Establishing a Center to Support Faculty Research

This article describes the establishment in fall 2002 of a School of Education Research Center designed to support faculty in increasing productivity and quality in research. Details are provided about center goals, services, staffing, space, resources, and logistics during the first year of operation. In addition, data are shared about faculty usage of the Center, the level of faculty satisfaction with center services in the first year, and initial increases in faculty productivity. The article concludes with plans for continued data collection to monitor the impact of the Center, a discussion of lessons learned at this point in the Center's development, and possibilities for the evolution of the Center. All authors are at the University of Colorado, Denver. Laura Goodwin, Ph.D., University of Colorado at Boulder, is Interim Associate Vice Chancellor for Faculty Affairs and continues to serve as a Faculty Research Associate. Elizabeth Kozleski, Ed.D., University of Northern Colorado, is the Associate Dean for Research in the School of Education. Lynn Rhodes, Ed.D., Indiana University, is the Dean of the School of Education. Rodney Muth, Ph.D., Claremont Graduate School, is a professor of Administrative Leadership and Policy Studies in the school and chaired the Research Center Advisory Board. Kim Kennedy White, M.A., University of Oregon, was the original School of Education Research Center Coordinator and was responsible for collecting most of the data included in this study.     

Models and Strategies for Factor Mixture Analysis: An Example Concerning the Structure Underlying Psychological Disorders

The factor mixture model (FMM) uses a hybrid of both categorical and continuous latent variables. The FMM is a good model for the underlying structure of psychopathology because the use of both categorical and continuous latent variables allows the structure to be simultaneously categorical and dimensional. This is useful because both diagnostic class membership and the range of severity within and across diagnostic classes can be modeled concurrently. Although the conceptualization of the FMM has been explained in the literature, the use of the FMM is still not prevalent. One reason is that there is little research about how such models should be applied in practice and, once a well-fitting model is obtained, how it should be interpreted. In this article, the FMM is explored by studying a real data example on conduct disorder. By exploring this example, this article aims to explain the different formulations of the FMM, the various steps in building a FMM, and how to decide between an FMM and alternative models.     

Number of Subjects and Time Points Needed for Multilevel Time-Series Analysis: A Simulation Study of Dynamic Structural Equation Modeling

Dynamic structural equation modeling (DSEM) is a novel, intensive longitudinal data (ILD) analysis framework. DSEM models intraindividual changes over time on Level 1 and allows the parameters of these processes to vary across individuals on Level 2 using random effects. DSEM merges time series, structural equation, multilevel, and time-varying effects models. Despite the well-known properties of these analysis areas by themselves, it is unclear how their sample size requirements and recommendations transfer to the DSEM framework. This article presents the results of a simulation study that examines the estimation quality of univariate 2-level autoregressive models of order 1, AR(1), using Bayesian analysis in Mplus Version 8. Three features are varied in the simulations: complexity of the model, number of subjects, and number of time points per subject. Samples with many subjects and few time points are shown to perform substantially better than samples with few subjects and many time points.     

Three AMIGO<Superscript>3</Superscript>s: Using “Anchored modular inquiry” to help prepare future teachers

We discuss three case studies associated with Vanderbilt’s PT3 (Preparing Tomorrow’s Teachers to Use Technology) grant. The studies explore some initial effects of attempts to enhance the education of preservice teachers in three areas: (a) How People Learn, (b) Mathematics, and (c) Adolescent Psychology. The case studies to be described each build on Vanderbilt’s AMIGO³ project, which involves technology architecture for flexible modular design that was developed to be consistent with principles of How People Learn. Three different research teams used the AMIGO³ architecture and rationale to design, implement, and study their own courses. All teams agreed on some basic guidelines, but then proceeded independently of one another. The purpose of this report is to compare similarities and differences in the experiences of the teams. The PT3 group: Primary Investigator—John Bransford; Project Director—Bob Plants; How People Learn Course—John Bransford, Nancy Vye, Kay Burgess, and Sean Brophy; Adolescent Psychology—Helen Bateman, and Christopher J. Bateman; Mathematics—Paul Cobb, Chrystal Dean, and Lori Tyler; Development Team—Tim Altman, Jason Adair, Hank Clark, Bill Corbin, John Harwood, Elliott Mitchell, and Carolyn Stalcup. Vanderbilt PT3 Partners: AACTE, Apple Computers, Bankstreet College, Concord Consortium, Little Planet Software, Middle Tennessee University, University of Illinois-Chicago, University of Minnesota, and University of Vermont. Research presented in this article was supported by grants: The Department of Education Preparing tomorrow’s teachers to use technology (PT3) Catalyst grant, #P342A990348, The National Science Foundation VaNTH Bioengineering grant, #EEC 9876363, and the Atlantic Philanthropic Association K-12 Learning Consortium (no assigned grant number).     

