriculum that is centrally focused on mathematical analysis of real world situations and the use of computational tools. We have built an intelligent tutor, called PAT, that supports this curriculum and has been made a regular part of 9th grade Algebra in 3 Pittsburgh schools. In the 1993-94 school year, we evaluated the effect of the PUMP curriculum and PAT tutor use. On average the 470 students in experimental classes outperformed students in comparison classes by 15% on standardized tests and 100% on tests targeting the PUMP objectives. This study provides further evidence that laboratory tutoring systems can be scaled up and made to work, both technically and pedagogically, in real and unforgiving settings like urban high schools.




Table of Contents

       Introduction 1    
A Curriculum and Cognitive Tutor for Practical Algebra 2    
     Client-Centered Design and the PUMP Curriculum 2.1    
     Principled Design of Cognitive Tutors 2.2    
     Description of PAT: A Cognitive Tutor for Practical Algebra 2.3    
     Special Features of the PUMP Classroom 2.4    
A Large-Scale Classroom Experiment 3    
     Method 3.1    
     Assessment Design 3.2    
     Results and Discussion 3.3    
Conclusion 4    
Acknowledgments 4    
References 5    




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