Bi-factor confirmatory factor models have been influential in research on cognitive abilities because they often better fit the data than correlated factors and higher-order models. They also instantiate a perspective that differs from that offered by other models. Motivated by previous work that hypothesized an inherent statistical bias of fit indices favoring the bi-factor model, we compared the fit of correlated factors, higher-order, and bi-factor models via Monte Carlo methods. When data were sampled from a true bi-factor structure, each of the approximate fit indices was more likely than not to identify the bi-factor solution as the best fitting. When samples were selected from a true multiple correlated factors structure, approximate fit indices were more likely overall to identify the correlated factors solution as the best fitting. In contrast, when samples were generated from a true higher-order structure, approximate fit indices tended to identify the bi-factor solution as best fitting. There was extensive overlap of fit values across the models regardless of true structure. Although one model may fit a given dataset best relative to the other models, each of the models tended to fit the data well in absolute terms. Given this variability, models must also be judged on substantive and conceptual grounds.

The Stability of Teacher Performance and Effectiveness: Implications for Policies Concerning Teacher Evaluation

The purpose of the current study was to compare the use of virtual discussion boards in various educational settings in the United States and Costa Rica. Participants included professors of education, in-service and pre-service teachers in the United States and Costa Rica where a survey was used that included demographic, knowledge, attitude, and behavioral questions regarding the use of virtual discussion boards. Results indicated that sixty-two percent of the participants used discussion boards in an educational setting. Instructors reported creating discussion board prompts that were constructivist in nature, and responses were frequently assessed for reflection, application, or collaboration. Findings show implications for educators in Costa Rica the United States due to the extensive rural landscape that perpetuates a need for alternative forms of communication and distance learning as well as to provide a comparison to how this technology is used in United States educational settings.