Power,involvement, and organizational effectiveness in higher education

Focusing on theoretical and empirical relations among power variables, faculty job involvement, and college organizational effectiveness, this study found that power behaviors variously affect one's sense of job involvement and overall effectiveness of one's college. In particular, influence was found to be positively related to involvement and to effectiveness, while coercion was found to be negatively related to effectiveness but not related to involvement. These findings suggest that empirical integration of divergent normative theories is useful for understanding how academic administrators might behave to improve the performance of their institutions and provide support for earlier studies which have used the empirical model used here.     

The incidence of infant physical abuse in Alaska

OBJECTIVES: To determine the incidence of and risk factors associated with infant (< 1 year of age) physical abuse in Alaska. METHODS: A population-based retrospective cohort study for the 1994-2000 resident birth cohort was conducted by linking data from birth certificates, Child Protective Services, a statewide hospital-based trauma registry, hospital discharge data, and the Alaska Infant Mortality Review (including death certificates). The main outcome measures were the incidences of overall physical abuse and abuse resulting in hospitalization or death. A case of child abuse was defined as an instance of substantiated physical abuse to an infant identified in the Child Protective Services database or an infant death with homicide identified on the death certificate as the manner of death. RESULTS: During the 7-year study period, there were 70,842 births and 325 cases of physical abuse including 72 that led to hospitalization (n = 58), death (n = 4), or both (n = 10); respective incidences for all abuse and abuse leading to hospitalization or death were 4.6 and 1.0 per 1000 live births. Following multivariate analyses, the risk factors with the highest population attributable risks were maternal or paternal education < or = 12 years, unmarried mother, and maternal prenatal substance use. To determine if the study methodology was likely to have missed cases of severe abuse, we examined information for all 216 infants hospitalized for trauma during the study period who did not have identification of abuse in one of the study databases; of these, at least 39 had injuries inconsistent with the reported mechanism (a long bone or skull fracture that reportedly resulted from a fall of less than 3 feet or from a caretaker's arms or for which the caretaker denied a history of trauma). Conclusions: Alaska has one of the highest documented infant physical abuse incidences reported in the literature and abuse is associated with potentially modifiable-primarily social-risk factors. Despite this high incidence, substantial under-reporting of hospitalized cases likely occurs.     

Text-Comprehension Strategies Based on Outlines

Prior to studying an instructional text, college students were given either a topically relevant outline or a topically irrelevant (control) outline and asked to generate propositions about the topics by drawing upon their existing knowledge. The results indicate that comprehension was highest among those students who activated relevant prior knowledge before text study, and who were again provided with an outline of that knowledge during testing. The measure of comprehension used here was total meaningful recall: It included text propositions plus valid elaborations based on the interaction of text information and students’ existing knowledge. The results of conceptual clustering analyses suggest that organization was one of the mechanisms by which topical outlines increased meaningful recall. Additional analyses conducted only on the elaborations indicate that students produced more of them during long-term (six week) recall than during immediate recall.     

Causal Effects in Mediation Modeling: An Introduction With Applications to Latent Variables

Causal inference in mediation analysis offers counterfactually based causal definitions of direct and indirect effects, drawing on research by Robins, Greenland, Pearl, VanderWeele, Vansteelandt, Imai, and others. This type of mediation effect estimation is little known and seldom used among analysts using structural equation modeling (SEM). The aim of this article is to describe the new analysis opportunities in a way that is accessible to SEM analysts and show examples of how to perform the analyses. An application is presented with an extension to a latent mediator measured with multiple indicators.