Slideshow automata

7/31/2019 Slideshow automata

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NSF CCLI Showcase

SIGCSE 2006


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NSF CCLI ShowcaseSIGCSE 2006

Thursday, 10:30 a.m.12:00 p.m.

Program Visualization using Virtual WorldsStephen Cooper, St. Josephs UniversityWanda Dann, Ithaca College

Barbara Moskal, Colorado School of MinesRandy Pausch, Carnegie Mellon University

Online Programming Tutors for Computer Science IAmruth Kumar, Ramapo College of New Jersey

Extending the Next Generation Robot Laboratory to Increase Diversity inUndergraduate CS ProgramsMaria Gini, University of MinnesotaKaren Sutherland, Augsburg CollegeJanice Pearce, Berea College


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Program Visualization using

Virtual Worlds

Stephen Cooper, Saint Josephs UniversityWanda Dann, Ithaca College

Barbara Moskal, Colorado School of MinesRandy Pausch, Carnegie Mellon University

CCLI NSF-0339734Novices author 3Dmovies and createinteractive computer

games as they learnobject-orientedprogramming concepts

-- Increasing retention

-- Attracting more majors

Running professionaldevelopment workshopsfor teachers


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Problets: Online ProgrammingTutors 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: [email protected]


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Objectives:

To increase confidence through hands-onprogramming experiences.

To solve real-world and open-endedproblems.

To foster cooperation by working ingroups.

Extending the Next Generation RobotLaboratory to Increase Diversity in

Undergraduate CS Programs

Process:

We are developing programming

modules designed to encourageundergraduates majoring in fields suchas health professions, business, art,and education to take more computerscience courses. The approach iscentered around using the AIBO Sonyrobot dogs at the very beginning of thecomputer science curriculum.

Maria Gini,University of MinnesotaJan Pearce, Berea CollegeKaren Sutherland, Augsburg College

Extending the Next Generation RobotLaboratory to Increase Diversity in

Undergraduate CS Programs


6/16


Friday 10:30 a.m.12:00 p.m.

The UC-WISE project: Online Curricula for Monitored, Closed-lab First-year CSCoursesMike Clancy, Marcia Linn & Nate Titterton, University of California at Berkeley

Integrating Algorithm Visualization into Computer Science EducationScott Grissom, Grand Valley State UniversityMyles McNally, Alma CollegeThomas Naps, University of Wisconsin, Oshkosh

CS 0.5: A New Approach to Introductory Computer Science for MajorsRobert H. Sloan & Patrick Troy, University of Illinois at Chicago

Intelligent Tutoring System for CS-I and II LaboratoryJungsoon Yoo, Sung Yoo, Chrisila Pettey, Judy Hankins, Cen Li & Suk Seo,Middle Tennessee State University


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The UC-WISE project: Online curriculafor monitored, closed-lab first-year CS courses

(Michael Clancy, Marcia Linn, Nate Titterton, all at U.C. Berkeley)

Curriculum Components a wide variety of programming activities,

including interactive and constrainedprogramming activities with real-timecode 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 ofimmediate feedback for students;

analysis of student misconceptionsrevealed by the rich variety of activities inUC-WISE courses;

comparison of online vs. face-to-facecollaborative activities;

exploration of differential benefits forunderrepresented populations;

design of instructor support systemsduring phases of course creation,delivery, refinement, and research.

Lab instructors monitor studentunderstanding and provide targetedtutoringwhere and when it will be mostappropriate.

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 newcourse elements, and collect review comments from experienced course developers.


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Integrating Algorithm Visualization intoComputer Science Courses

JHAV: Java Hosted Algorithm Visualization Environment

Goal: Development of a comprehensive suite of visualization-basedmaterials 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


9/16

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


10/16

Adaptive Tutor for OnlineLearning

Middle Tennessee State UniversityJ. 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 strategyadaptation

Student progress monitoring system Question generation module

Automatic grading


11/16


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 HartfordZdravko Markov, Central Connecticut State UniversityTodd 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


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jGRASPA Framework for Integrating Visualizations of Software

James Cross, Dean Hendrix, David UmphressAuburn University

Control Structure Diagram UML Class Diagram

Data Structure Diagram


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Project MLExAI: Machine Learning Experiences in AI

Ingrid Russell, University of HartfordZdravko Markov, Central Connecticut State University

Todd Neller, Gettysburg College

ObjectivesEnhance student learning experience byimplementing a unifying theme of machine learningto tie together core AI topics.

Increase student interest and motivation to learn AIby providing a framework for the presentation of themajor AI topics that emphasizes the strongconnection between AI and computer science.

Highlight the bridge that machine learning providesbetween AI technology and modern softwareengineering.

Introduce students to an increasingly importantresearch area, thus motivating them to pursuefurther study in this area.

Project GoalThe project goal is to develop aframework for teaching core AItopics with a unifying theme ofmachine learning. A suite ofhands-on term-long projects aredeveloped, each involving thedesign and implementation of alearning system that enhances a

commonly-deployed application.


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SIGCSE NSF ShowcaseMarch, 2006

A radical approach to teaching object-oriented programming

Kate Sanders & Ann Moskol

Rhode Island College

Objects, inheritance, andpolymorphism early

Graphical examples

Stress on design

I am a

composite

object


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ObjectivesEnhance learning of automata andlearning experience

Expose students to current applicationsof automata

Provide glimpses of the variety of finiteautomata including tree and DAG automata

Background

Problems in learning Automata Theory

Too abstract

Too difficult

Student Perception: Of little use

Student Perception: Dated material

Methods

Enhance and integrate visualization tools,e.g., JFLAP from Duke and LRR from

University of Houston

Add current applicationsAdd useful examples of automata

We have:

Enhanced JFLAP to generate randomstrings for debugging of automata designs

We have developed:

Lecture notes with HTML and PowerPointslide presentations that include JFLAP

animations

New course materials that includeapplications of finite automata

New lab assignments and problem sets A Web repository with teaching materialsGraphical interface, RuleMaker, forvisualizing tree automata

Results

Inspired students to work on LRR andautomata projects

Positive end of course evaluations,

tool/website appreciation

Students helped with slides and web page

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

By Rakesh Verma, Pavan Podila and Saquib HakimComputer Science Department

University of Houston, Houston, TX 77204-3010

http://www.cs.uh.edu/~rmverma


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Saturday 10:30 a.m.12:00 p.m.

Due to logistical reasons, the Saturdayshowcase session has been cancelled

Documents

Slideshow automata