Many educational and psychological assessments focus on multidimensional latent traits that often have a hierarchical structure to provide both overall-level information and fine-grained diagnostic information. A test will usually have either separate time limits for each subtest or an overall time limit for administrative convenience and test fairness. In order to complete the items within the allocated time, examinees frequently adopt different test-taking behaviours during the test, such as solution behaviour and rapid guessing behaviour. In this paper we propose a new mixture model for responses and response times with a hierarchical ability structure, which incorporates auxiliary information from other subtests and the correlation structure of the abilities to detect rapid guessing behaviour. A Markov chain Monte Carlo method is proposed for model estimation. Simulation studies reveal that all model parameters could be recovered well, and the parameter estimates had smaller absolute bias and mean squared error than the mixture unidimensional item response theory (UIRT) model. Moreover, the true positive rate of detecting rapid guessing behaviour is also higher than when using the mixture UIRT model separately for each subscale, whereas the false detection rate is much lower than the mixture UIRT model. The deviance information criterion and the logarithm of the pseudo-marginal likelihood are employed to evaluate the model fit. Finally, a real data analysis is presented to demonstrate the practical value of the proposed model. 相似文献
The four-parameter logistic model (4PLM) has recently attracted much interest in various applications. Motivated by recent studies that re-express the four-parameter model as a mixture model with two levels of latent variables, this paper develops a new expectation–maximization (EM) algorithm for marginalized maximum a posteriori estimation of the 4PLM parameters. The mixture modelling framework of the 4PLM not only makes the proposed EM algorithm easier to implement in practice, but also provides a natural connection with popular cognitive diagnosis models. Simulation studies were conducted to show the good performance of the proposed estimation method and to investigate the impact of the additional upper asymptote parameter on the estimation of other parameters. Moreover, a real data set was analysed using the 4PLM to show its improved performance over the three-parameter logistic model. 相似文献
African Americans, especially African American women, remain one of the most underrepresented groups in technology-based degrees and careers. However, little is known about whether gender differences permeate African American adolescents’ engagement in technology in earlier development, such as in middle and high school (ages 12–18). Drawing on an ecological and intersectional framework, we examined if African American male and female adolescents differed in technological engagement and what contextual factors affected their engagement. We hypothesized that parental encouragement would be associated with greater technological confidence in adolescents, which would be linked to more experiences with and interests in technology. Further, we investigated if these associations would vary by adolescents’ and parents’ gender. Survey data from 1041 African American parent-adolescent dyads highlighted that adolescents had less experience and interest with technical activities than with creative activities, especially among female adolescents. More parents encouraged adolescent sons but limited daughters to use technology, yet female adolescents reported greater technological confidence. Moderated mediation analyses revealed that adolescents’ technological confidence mediated the positive association between parental encouragement and adolescents’ technological engagement across all parent-adolescent dyads, but with some nuances. Our findings suggest that prospective gender studies and educational programs should consider the influences of parenting and gender on promoting African American adolescents’ technological involvement and confidence.
This paper argues for a clearer conceptualization of media stimuli in experimental research and identifies 3 issues impeding our understanding of message processing: (a) assumptions bolstered by manipulation checks about homogeneity of response to media stimuli, (b) conflation of 2 different classes of variables—media attributes and psychological states, and (c) discrepancies between the conceptual model and operational‐level hypotheses used to test research questions. To provide a more comprehensive framework for investigating media effects in experimental research, we argue for a clearer conceptual separation between message attributes and user perceptions and apply a mediation model of information processing to overcome the limitations of conventional approaches. Subjected to 2 empirical tests involving the assessment of Web‐based media, the model finds an increase in explained variance in each instance.相似文献
Human vision supports social perception by efficiently detecting agents and extracting rich information about their actions, goals, and intentions. Here, we explore the cognitive architecture of perceived animacy by constructing Bayesian models that integrate domain‐specific hypotheses of social agency with domain‐general cognitive constraints on sensory, memory, and attentional processing. Our model posits that perceived animacy combines a bottom–up, feature‐based, parallel search for goal‐directed movements with a top–down selection process for intent inference. The interaction of these architecturally distinct processes makes perceived animacy fast, flexible, and yet cognitively efficient. In the context of chasing, in which a predator (the “wolf”) pursues a prey (the “sheep”), our model addresses the computational challenge of identifying target agents among varying numbers of distractor objects, despite a quadratic increase in the number of possible interactions as more objects appear in a scene. By comparing modeling results with human psychophysics in several studies, we show that the effectiveness and efficiency of human perceived animacy can be explained by a Bayesian ideal observer model with realistic cognitive constraints. These results provide an understanding of perceived animacy at the algorithmic level—how it is achieved by cognitive mechanisms such as attention and working memory, and how it can be integrated with higher‐level reasoning about social agency. 相似文献