In cognitive diagnosis modeling, the attributes required for each item are specified in the Q-matrix. The traditional way of constructing a Q-matrix based on expert opinion is inherently subjective, consequently resulting in serious validity concerns. The current study proposes a new validation method under the deterministic inputs, noisy “and” gate (DINA) model to empirically validate attribute specifications in the Q-matrix. In particular, an iterative procedure with a modified version of the sequential search algorithm is introduced. Simulation studies are conducted to compare the proposed method with existing parametric and nonparametric methods. Results show that the new method outperforms the other methods across the board. Finally, the method is applied to real data using fraction-subtraction data.
In cognitive diagnosis modeling, the attributes
required for each item are specified in the Q-matrix. The traditional way of
constructing a Q-matrix based on expert opinion is inherently subjective,
consequently resulting in serious validity concerns. The current study proposes
a new validation method under the deterministic inputs, noisy “and” gate (DINA)
model to empirically validate attribute specifications in the Q-matrix. In
particular, an iterative procedure with a modified version of the sequential
search algorithm is introduced. Simulation studies are conducted to compare the
proposed method with existing parametric and nonparametric methods. Results
show that the new method outperforms the other methods across the board.
Finally, the method is applied to real data using fraction-subtraction data.
Primary Language | English |
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Subjects | Studies on Education |
Journal Section | Articles |
Authors | |
Publication Date | May 19, 2018 |
Submission Date | February 2, 2018 |
Published in Issue | Year 2018 Volume: 5 Issue: 2 |