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As Table 2 suggests, item parameters drawn from the released 2007 TIMSS grade 4 assessment varied in both difficulty and discrimination, although these values would be considered typical in such assessments.
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A two parameter IRT model was selected in order to be able to estimate both a difficulty and discrimination parameter.
For both statement difficulty and discrimination, we fitted a mixed-effects model to test for differences between the way students answered statements that address misconceptions versus statements that address key concepts.
θ j represents the ability of student j, and b i is the difficulty parameter of question i. 2) Two parameter logistic model (2PL): This model is a slightly more complex model, as it considers both the question's difficulty and discrimination.
IRT can provide two useful measures; difficulty and discrimination, both of which are technical properties of the Item Characteristic Curve (ICC).
Our item analysis showed that the questions' difficulty and discrimination indices were in agreement with published recommended standards and discriminated effectively between high- and low-scoring students.
Analyses of the difficulty and discrimination index were carried out for the items included in the on-line test.
Questions were analyzed for difficulty and discrimination.
In conditions with large DIF, differences were 1.00 and.80 for difficulty and discrimination parameters, respectively.
Similar to CTT, IRT models are used to assess the question's difficulty and discrimination.
Focal groups that did not contain DIF items had difficulty and discrimination parameters equal to those of the reference group.
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