Apr 27th Meeting

First Presenter: Michael Yudelson
Topic: Comparison of 3 Paper Sharing Systems (CoPE, CUL, Comtella)

Michael compared three similar system in the purpose to share papers - CoPE, CiteULike, and Comtella. He compared them from various aspects such as support of community, navigation and interactivity, along with demonstration of each system. After his presentation, he collected questionnaires asking opinions about paper sharing system and explained the results. Privacy is important and quality and easy of use is also necessary to users. The discussion about what makes a certain system superior to others was followed. In order to attract world, the new functionality to meet users' needs like the CiteUlike case and usability should be considered as well.

Second Presenter: Rosta Farzan
Topic: 'Social' Systems: Designing Digital Systems that Support Social Intelligence

Rosta made a presentation about a paper regarding how to design a system to support social intelligence. Using social proxy, the authors provided several visualizations to show activities happened in online chat rooms. The information about the presence and activities can help create coherent behavior comprising social intelligence. In our system, Dr. Brusilovsky pointed that it is necessary to share the social activities happening inside of our system and the information about who contribute what in the system. Dr. Vassileva suggested that using Comtella it was motivational to users to see the effect of their actions.

PAWS Meeting 04/20/2007

It was a first meeting of the "Social" Month. Though Jill's presentation was not social, but an interesting one.

1. Sharon was presenting Dogear system - IBM-developed system for social bookmarking on the enterprise. Nothing too novel. They took everything good from del.icio.us and implemented it in nice and fancy way. The main question they have - can the social bookmarking system be beneficial in the enterprise settings. They use REST as a communication protocol. Tags and bookmarks have a representation in form of RSS feeds, hence it is possible to subscribe, for example on some user's bookmarks. They also plan to implement recommendation based on collaborative filtering.
They describe an experiment with 686 participants. Only 1/4 of them created tags and bookmarks. Half of them navigated bookmarked resources. The question then, - what did the rest of "participants"?
They did some quantitative analysis of numbers of tags per bookmark, number of people using a bookmark etc., they also applied some social network analysis to identify the connections between people through the resources they tag, bookmark and navigate.

2. Jill talked about a system Volant, that implements a rather novel methodology for Web search. The main motivation behind the system is following: Modern Search engines do not take into account that the querying is only a first step in the search process; usually after people query an engine they start navigating through linked pages. Hence the idea is that the search engine should not try to generate the pages which are the best answers to a query, instead they should direct users to the pages that are the best entry points, starting from which a user can easily navigate to the page meeting his/her information goal.
Then there was a lot of math formulating the work of a search engine exploiting navigational patterns existing on the web and retrieving the best entry points. And at the end it some evaluation was described, a very thin, though.
Interesting project.

PAWS Meeting April 13, 2007

First Paper: Design and Evaluation of an Adaptive Incentive Mechanism for Sustained Educational Communities
Presenter: Rosta Farzan

Online communities have faced insufficient participation. Even though providing incentives is such a good way to solve the problem, its affect gives too much, low quality participation. The authors proposed a new incentive mechanism to generate quality and quantity contribution from online users. From a related work, collaborative quality evaluation mechanism, not only need user participation but also quality control. In academia, we measure quality of papers or journals by counting times they are cited as well as in online communities, counting on numbers of clicks. But not every click means a positive attitude. In an explicit way, measuring on user rating has a drawback, "rich get richer".

The authors came up with the Comtella, online community system. Comtella provides an ability to share class-related web-resources. C0mtella also has a mechanism encouraging users to rate resources by providing a reward to user contribution. Users can contribute on the system by two ways: one is to post a new URL web resource or, two is to rate others' contribution. Each user receives a certain number of rating points to use. The number of rating points varies on a level of membership. Calculating adaptive rewards is done by two models, community model and individual model. Community model controls a number of contributions and usefulness of news resources. Individual model monitors quality of rating, based on the assumption that the average of all ratings the resource gets should be equal. From their experiment, users in the test group were more active in rating articles and the articles with higher ratings were more likely to be chosen to summarize. Limitations of Comtella are a scale of rating is too rigid, 1 and -1. The system should provide more on the aspect of rating such as originality, interestingness, relevancy etc. Another thing is the system should not reveal the absolute c-point. It should provide only relative ordering of the article.

Discussion
The features Comtella has should be integrated to CoPE. CoPE would get benefit from an ability for users to rate articles.

Second Paper: Classifying Learning Engagement Through Integration of Multiple Data Sources.
Presenter: Tomek Loboda

The paper is about combination of self reports from high school students and teacher reports. The system classifies action sequences into five finite state machines. The motivation of self reports is related to cluster of behaviors associated with learning success such as effective monitoring, study behaviors, etc. The motivation of learners and self-regulation can be a stronger predictor of learning performance than prior academic achievement. The web-based tutoring system for high school mathematics was set to prepare students for high-quality exams such as SAT.

In summary, sources can be integrated and used to classify students' beliefs into learning situation. Self reports from learners can be identified as disengaged but like other systems that students use ITS in a manner eliciting learning pattern. Results indicated that there is possibility that if we seed this models in advance with learner profile data which is timely and inexpensive to elicit and with strategies quite predictive will be used once when student begin studying with the ITS.