Multidimensional adaptive testing (MAT) procedures are proposed for the measurement of several latent traits by a single examination. Bayesian latent trait estimation and adaptive item selection are derived. Simulations were conducted to compare the measurement efficiency of MAT with those of unidimensional adaptive testing and random administration. The results showed that the higher the correlation between latent traits, the more latent traits there were, and the more scoring levels there were in the items, the more efficient MAT was than the other two procedures. For tests containing multidimensional items, only MAT is applicable, whereas unidimensional adaptive testing is not. Issues in implementing MAT are discussed.

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Rater centrality, in which raters overuse middle scores for rating, is a common rater error which can affect test scores and subsequent decisions. Past studies on rater errors have focused on rater severity and inconsistency, neglecting rater centrality. This study proposes a new model within the hierarchical rater model framework to explicitly specify and directly estimate rater centrality in addition to rater severity and inconsistency. Simulations were conducted using the freeware JAGS to evaluate the parameter recovery of the new model and the consequences of ignoring rater centrality. The results revealed that the model had good parameter recovery with small bias, low root mean square errors, and high test score reliability, especially when a fully crossed linking design was used. Ignoring centrality yielded poor item difficulty estimates, person ability estimates, rater errors estimates, and underestimated reliability. We also showcase how the new model can be used, using an empirical example involving English essays in the Advanced Placement exam.

Attending cram school has long been a trend in ethnic Chinese culture areas, including Taiwan. Despite the fact that school reform policies have been implemented in Taiwan, cram schools have continued to prosper. Therefore, in this educational culture, how to achieve a good educational effect is also a topic worthy of discussion. However, whether students really engage in those tutoring programs provided by cram schools has seldom been studied. To address this gap, this study explored how parents’ hovering attitude toward life and coursework influences their children’s engagement in cram schools. This study targeted those students who attend English cram schools to test the correlates between two types of helicopter parenting, tutoring engagement and continued attendance at cram schools. A total of 320 questionnaires were sent out, and 300 were returned, giving an overall response rate of 93.75%. Excluding seven incomplete or invalid questionnaires, 293 valid questionnaires were received. The results of this study show that hovering behavior awareness is negatively related to cram school engagement, whereas cram school engagement is positively related to the intention to continue attending cram school. Moreover, the results imply that parents should alleviate their helicoptering behavior to enhance their children’s engagement in cram school tutoring programs.

The multidimensional mixture data structure exists in many test (or inventory) conditions. Heterogeneity also relatively exists in populations. Still, some researchers are interested in deciding to which subpopulation a participant belongs according to the participant’s factor pattern. Thus, in this study, we proposed three analysis procedures based on the factor mixture model to analyze data in the multidimensional mixture context. Simulations were manipulated with different levels of factor numbers, factor correlations, numbers of latent classes, and class separation. Issues with regard to model selection were discussed at first. The results showed that in the two-class situations the procedures of “factor structure first then class number” (Procedure 1) and “factor structure and class number considered simultaneously” (Procedure 3) performed better than the “class number first then factor structure” (Procedure 2) and yielded precise parameter estimation and classification accuracy. It would be appropriate to choose Procedures 1 and 3 when strong measurement invariance is assumed while using an information criterion, but Procedure 1 saved more time than Procedure 3. In the three-class situations, the performance of all three procedures was limited. Implementations and suggestions have been addressed in this research.

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Previous studies have focused on individuals learning from observing a model to be able to produce the modeled behavior. However, there is a lack of studies emphasizing the perspective of being observed to understand the role of perceived value and stress when teachers act as a teaching model. To address this gap, the present study explored the correlates between teachers’ teaching beliefs, perceived value, psychosocial stress, and continuous intention to be the observed teaching model in classroom observations. Data of 349 respondents were usefully collected, and confirmatory factor analysis with structural equation modeling was performed. Results showed that teachers’ constructivist belief in teaching was positively related to perceived value of being observed and getting feedback, but was negatively related to psychosocial stress. Perceived value was positively related to continuous intention to be observed in future classroom observations, but perceived psychosocial stress was not significantly related to continuous intention. The results of this study can be applied to encourage those who are resistant to presenting their teaching experience in classroom observations.

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