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NSF CCLI Showcase

NSF CCLI Showcase. SIGCSE 2006. NSF CCLI Showcase SIGCSE 2006. Thursday, 10:30 a.m.—12:00 p.m. Program Visualization using Virtual Worlds Stephen Cooper, St. Joseph’s University Wanda Dann, Ithaca College Barbara Moskal, Colorado School of Mines Randy Pausch, Carnegie Mellon University

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NSF CCLI Showcase

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  1. NSF CCLI Showcase SIGCSE 2006

  2. NSF CCLI ShowcaseSIGCSE 2006 Thursday, 10:30 a.m.—12:00 p.m. Program Visualization using Virtual Worlds Stephen Cooper, St. Joseph’s University Wanda Dann, Ithaca College Barbara Moskal, Colorado School of Mines Randy Pausch, Carnegie Mellon University Online Programming Tutors for Computer Science I Amruth Kumar, Ramapo College of New Jersey Extending the Next Generation Robot Laboratory to Increase Diversity in Undergraduate CS Programs Maria Gini, University of Minnesota Karen Sutherland, Augsburg College Janice Pearce, Berea College

  3. Program Visualization using Virtual Worlds Novices author 3D movies and create interactive computer games as they learn object-oriented programming concepts -- Increasing retention -- Attracting more majors Running professional development workshops for teachers CCLI NSF-0339734 Stephen Cooper, Saint Joseph’s University Wanda Dann, Ithaca College Barbara Moskal, Colorado School of Mines Randy Pausch, Carnegie Mellon University

  4. Problets: Online Programming Tutors for Computer Science I • Helps students learn by solving problems • Explains the execution of program code • Adapts to the learning needs of students • Available for C/C++/Java/C# • For expressions, selection, loops, functions • Provides class summary to instructors • Runs on recent Java-aware browsers • Free for educational use • Contact: amruth@ramapo.edu

  5. Extending the Next Generation Robot Laboratory to Increase Diversity in Undergraduate CS Programs Extending the Next Generation Robot Laboratory to Increase Diversity in Undergraduate CS Programs Maria Gini,University of Minnesota Jan Pearce, Berea College Karen Sutherland, Augsburg College Process: We are developing programming modules designed to encourage undergraduates majoring in fields such as health professions, business, art, and education to take more computer science courses. The approach is centered around using the AIBO Sony robot dogs at the very beginning of the computer science curriculum. Objectives: • To increase confidence through hands-on programming experiences. • To solve real-world and open-ended problems. • To foster cooperation by working in groups.

  6. NSF CCLI ShowcaseSIGCSE 2006 Friday 10:30 a.m.—12:00 p.m. The UC-WISE project: Online Curricula for Monitored, Closed-lab First-year CS Courses Mike Clancy, Marcia Linn & Nate Titterton, University of California at Berkeley Integrating Algorithm Visualization into Computer Science Education Scott Grissom, Grand Valley State University Myles McNally, Alma College Thomas Naps, University of Wisconsin, Oshkosh CS 0.5: A New Approach to Introductory Computer Science for Majors Robert H. Sloan & Patrick Troy, University of Illinois at Chicago Intelligent Tutoring System for CS-I and II Laboratory Jungsoon Yoo, Sung Yoo, Chrisila Pettey, Judy Hankins, Cen Li & Suk Seo, Middle Tennessee State University

  7. Curriculum Components a wide variety of programming activities, including interactive and constrained programming activities with real-time code analysis and execution; online and face-to-face collaborations; embedded assessments, surveys, and self-tests. Research Areas evaluation of activities not in traditional-format courses, and of various kinds of immediate feedback for students; analysis of student misconceptions revealed by the rich variety of activities in UC-WISE courses; comparison of online vs. face-to-face collaborative activities; exploration of differential benefits for underrepresented populations; design of instructor support systems during phases of course creation, delivery, refinement, and research. The UC-WISE project: Online curricula for monitored, closed-lab first-year CS courses(Michael Clancy, Marcia Linn, Nate Titterton, all at U.C. Berkeley) CCLI project goal: Provide technology and curricula for lab-based CS 1 and CS 2. Longer-term goal: Allow instructors to build and customize courses, prototype new course elements, and collect review comments from experienced course developers. Lab instructors monitor student understanding and provide targeted tutoring where and when it will be most appropriate.

