First-Order Learning Models With the GDINA: Estimation With the EM Algorithm and Applications

In learning environments, understanding the longitudinal path of learning is one of the main goals. Cognitive diagnostic models (CDMs) for measurement combined with a transition model for mastery may be beneficial for providing fine-grained information about students’ knowledge profiles over time. An efficient algorithm to estimate model parameters would augment the practicality of this combination. In this study, the Expectation–Maximization (EM) algorithm is presented for the estimation of student learning trajectories with the GDINA (generalized deterministic inputs, noisy, “and” gate) and some of its submodels for the measurement component, and a first-order Markov model for learning transitions is implemented. A simulation study is conducted to investigate the efficiency of the algorithm in estimation accuracy of student and model parameters under several factors—sample size, number of attributes, number of time points in a test, and complexity of the measurement model. Attribute- and vector-level agreement rates as well as the root mean square error rates of the model parameters are investigated. In addition, the computer run times for converging are recorded. The result shows that for a majority of the conditions, the accuracy rates of the parameters are quite promising in conjunction with relatively short computation times. Only for the conditions with relatively low sample sizes and high numbers of attributes, the computation time increases with a reduction parameter recovery rate. An application using spatial reasoning data is given. Based on the Bayesian information criterion (BIC), the model fit analysis shows that the DINA (deterministic inputs, noisy, “and” gate) model is preferable to the GDINA with these data.     

Regulation of behaviour in pursuit of health goals

Abstract

Prediction of health related behaviours and the specification of cognitive processes which might guide development of effective interventions may be promoted by the identification of processes which mediate between intentions and health behaviour. The present commentary addresses theoretical developments concerning the role of cognitive and personality processes in volitional pursuit of health related goals and in the maintenance of behavioural change.     

Habitual Self‐Control: A Brief Measure of Persistent Goal Pursuit

Habitual self‐control is defined as a trait‐like personal resource factor that facilitates the enactment of difficult intentions. A 14‐item Habitual Self‐Control Questionnaire (HSCQ) was developed to assess this trait. Reliability, factorial validity, and criterion validity were assessed in five undergraduate student subsamples with an overall N of 2224. Internal consistency was .81 across the entire sample, and test–retest reliability was .83 over a one‐month interval. The HSCQ showed a theoretically meaningful pattern in terms of convergent and discriminant validity and criterion validity in predicting a variety of health behaviours that relate to self‐control, including exercise, dieting behaviour, binge eating and weight loss success. Further, the HSCQ contributed uniquely to the prediction of health behaviours beyond alternative self‐control scales. In a longitudinal part of the study, the HSCQ added to the prediction of action plan completion and satisfaction beyond motivation and moderated the relationship between motivation and enactment of action plans as theoretically expected. In sum, the results provided strong evidence for the reliability and validity of the HSCQ and highlighted some theoretically meaningful differences to already existing measures of self‐control. Theoretical implications are discussed. Copyright © 2012 John Wiley & Sons, Ltd.     

Axiomatising first-order temporal logic: Until and since over linear time

We present an axiomatisation for the first-order temporal logic with connectives Until and Since over the class of all linear flows of time. Completeness of the axiom system is proved.We also add a few axioms to find a sound and complete axiomatisation for the first order temporal logic of Until and Since over rational numbers time.The author would like to thank Dov Gabbay and Ian Hodkinson for helpful discussions on this material. The work was supported by the U.K. Science and Engineering Research Council under the Metatem project (GR/F/28526).Presented by Dov Gabbay     

师范生职业认同感的效能—价值双维核心模型的构建

以师范生职业认同感研究的"职业能力"和"职业价值"两大取向为基础,根据其单维评估的不足,将职业效能感和职业价值感指标联合,提出师范生职业认同感的效能—价值双维核心模型,并考察该模型在3所部属师范大学的1237名免费师范生中是否存在及其效用。研究表明:(1)模型能有效将免费师范生分组,其中低效能—低价值占31.69%、低效能—高价值占6.63%、高效能—低价值占40.01%、高效能—高价值仅占21.67%,克服了单维评估存在的高估或低估问题;(2)模型在职业认同结果(职业意志感、职业意愿与期望感)、学业满意度、总体生活满意度及未来担忧上的分组效应显著,同时拥有高职业效能感和高职业价值感的免费师范生具有最佳的职业认同感、学业满意度、总体生活满意度和最少的未来担忧。     

Combined reasoning by automated cooperation

Different reasoning systems have different strengths and weaknesses, and often it is useful to combine these systems to gain as much as possible from their strengths and retain as little as possible from their weaknesses. Of particular interest is the integration of first-order and higher-order techniques. First-order reasoning systems, on the one hand, have reached considerable strength in some niches, but in many areas of mathematics they still cannot reliably solve relatively simple problems, for example, when reasoning about sets, relations, or functions. Higher-order reasoning systems, on the other hand, can solve problems of this kind automatically. But the complexity inherent in their calculi prevents them from solving a whole range of problems. However, while many problems cannot be solved by any one system alone, they can be solved by a combination of these systems.We present a general agent-based methodology for integrating different reasoning systems. It provides a generic integration framework which facilitates the cooperation between diverse reasoners, but can also be refined to enable more efficient, specialist integrations. We empirically evaluate its usefulness, effectiveness and efficiency by case studies involving the integration of first-order and higher-order automated theorem provers, computer algebra systems, and model generators.     

Examining how aspects of vocational privilege relate to living a calling

The current study examined how aspects of vocational privilege directly – and indirectly via work meaning and career commitment – related to living a calling. With an economically diverse sample of 361 employed adults, both social class and work volition were found to moderately to strongly correlate with work meaning, career commitment, and living a calling. We used a structural equation model and found career commitment and work meaning to significantly predict living a calling and fully mediate the link between work volition and living a calling. Additionally, social class related to work meaning and career commitment via work volition. Findings suggest that the links between social class, work volition, and living a calling may be explained by individuals working in jobs they are committed to and that are meaningful, and that work volition may represent the gateway from social class to the experience of fulfilling work. Implications for practice are discussed.