Using a Mixture Irt Model to Improve Parameter Estimates When Some Examinees Are Amotivated.

Test-takers can be required to complete a test form, but cannot be forced to demonstrate their knowledge. Even if an authority mandates completion of a test, examinees can still opt to enter responses randomly. When a test has important consequences for individuals, examinees are unlikely to behave this way. However, random responding becomes more likely when the consequences associated with a test are less significant to the examinees. To thwart random responding, test administrators have explored methods to motivate examinees to respond attentively. Ultimately, differences in how examinees approach low-stakes tests are inevitable, and measurement models that account for this difference are needed. This dissertation provides an overview of the approaches that have been proposed for modeling low-stakes test data. Further, it specifically investigates the performance and utility of the mixed-strategies item response model (Mislevy & Verhelst, 1990) as one method of capturing amotivated examinees. Amotivated examinees are defined here as examinees who do not provide meaningful responses to any test items. A simulation study shows that if a normal item response model is used, parameter recovery rates are unacceptable when 9% or more of the examinees were amotivated. However, normal item response models may still be useful if less than 1% of examinees were amotivated. Use of the mixed-strategies item response model led to better parameter estimation than the normal item response model regardless of the proportion of amotivated examinees in the dataset. Additional research is needed to determine if using the mixed-strategies model results in satisfactory parameter recovery when greater than 20% of examinees were amotivated. A second study shows that when the mixed-strategies model was used on real low-stakes test data, the examinees classified as amotivated reported much lower test-taking effort than other examinees. However, examinees classified as amotivated were not very different than other examinees in terms of academic ability. This finding supports the notion that the second class in the mixed-strategies model is capturing amotivated examinees rather than low-ability examinees. Limitations of the mixed strategies modeling technique are discussed, as is the appropriateness of applying this technique in various testing contexts.