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knowledge_assessment:q-matrix [2012/07/05 13:09] jpetrovic |
knowledge_assessment:q-matrix [2012/07/05 14:41] jpetrovic |
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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. | ||
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+ | As Sellers found in her research, the results obtained through | ||
+ | q-matrix analysis seem to describe relationships among variables in interpretable ways. | ||
+ | Factor analysis and principal components analysis, on the other hand, do not readily offer | ||
+ | interpretable results. | ||
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+ | Later researchers found that, although the q-matrix model was a good way to compare student data to a concept model, expert-constructed q-matrices did not correspond to student data any better than random q-matrices did. | ||
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+ | the findings in Brewer's previous research, which found that the factor analysis method performed poorly in comparison with the q-matrix | ||
+ | method when fewer observations were available. |