WPI Worcester Polytechnic Institute

Computer Science Department
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AIRG Topics - Fall 2010

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


Dates and topics for this semester are as follows:

Sept 2
AIRG Organizational Meeting (Coordinator: Joe Beck)

Sept 9
Yue Gong
"How to Construct More Accurate Student Models:
  Comparing and Optimizing Knowledge Tracing and Performance Factor Analysis"
    Student modeling is a fundamental concept applicable to a variety of intelligent tutoring systems (ITS). However, there is not a lot of practical guidance on how to construct and train such models. This paper compares two approaches for student modeling, Knowledge Tracing (KT) and Performance Factors Analysis (PFA), at predicting individual student trials. We explore the space of design decisions for each approach and find a set of "best practices" for each. In a head to head comparison, we find that PFA has considerably higher predictive accuracy than KT: R2 of 0.18 vs. 0.07 and AUC of 0.76 vs. 0.68 (p<0.001 for both). In addition, we found that PFA's parameter estimates were more plausible. Our best-performing model was a variant of PFA that ignored the tutor's transfer model; that is, it assumed all skills influenced performance on all problems.

Sept 16
Dovan Rai
"Self-disciplined students"
    In this study, we are interested to see the impact of self-discipline on students' knowledge and learning. Self-discipline can influence both learning rate as well as knowledge accumulation over time. We used a Knowledge Tracing (KT) model to make inferences about students' knowledge and learning. Based on a widely used questionnaire, we measured students' level of self-discipline. When we analyzed the relation of students' self-discipline with their knowledge attributes, we found that high self-discipline students had significantly higher initial knowledge, but there is no consistent relationship of learning while using the tutor. Moreover, higher self-discipline students seemed more careful with respect to making careless mistakes. We also found that a quarter of students who were not consistent in their survey response had significantly lower performance, knowledge and learning.

Sept 23
Matt Bachmann
    The presentation will be about performing user modeling in an inquiry environment. The purpose of the talk is to present preliminary results, and to solicit feedback on how to conduct this MS thesis research.

Sept 30
Dave Brown
"The Curse of Creativity"
    Computational design creativity is hard to study, and until fairly recently it has received very little attention. Mostly the focus has been on extreme non-routine cases. But there are hard sub-problems and others ways of moving towards creative systems that are worth considering. This paper presents three of the alternatives, discussing one in more depth: i.e., to look at what changes can be made to routine design systems in order to produce more creative outputs. This focuses on working "upwards" towards creativity, examining smaller, ingredient decisions that make a difference to the result. As the amount of creativity displayed by a design is a judgment made by some person or group, it should be possible to investigate the degree of impact of changes to routine design mechanisms. This will contribute to our understanding of less "extreme" reasoning that leads to judgments of increased creativity: i.e., the foundation on which other methods rest.

Oct 7
Neil Heffernan and Yutao Wang
    Neil will provide an overview of some research done in the ASSISTment lab for about 20 minutes. Then both will present their most recent finding. We are trying to see what is the right way to use hints and attempts in predicting student performance. We have results we want to share with the group. This work is hot off the shelf. In fact it is not even on the shelf yet!

Oct 21
Andrew Tremblay (first half)
"Axeawesome: A Return to Green Globs"
    Green Globs provided students with "a meaningful and highly motivating experience with the graphing of equations" and was celebrated for its novelty, but has since become ignored by present-day students due to its antiquated form. This project, named "Axeawesome", tackles the same goal in a modern context, including a more pleasing aesthetic and online publication with data-mining capability. This talk will present the current state of Axeawesome, as well as request advice on how to design the data analysis phase of the project.

Joseph Beck (second half)
"Why are we fighting over when to disaggregate? An automated approach to model construction"
    A common discussion point is when to disaggregate data vs. when to collapse points together. This discussion is another version of the bias/variance tradeoff in machine learning. This talk will propose an automated approach to constructing models that automatically tests various disaggregation possibilities and uses bootstrapping to decide whether such a disaggregation is sensible.

