Educational assessments tests are often constructed using testlets because of the flexibility to test various aspects of the cognitive activities and broad content sampling. However, the violation of the local item independence assumption is inevitable when tests are built using testlet items. In this study, simulations are conducted to evaluate the performance of item response theory models and testlet response theory models for both the dichotomous and polytomous items in the context of equating tests composed of testlets. We also examine (...) the impact of testlet effect, length of testlet items, and sample size on estimating item and person parameters. The results show that more accurate performance of testlet response theory models over item response theory models was consistently observed across the studies, which supports the benefits of using the testlet response theory models in equating for tests composed of testlets. Further, results of the study indicate that when sample size is large, item response theory models performed similarly to testlet response theory models across all studies. (shrink)

Numerous studies have shed some light on the importance of associated factors of collaborative attitudes. However, most previous studies aimed to explore the influence of these factors in isolation. With the strategy of data-driven decision making, the current study applied two data mining methods to elucidate the most significant factors of students' attitudes toward collaboration and group students to draw a concise model, which is beneficial for educators to focus on key factors and make effective interventions at a lower cost. (...) Structural equation model trees and structural equation model forests were applied to the Program for International Student Assessment 2015 dataset. By establishing the most important predictors and the splitting rules, these methods constructed multigroup common factor models of collaborative attitudes. The SEM trees showed that home educational resources, home possessions, mother's education, and gender were the most important predictors among the demographic variables, drawing a 5-group model. Among all the predictors, achievement motivation and sense of belonging at school were the most important, drawing a 6-group model. The SEM forest findings proved the relative importance of these variables. This paper discusses various interpretations of these results and their implications for educators to formulate corresponding interventions. Methodologically, this research provides a data mining approach to discover important information from large-scale educational data, which might be a complementary approach to enhance data-driven decision making in education. (shrink)

Emotion regulation plays a vital role in individuals’ well-being and successful functioning. In this study, we attempted to develop a computerized adaptive testing to efficiently evaluate ER, namely the CAT-ER. The initial CAT-ER item bank comprised 154 items from six commonly used ER scales, which were completed by 887 participants recruited in China. We conducted unidimensionality testing, item response theory model comparison and selection, and IRT item analysis including local independence, item fit, differential item functioning, and item discrimination. Sixty-three items (...) with good psychometric properties were retained in the final CAT-ER. Then, two CAT simulation studies were implemented to assess the CAT-ER, which revealed that the CAT-ER developed in this study performed reasonably well, considering that it greatly lessened the test items and time without losing measurement accuracy. (shrink)