Difference between revisions of "CUMULATE user and domain adaptive user modeling"

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(Study 1)
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This stream of work is aimed at improving [[CUMULATE]]'s [[CUMULATE asymptotic knowledge assessment|legacy]] ''one-fits-all'' algorithm for  modeling user's problem-solving activity and creating a context-sensitive user modeling algorithm adaptable/adaptive to individual users' cognitive abilities as well as to individual problem complexities.
 
This stream of work is aimed at improving [[CUMULATE]]'s [[CUMULATE asymptotic knowledge assessment|legacy]] ''one-fits-all'' algorithm for  modeling user's problem-solving activity and creating a context-sensitive user modeling algorithm adaptable/adaptive to individual users' cognitive abilities as well as to individual problem complexities.
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{{ambox| text='''This page is under construction. More content will be added soon'''|type=exclamation}}
  
 
=Creating Parametrized User Modeling Algorithm=
 
=Creating Parametrized User Modeling Algorithm=
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==Study 1==
 
==Study 1==
 
This study involves retrospective comparative evaluation of the [[CUMULATE]]'s [[CUMULATE asymptotic knowledge assessment|legacy]] and [[CUMULATE parametrized asymptotic knowledge assessment|parametrized]] user modeling algorithms. The evaluation is done using [[CUMULATE Usage Logs|usage logs]] collected from 6 Database Management courses offered during Fall 2007 and Spring 2008 semesters at the [http://www.pitt.edu University of Pittsburgh], [http://www.ncirl.ie National College of Ireland], and [http://www.dcu.ie Dublin City University]. Each course had roughly the same structure and an identical set of problems served by [[SQLKnoT]] system.
 
This study involves retrospective comparative evaluation of the [[CUMULATE]]'s [[CUMULATE asymptotic knowledge assessment|legacy]] and [[CUMULATE parametrized asymptotic knowledge assessment|parametrized]] user modeling algorithms. The evaluation is done using [[CUMULATE Usage Logs|usage logs]] collected from 6 Database Management courses offered during Fall 2007 and Spring 2008 semesters at the [http://www.pitt.edu University of Pittsburgh], [http://www.ncirl.ie National College of Ireland], and [http://www.dcu.ie Dublin City University]. Each course had roughly the same structure and an identical set of problems served by [[SQLKnoT]] system.
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=== Scenario ===
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Legacy CUMULATE algorithm and 3 versions of parametrized CUMULATE algorithm. The versions differed in the parameters used for user modeling.
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* First, was an attempt to shadow the [[CUMULATE asymptotic knowledge assessment|legacy]] algorithm by ''guessing'' the best parameters for modeling, without discriminating individual user and problem differences.
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* The second version, did not discriminate users/problems as well, but the parameters were obtained by fitting the
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=== Results ===
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=== Publication ===
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=== References ===
  
 
= Contacts =
 
= Contacts =
 
[[User:Myudelson|Michael V. Yudelson]]
 
[[User:Myudelson|Michael V. Yudelson]]

Revision as of 02:42, 9 April 2009

This stream of work is aimed at improving CUMULATE's legacy one-fits-all algorithm for modeling user's problem-solving activity and creating a context-sensitive user modeling algorithm adaptable/adaptive to individual users' cognitive abilities as well as to individual problem complexities.

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This page is under construction. More content will be added soon


Creating Parametrized User Modeling Algorithm

To overcome the shortcomings of the CUMULATE's legacy user modeling algorithm, a new parametrized version of it has been devised. A set of studies is set up to evaluate the new algorithm as well as its adaptability/adaptivity.

Study 1

This study involves retrospective comparative evaluation of the CUMULATE's legacy and parametrized user modeling algorithms. The evaluation is done using usage logs collected from 6 Database Management courses offered during Fall 2007 and Spring 2008 semesters at the University of Pittsburgh, National College of Ireland, and Dublin City University. Each course had roughly the same structure and an identical set of problems served by SQLKnoT system.

Scenario

Legacy CUMULATE algorithm and 3 versions of parametrized CUMULATE algorithm. The versions differed in the parameters used for user modeling.

  • First, was an attempt to shadow the legacy algorithm by guessing the best parameters for modeling, without discriminating individual user and problem differences.
  • The second version, did not discriminate users/problems as well, but the parameters were obtained by fitting the

Results

Publication

References

Contacts

Michael V. Yudelson