Comparisons of Four Methods for Estimating a Dynamic Factor Model

Four methods for estimating a dynamic factor model, the direct autoregressive factor score (DAFS) model, are evaluated and compared. The first method estimates the DAFS model using a Kalman filter algorithm based on its state space model representation. The second one employs the maximum likelihood estimation method based on the construction of a block-Toeplitz covariance matrix in the structural equation modeling framework. The third method is built in the Bayesian framework and implemented using Gibbs sampling. The fourth is the least squares method, which also employs the block-Toeplitz matrix. All 4 methods are implemented in currently available software. The simulation study shows that all 4 methods reach appropriate parameter estimates with comparable precision. Differences among the 4 estimation methods and related software are discussed.     

Prenatal cocaine exposure: a comparison of 2-year-old children in parental and nonparental care

Effects of prenatal cocaine exposure and parental versus nonparental care on outcome at 2 years of age were examined. The sample included 83 cocaine-exposed and 63 nonexposed children and their caregivers; 49 and 34 of the cocaine-exposed children experienced parental and nonparental care, respectively. Prenatal drug exposure was not related directly to children's outcome at 2 years of age. However, compared with cocaine-exposed children in parental care, those in nonparental care experienced a more optimal environment and performed better in several developmental domains at 2 years of age in spite of being at greater neonatal risk. Further analyses suggested that this protective effect of nonparental care was in part due to nonkin rather than kin care.     

Predicting who will major in a science discipline: Expectancy–value theory as part of an ecological model for studying academic communities

Research on factors that shape recruitment and retention in undergraduate science majors currently is highly fragmented and in need of an integrative research framework. Such a framework should incorporate analyses of the various levels of organization that characterize academic communities (i.e., the broad institutional level, the departmental level, and the student level), and should also provide ways to study the interactions occurring within and between these structural levels. We propose that academic communities are analogous to ecosystems, and that the research paradigms of modern community ecology can provide the necessary framework, as well as new and innovative approaches to a very complex area. This article also presents the results of a pilot study that demonstrates the promise of this approach at the student level. We administered a questionnaire based on expectancy-value theory to undergraduates enrolled in introductory biology courses. Itself an integrative approach, expectancy-value theory views achievement-related behavior as a joint function of the person's expectancy of success in the behavior and the subjective value placed on such success. Our results indicated: (a) significant gender differences in the underlying factor structures of expectations and values related to the discipline of biology, (b) expectancy-value factors significantly distinguished biology majors from nonmajors, and (c) expectancy-value factors significantly predicted students' intent to enroll in future biology courses. We explore the expectancy-value framework as an operationally integrative framework in our ecological model for studying academic communities, especially in the context of assessing the underrepresentation of women and minorities in the sciences. Future research directions as well as practical implications are also discussed.     

Sources of academic and self-regulatory efficacy beliefs of entering middle school students

The purpose of this study was to examine the influence of Bandura’s (1997) hypothesized sources of self-efficacy on the academic and self-regulatory efficacy beliefs of entering middle school students (N = 263) and to explore whether these sources differ as a function of gender, reading ability, and race/ethnicity. For the full sample, mastery experience, vicarious experience, social persuasions, and physiological state independently predicted academic and self-regulatory self-efficacy, with mastery experience proving the strongest predictor. Mastery experience and social persuasions predicted girls’ academic and self-regulatory self-efficacy, whereas mastery and vicarious experiences predicted these self-beliefs for boys. African American students’ mastery experiences and social persuasions predicted their academic self-efficacy. Mastery experience did not predict the self-efficacy beliefs of low-achieving students. Findings support and refine the theoretical tenets of Bandura’s social cognitive theory.     

Didactic and technical considerations when developing e-learning and CME

Several usability issues were encountered during the design of a blended e-learning program for a course in evidence-based medicine for general practice trainers. The program was developed in four steps. We focused in this article on step 2 and 3. Step 2 focused on which educational principles to apply, that is, which learning theories, instructional designs and other theories should influence the program. Step 3 focused on the design elements, namely whether to use hypermedia and/or multimedia, and what screen design and which font to use. This article presents the important issues in designing an e-course and provides an impression of the complexity of designing high quality e-learning in particular for continuing medical education (CME).     

Online vs. offline course evaluation revisited: testing the invariance of a course evaluation questionnaire using a multigroup confirmatory factor analysis framework

Educational Assessment, Evaluation and Accountability - Survey-based formats of assessing teaching quality in higher education are widely used and will likely continue to be used by higher...