EDUFORM --  A Tool for Creating Adaptive Questionnaires

DMCA

EDUFORM -- A Tool for Creating Adaptive Questionnaires (2004)

Cached

Download Links

[cosco.hiit.fi]

by Miikka Miettinen , Petri Nokelainen , Jaakko Kurhila , Tomi Silander , Henry Tirri

Citations

12411	Elements of Information Theory - Cover, Thomas - 2006 (Show Context) Citation Context ...time, the most informative set of questions to ask next is the one that is expected to change the profile distribution most. EDUFORM searches for this set by maximizing the Kullback-Leibler distance (=-=Cover and Thomas 1991-=-) between the current distribution and the distribution that would be expected if answers to a particular set of additional questions were received. The first questions are the same for everybody, but...
1507	Bayesian theory, - Bernardo, Smith - 2009 (Show Context) Citation Context ...phase, where the model is used for adaptive questioning. The design is generic and allows the application of any type of predictive model suitable for the task. We have adopted the Bayesian approach (=-=Bernardo and Smith, 2000-=-) and use the language of probability distributions to describe the profiles.sIn practice, the profiles are constructed by dividing the data vectors to a number of mutually exclusive groups and summar...
603	Adaptive hypermedia. User Modeling and User Adapted Interaction, - Brusilovsky - 2001 (Show Context) Citation Context ...quisite for effective adaptation. Some systems are able to accumulate useful data during the course of their interaction with the user, but additional input must almost always be provided explicitly (=-=Brusilovsky 2001-=-). EDUFORM could be employed for gathering this information efficiently or creating probabilistic user profiles for direct application in the other system. The current version of EDUFORM is suitable f...
156	Ordinal data modeling - Johnson, Albert - 1999
16	Probabilistic instance-based learning - Tirri, Kontkanen, et al. - 1996 (Show Context) Citation Context ...a vectors to a number of mutually exclusive groups and summarizing the contents of each group in a probability distribution. The details of the procedure are described in (Kontkanen et al. 1996) and (=-=Tirri et al. 1996-=-), but the underlying intuitive idea can be illustrated briefly as follows. Each profile is a prototype, which can be employed for creating a more compact representation of the data. In order to descr...
14	Motivation and Self-regulation in Learning. In - Ruohotie - 2002
10	Predictive Data Mining with Finite Mixtures - Kontkanen, Myllymäki, et al. - 1996 (Show Context) Citation Context ...structed by dividing the data vectors to a number of mutually exclusive groups and summarizing the contents of each group in a probability distribution. The details of the procedure are described in (=-=Kontkanen et al. 1996-=-) and (Tirri et al. 1996), but the underlying intuitive idea can be illustrated briefly as follows. Each profile is a prototype, which can be employed for creating a more compact representation of the...