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The purpose of this study was to identify patterns of Taiwanese students' perceptions of good citizenship in terms of citizenship behaviours rooted in Western democracy and character and moral (CM) oriented citizenship. Data from Taiwanese eighth graders participating in the 2016 International Civic and Citizenship Education Study (ICCS) were examined. Citizenship behaviours were measured by items from the ICCS student questionnaire and the ICCS Asian Regional Module. The results showed that students who emphasised all but CM oriented citizenship had the weakest attitude towards the personal morality of politicians. Students who endorsed all citizenship behaviours had the highest levels of expected civic engagement. The findings suggest that the development of the good citizenship perceived by Taiwanese students may be enhanced by multiple sources in addition to citizenship education.

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.

This study aimed to develop an illustration-based developmental motor screening questionnaire (DMSQi) for young children and examined its psychometric properties. 463 young children and their caregivers were collected and received the DMSQi assessment. DMSQi is made up of two domains. The gross motor (GM) domain includes body coordination and stability/mobility subdomains. The fine motor (FM) domain includes visual motor integration and hand grasp/manipulation subdomains. The internal consistency (Cronbach's a) and test-retest reliabilities (ICCs) of DMSQi were 0.88-0.98 and 0.85-0.95, respectively. For concurrent validity, the GM and FM domains of DMSQi were highly correlated with the corresponding domains of Peabody Developmental Motor Scale, second edition (r = 0.85-0.95). DMSQi had good discriminant validity for age (p < 0.001). Most items (96%) were fitted and the item difficulty was from -7 to 5 scaled by Rasch analysis. DMSQi is easy, quick, and culture-specific. It has good reliability, validity, and item fit for assessing the motor development of young children.

Patients with schizophrenia tend to have deficits in emotion recognition (ER) that affect their social function. However, the commonly-used ER measures appear incomprehensive, unreliable and invalid, making it difficult to comprehensively evaluate ER. The purposes of this study were to develop the Computerized Emotion Recognition Video Test (CERVT) evaluating ER ability in patients with schizophrenia. This study was divided into two phases. First, we selected candidate CERVT items/videos of 8 basic emotion domains from a published database. Second, we validated the selected CERVT items using Rasch analysis. Finally, the 269 patients and 177 healthy adults were recruited to ensure the participants had diverse abilities. After the removal of 21 misfit (infit or outfit mean square > 1.4) items and adjustment of the item difficulties of the 26 items with severe differential item functioning, the remaining 217 items were finalized as the CERVT items. All the CERVT items showed good model fits with small eigenvalues (≤ 2) based on the residual-based principal components analysis for each domain, supporting the unidimensionality of these items. The 8 domains of the CERVT had good to excellent reliabilities (average Rasch reliabilities = 0.84–0.93). The CERVT contains items of the 8 basic emotions with individualized scores. Moreover, the CERVT showed acceptable reliability and validity, and the scores were not affected by examinees' gender. Thus, the CERVT has the potential to provide a comprehensive, reliable, valid, and gender-unbiased assessment of ER for patients with schizophrenia. [ABSTRACT FROM AUTHOR]

Energy literacy is multidimensional, comprising broad content knowledge as well as affect and behavior. Our previous study has defined four core dimensions for the assessment framework, including energy concepts, reasoning on energy issues, low-carbon lifestyle, and civic responsibility for a sustainable society. The present study compiled a series of contextualized question items into a computer-based test (CBT) platform to examine students' energy literacy. Each test unit included a scenario, presented via multimedia materials (e.g., text, image, short video, and animation), that pertained to real-life situations. Various types of questions were employed (e.g., multiple true-false, multiple choice, and short-answer) that required students to construct responses and make judgments. A total of 1,711 secondary school students participated in this survey. The results indicate that the energy literacy level of Taiwanese secondary students is discouragingly low and inter-correlations between the dimensions of energy literacy reveal that energy knowledge and behavior are more closely correlated than affect and behavior. In addition, the scores on the attitudinal items were slightly higher for junior than senior students and the students in the southern region scored higher on energy literacy than those in other regions. These findings provide evidence for the future development of energy-related educational curricula and materials that can improve students' energy literacy and engagement in energy-related decisions.

This study explored cultural influences on English language teachers' judgments of English metaphors created by Taiwanese learners of English. Based on a mixed-methods approach, it delved into the rating severity and implicit evaluation criteria of two cultural groups of teachers: Taiwanese and Americans. Ten Taiwanese teachers and 10 American teachers evaluated 120 novel metaphoric expressions using the Consensual Assessment Technique (Amabile, 1996). "Creativity in context: Update to the social psychology of creativity." They further filled out a creativity evaluation survey, which was designed to bring to light what qualities within the metaphors influenced their judgments of metaphoric creativity. With the teachers' ratings being analyzed by means of many-facet Rasch measurement, this study first indicated that the American teachers were more severe raters than the Taiwanese teachers, but no significant difference was found between them. Analysis of the evaluation survey further demonstrated that both cultural groups shared largely similar evaluation criteria; yet, two contrasts emerged between them. Specifically, the American teachers seemed to favor metaphors that expressed the creator's thoughts; by contrast, the Taiwanese teachers preferred metaphors that relied on readers' imagination to work out the meanings. These findings shed light on implications for teaching creativity in English L2 classrooms and assessing learners' creative language artifacts in an English L2 context.

