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
AIRG Coordinator /
Fri, 22 Feb 2008