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knowledge_assessment:q-matrix [2012/07/05 13:09]
jpetrovic
knowledge_assessment:q-matrix [2012/07/05 13:34]
jpetrovic
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 all students for a given set of n questions. To avoid of local minima, each hill-climbing ​ all students for a given set of n questions. To avoid of local minima, each hill-climbing ​
 search is seeded with different random Q-matrices and the best of these is kept.  search is seeded with different random Q-matrices and the best of these is kept. 
 +
 +When forming a correlation matrix, we lose individual student data in favor of calculating average relationships between questions. The q-matrix method is optimized to assign each student the most appropriate knowledge state, using all available response data for each student.
  
knowledge_assessment/q-matrix.txt ยท Last modified: 2023/06/19 18:03 (external edit)