Oct 28
Dan Spitz
"The Role of Surprise in Design Creativity"
    One of the key aspects that people use to judge whether a designed product is creative is "Novelty". Studies show that this breaks down into the components "Originality" and "Surprise". In order to produce a computational system that can produce creative designs it is conjectured that the system must be able to judge the creativity of complete or partial designs. Hence, such a system must be able to judge Novelty. There is research in progress on computational judgement of originality, and of surprise, but much more of the former. This talks presents progress on MQP work being done to model surprise and to build a prototype system that can demonstrate surprise in appropriate situations.

Nov 4
Jonathan Gibbons
"Structure optimization for low-end additive manufacturing"
    Costs for additive manufacturing processes have dropped well into the hobbyist range, and are now being used as on-demand manufacturing for a variety of goods beyond prototypes. This project is exploring structure optimization methods that incorporate knowledge of the specific manufacturing constraints and preferences of the fused filament fabrication process, as used by the sub-$1500 RepRap and Makerbot machines. Two genetic algorithm methods and an extension of the solid isotropic material penalization method are being developed, with the aim of forming the foundation of a practical system to automatically reduce the material use and fabrication time of objects produced using these machines.

Nov 11
Yue Gong
"Evaluating web-based resources for educational systems"
    Intelligent Tutoring Systems have been shown to have positive effect on helping student learning. However, almost all types of the current tutorial content is context-sensitive, thus hard to be reused in other questions, even for those questions about the same topic. This talk will propose an idea of using web pages as a new means to help student learning in an ITS. We will discuss the framework of how the idea can be applied, as well as relevant research questions, and how those questions can be answered by using AI techniques. For example, in order to conduct experiments which are able to efficiently allocate "trials" for figuring out which web pages are good, the technique of Reinforcement Learning can be used. Our goal is to maximize the payoff (determine the usefulness of web pages), yet use as few trials as possible, while considering the trade-off between exploration and exploitation. In addition, how to evaluate the effect of a web page on student learning is another important problem which could be addressed by applying a variety of student modeling techniques, such as augmented knowledge tracing models, learning decomposition. Finally, we want to use machine learning to extract knowledge (web page features) from the process of web page evaluations, so that the extracted knowledge can be used in the future for refining the web page selection. This talk will discuss these approaches, and solicit feedback for other methods.

Nov 18
Jason Zhang
Meeting cancelled

Nov 25
Thanksgiving Break - No Meeting

Dec 2
Kaiyu Zhao
"Structure learning in temporal models"
    When learning a model, tradeoff between the capability of representation and the complexity has always to be made. In this study, a statistical learning approach is introduced to facilitate the model constructing process, specifically, the student modeling. Knowledge tracing as one of the well known models is powerful in interpretation and also tractable in computation. However, if any extension of KT exists that is able to enrich the interpretability and avoids the issue of over complicating the real world, the causalities as well as the changes of the world will be better captured through the model. A methodology is proposed in finding such models and preliminary results will be presented together.

Dec 9
Yingmei Qi, Shubhendu Trivedi, and Kaiyu Zhao
"Blind Source Separation in Magnetic Resonance Images"
    Blind source separation has received much attention in the past few years because of its wide range of applications (Neural Networks, Financial Series Data, Denoising, EEG/MEG data). One important method to do Blind Source Separation is Independent Component Analysis. And an important application is in MR Images. A MR Image can be considered to be a mixture as it is composed of a number of different tissue types such as white matter, gray matter etc. Source Separation in fMRI is however easier as compared to MRI as there are enough number of mixtures from which to estimate the hidden sources. The problem is much harder in MRI as the number of mixtures is just three (T1, T2 and PD), while the number of sources is around 10, thus being an under-determined system. Not surpisingly this problem has not recieved much attention. This project explores ways to solve this problem. Also, ICA assumes independence of the sources, but it is likely that this assumption does not hold. We also explore a method to do blind source separation when some correlation between the sources is assumed. The results are compared and more ideas on solving this problem presented.

-- Wed Dec 15 -- Last day of Semester


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AIRG Coordinator / Wed, 8 Dec 2010