  8. Integrating Algorithm Visualization into Computer Science Courses • JHAVÉ: Java Hosted Algorithm Visualization Environment • Goal: Development of a comprehensive suite of visualization-based materials and best practices for teaching algorithms and data structures • Principal Investigators: • Scott Grissom (Grand Valley State University) • Myles McNally (Alma College) • Thomas Naps (University of Wisconsin - Oshkosh) • Website: http://www.jhave.org

  9. CS 0.5 - A New Approach to Introductory Computer Science • Problem: High Attrition Rates • Cause: Failure to Engage Students • Cause: One Size fits All Approach • Solution: Separate and Engage • Allow Experience Student to test out • Uses Media to Engage Students • Results: Higher Success Rate

  10. Adaptive Tutor for Online Learning Middle Tennessee State University J. Yoo, C. Pettey, S. Yoo J. Hankins, C. Li, S. Seo • Web-based lab environment to provide personalized assistance. • Tutor employs a two-step semi-supervised learning system for strategy adaptation • Student progress monitoring system • Question generation module • Automatic grading

  11. NSF CCLI ShowcaseSIGCSE 2006 Friday 2:00 p.m.—3:30 p.m. jGRASP: A Framework for Integrating Visualizations of Software (page 11) James Cross, Dean Hendrix & David Umphress, Auburn University Project MLExAI: Machine Learning Experiences in AI (page 12) Ingrid Russell, University of Hartford Zdravko Markov, Central Connecticut State University Todd Neller, Gettysburg College A Radical Approach to Teaching Object-oriented Programming(page 13) Kathryn E. Sanders & Ann Moskol, Rhode Island College Increasing Interaction and Visualization in the Computability Course (page 14) Rakesh M. Verma, Pavan Podila & Saquib Hakim, University of Houston

  12. jGRASPA Framework for Integrating Visualizations of SoftwareJames Cross, Dean Hendrix, David UmphressAuburn University Control Structure Diagram UML Class Diagram Data Structure Diagram

  13. Project MLExAI: Machine Learning Experiences in AI Project Goal The project goal is to develop a framework for teaching core AI topics with a unifying theme of machine learning. A suite of hands-on term-long projects are developed, each involving the design and implementation of a learning system that enhances a commonly-deployed application. • Objectives • Enhance student learning experience by implementing a unifying theme of machine learning to tie together core AI topics. • Increase student interest and motivation to learn AI by providing a framework for the presentation of the major AI topics that emphasizes the strong connection between AI and computer science. • Highlight the bridge that machine learning provides between AI technology and modern software engineering. • Introduce students to an increasingly important research area, thus motivating them to pursue further study in this area. Ingrid Russell, University of Hartford Zdravko Markov, Central Connecticut State University Todd Neller, Gettysburg College

  14. I am a composite object … A radical approach to teaching object-oriented programmingKate Sanders & Ann MoskolRhode Island College • Objects, inheritance, and polymorphism early • Graphical examples • Stress on design SIGCSE NSF Showcase March, 2006

  15. A Visual and Interactive Automata Theory Course Emphasizing Breadth of Automata By Rakesh Verma, Pavan Podila and Saquib Hakim Computer Science Department University of Houston, Houston, TX 77204-3010 http://www.cs.uh.edu/~rmverma Objectives • Enhance learning of automata and learning experience • Expose students to current applications of automata • Provide glimpses of the variety of finite automata including tree and DAG automata We have: • Enhanced JFLAP to generate random strings for debugging of automata designs We have developed: • Lecture notes with HTML and PowerPoint slide presentations that include JFLAP animations • New course materials that include applications of finite automata • New lab assignments and problem sets • A Web repository with teaching materials • Graphical interface, RuleMaker, for visualizing tree automata Background Problems in learning Automata Theory • Too abstract • Too difficult • Student Perception: Of little use • Student Perception: Dated material Conclusions & Future Work • It can be done! • Add more recent applications, e.g., Buchi automata and model checking • Write a new text book ?! • Acknowledgements: Thanks to M.F. Anwar. Work supported in part by NSF grant DUE 0311407 Methods • Enhance and integrate visualization tools, e.g., JFLAP from Duke and LRR from University of Houston • Add current applications • Add useful examples of automata Results • Inspired students to work on LRR and automata projects • Positive end of course evaluations, tool/website appreciation • Students helped with slides and web page

  16. NSF CCLI ShowcaseSIGCSE 2006 Saturday 10:30 a.m.—12:00 p.m. Due to logistical reasons, the Saturday showcase session has been cancelled

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