A five-stage prediction-observation-explanation inquiry-based learning (FPOEIL) model was developed to improve students' scientific learning performance. In order to intensify the science learning effect, the repertory grid technology-assisted learning (RGTL) approach and the collaborative learning (CL) approach were utilized. A quasi-experimental design study was conducted to examine whether the students who used the FPOEIL model only had better learning performances than those who used FPOEIL with RGTL or CL. This study adopted purposive sampling, selecting 123 fourth grade students. The experimental process was conducted during five weeks. It was found that the FPOEIL model improved the students' learning performance. Moreover, the low prior knowledge students who learned science using FPOEIL with RGTL or CL had better learning performances than those who learned using the FPOEIL model only, and the effectiveness showed no significant differences between the low prior knowledge students and the high prior knowledge students. Using the FPOEIL model, the positive effects were intensified in the continuous inquiry-based learning activities and feedback-correction process for the students learning science. The RGTL approach helped the students find, remember, and comprehend scientific knowledge. In the CL process, the students spent more time discussing how to integrate clues to answer the science question.

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. [ABSTRACT FROM AUTHOR]

Many latent traits in the human sciences have a hierarchical structure. This study aimed to develop a new class of higher order item response theory models for hierarchical latent traits that are flexible in accommodating both dichotomous and polytomous items, to estimate both item and person parameters jointly, to allow users to specify customized item response functions, and to go beyond two orders of latent traits and the linear relationship between latent traits. Parameters of the new class of models can be estimated using the Bayesian approach with Markov chain Monte Carlo methods. Through a series of simulations, the authors demonstrated that the parameters in the new class of models can be well recovered with the computer software WinBUGS, and the joint estimation approach was more efficient than multistaged or consecutive approaches. Two empirical examples of achievement and personality assessments were given to demonstrate applications and implications of the new models.

In the human sciences, a common assumption is that latent traits have a hierarchical structure. Higher order item response theory models have been developed to account for this hierarchy. In this study, computerized adaptive testing (CAT) algorithms based on these kinds of models were implemented, and their performance under a variety of situations was examined using simulations. The results showed that the CAT algorithms were very effective. The progressive method for item selection, the Sympson and Hetter method with online and freeze procedure for item exposure control, and the multinomial model for content balancing can simultaneously maintain good measurement precision, item exposure control, content balance, test security, and pool usage. (Contains 3 tables and 2 figures.)

Product assessment is widely applied in creative studies, typically as an important dependent measure. Within this context, this study had 2 purposes. First, the focus of this research was on methods for investigating possible rater effects, an issue that has not received a great deal of attention in past creativity studies. Second, the substantive question of whether restrictions on materials used and differences in instructions provided would influence outcomes on measures of creativity was considered. The many-facet Rasch model was used to investigate possible sources of rater bias, including the leniency/severity effect, central tendency effect, halo effect and randomness effect. No indications were found that these potential sources of bias strongly influenced the ratings. The result indicated that the examinees could be reliably differentiated in terms of their performance. Analysis of rater-criterion interactions depicted rater behavior more clearly and, it is suggested, can be of use as a tool for rater training in future studies. In terms of the substantive questions posed, 2 × 2 experimental instructions were manipulated and it was found that different instructions did not affect creative performance. The implications of these findings are discussed.

In traditional test models, test items are independent, and test-takers slowly and thoughtfully respond to each test item. However, some test items have a common stimulus (dependent test items in a testlet), and sometimes test-takers lack motivation, knowledge, or time (speededness), so they perform rapid guessing (RG). Ignoring the dependence in responses to testlet items can negatively bias standard errors of measurement, and ignoring RG by fitting a simpler item response theory (IRT) model can bias the results. Because computer-based testing captures response times on testlet responses, we propose a mixture testlet IRT model with item responses and response time to model RG behaviors in computer-based testlet items. Two simulation studies with Markov chain Monte Carlo estimation using the JAGS program showed (a) good recovery of the item and person parameters in this new model and (b) the harmful consequences of ignoring RG (biased parameter estimates: overestimated item difficulties, underestimated time intensities, underestimated respondent latent speed parameters, and overestimated precision of respondent latent estimates). The application of IRT models with and without RG to data from a computer-based language test showed parameter differences resembling those in the simulations. [ABSTRACT FROM AUTHOR]

A conventional way to analyze item responses in multiple tests is to apply unidimensional item response models separately, one test at a time. This unidimensional approach, which ignores the correlations between latent traits, yields imprecise measures when tests are short. To resolve this problem, one can use multidimensional item response models that use correlations between latent traits to improve measurement precision of individual latent traits. The improvements are demonstrated using 2 empirical examples. It appears that the multidimensional approach improves measurement precision substantially, especially when tests are short and the number of tests is large. To achieve the same measurement precision, the multidimensional approach needs less than half of the comparable items required for the unidimensional approach.

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.

This study explored cultural influences on English language teachers' judgments of English metaphors created by Taiwanese learners of English. Based on a mixed‐methods approach, it delved into the rating severity and implicit evaluation criteria of two cultural groups of teachers: Taiwanese and Americans. Ten Taiwanese teachers and 10 American teachers evaluated 120 novel metaphoric expressions using the Consensual Assessment Technique (Amabile, 1996). Creativity in context: Update to the social psychology of creativity. They further filled out a creativity evaluation survey, which was designed to bring to light what qualities within the metaphors influenced their judgments of metaphoric creativity. With the teachers' ratings being analyzed by means of many‐facet Rasch measurement, this study first indicated that the American teachers were more severe raters than the Taiwanese teachers, but no significant difference was found between them. Analysis of the evaluation survey further demonstrated that both cultural groups shared largely similar evaluation criteria; yet, two contrasts emerged between them. Specifically, the American teachers seemed to favor metaphors that expressed the creator's thoughts; by contrast, the Taiwanese teachers preferred metaphors that relied on readers' imagination to work out the meanings. These findings shed light on implications for teaching creativity in English L2 classrooms and assessing learners' creative language artifacts in an English L2 context. [ABSTRACT FROM AUTHOR]