WPI Worcester Polytechnic Institute

Computer Science Department

AIRG Topics - Spring 2008

Our group meets on Thursdays at 11:00 a.m., FL 246.

Jan 17
No Meeting

Jan 24
AIRG Organizational Meeting

Jan 31
Video: Peter Stone
"Robust, fully autonomous agents in the real world"
IJCAI 2007 Computers and Thought Lecture

Feb 7
Prof Charles Rich
"Overview of Intelligent User Interfaces"

Feb 14
Academic Advising Appointment Day: No meeting

Feb 21
Leena Razzaq
"A Comparison of Traditional Paper-and-Pencil Homework with Web-Based Homework Assistance"
    Web-based homework assistance is already popular in colleges. Blackboard (www.blackboard.com), WebAssign, (webassign.com), MasteringPhysics (masteringphysics.com) and WeBWorK (http://webwork.rochester.edu) are all systems that have thousands of student users at the college level, but K-12 web-based homework assistance lags behind. Systems such as Study Island (www.studyisland.com) and PowerSchool (powerschool.com) are gaining popularity with K-12 teachers and it seems likely that the use of web-based homework assistance for K-12 will increase as the digital divide between students narrows, teachers become more comfortable with the technology and teachers have access to systems that are low cost or that are free. The important question is, do such systems help students to learn more than doing traditional paper-and-pencil homework? In this talk, I will present results from two studies comparing the two that show promising results for using the computer to do homework.

Feb 28
Michael A. Sao Pedro
"A Dynamic Constraint Reasoning Approach to Mixed-Initiative Intermodal Lift Planning"

Mar 6
Spring Recess

Mar 13
Mingyu Feng
"Can an Intelligent Tutoring System Predict Math Proficiency as Well as a Standardized Test?"
    It has been reported in previous work that students. online tutoring data collected from intelligent tutoring systems can be used to build models to predict actual state test scores. In this paper, we replicated a previous study to model students. math proficiency by taking into consideration students. response data during the tutoring session and their help-seeking behavior. We found evidence that our model can do as well as a standardized test. To evaluate our results, we propose a new method of using students test scores from multiple years (referred to as cross-year data) for determining whether a student model is as good as the standardized test to which it is compared at estimating student math proficiency. We conclude that the approach of using student interaction data during the tutoring session to predict state test scores works relatively well. We stress that the contribution of the paper is the methodology of using student cross-year state test score to evaluate a student model against a standardized test.

Mar 20
Yu Guo
"Bottom Out Hints in Assistments"

Mar 27

Apr 3

Apr 10

Apr 17
Keith A. Pray
"Data Dimensionality Reduction Techniques"

Apr 24

Apr 25
Last day of Semester

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AIRG Coordinator / Fri, 22 Feb 2008