The Caring Teacher: A Multiple Case Study That Looks at What Teachers Do and Believe about Their Work With At-Risk Students

Caring teachers have been identified as a critical component of successful interventions with at-risk students, however just what constitutes a caring teacher is less well understood. Specifically, what are the behaviors, characteristics, and beliefs of caring teachers, and how are they impacted by the contexts within which they work? The purpose of this multiple case study was to understand more about caring teachers who work with at-risk students in secondary schools located in a Midwestern city and thereby to add complexity to the literature. Two middle school teachers and two high school teachers were recruited to participate. They were observed on multiple occasions and interviewed twice. The data from these observations and interviews were initially analyzed case by case; the cross case analysis based on the results from the individual case resulted in 6 themes that were present across the four cases. The following themes were identified: the role of relationships, perspective on at-risk students, providing opportunities for students to develop a positive sense of themselves, the value of a positive classroom experience for both students and teacher, negotiating power, and flexibility. Implications of this research for psychologists, educators, and policy makers, as well as future research are also discussed.

Evaluating Measurement Invariance with Censored Ordinal Data: A Monte Carlo Comparison of Alternative Model Estimators and Scales of Measurement

Evaluations of measurement invariance provide essential construct validity evidence. However, the quality of such evidence is partly dependent upon the validity of the resulting statistical conclusions. The presence of Type I or Type II errors can render measurement invariance conclusions meaningless. The purpose of this study was to determine the effects of categorization and censoring on the behavior of the chi-square/likelihood ratio test statistic and two alternative fit indices (CFI and RMSEA) under the context of evaluating measurement invariance. Monte Carlo simulation was used to examine Type I error and power rates for the (a) overall test statistic/fit indices, and (b) change in test statistic/fit indices. Data were generated according to a multiple-group single-factor CFA model across 40 conditions that varied by sample size, strength of item factor loadings, and categorization thresholds. Seven different combinations of model estimators (ML, Yuan-Bentler scaled ML, and WLSMV) and specified measurement scales (continuous, censored, and categorical) were used to analyze each of the simulation conditions. As hypothesized, non-normality increased Type I error rates for the continuous scale of measurement and did not affect error rates for the categorical scale of measurement. Maximum likelihood estimation combined with a categorical scale of measurement resulted in more correct statistical conclusions than the other analysis combinations. For the continuous and censored scales of measurement, the Yuan-Bentler scaled ML resulted in more correct conclusions than normal-theory ML. The censored measurement scale did not offer any advantages over the continuous measurement scale. Comparing across fit statistics and indices, the chi-square-based test statistics were preferred over the alternative fit indices, and ΔRMSEA was preferred over ΔCFI. Results from this study should be used to inform the modeling decisions of applied researchers. However, no single analysis combination can be recommended for all situations. Therefore, it is essential that researchers consider the context and purpose of their analyses.

Showing that Early Childhood Education Works: Lessons from Italy, China, and the USA

Lessons from around the world; What does it matter about early childhood education? Why the controversy about public support for early childhood education? What process or system should be used to determine what works in early education? Can the same process be used to improve services? What is the role of government? Alternatives: 1. Consumers should determine… (What happens when private choices drive the market for early childhood services?) Observed quality of care in four Midwestern states; Parent data: “All things considered, how would you grade the quality of the care your child is receiving from his/her current caregiver?” Role of government What is a Quality Rating System? Ten states have implemented statewide systems (e.g. Colorado, Kentucky, Oklahoma, North Carolina) Findings 2. Objective science should determine… Firm findings from empirical research 3. Something else is needed: Some differences between Italian and American models. Teacher action research (and documentation) from a Reggio-inspired preschool in South Korea by Misuk Kim. Teacher Action Research at the Ruth Staples CDL. Can we now answer our opening questions? What process or system should be used to determine what is best for young children? Can the same process be used to improve the quality of services? Conclusions: The free market does not work well to determine quality in early education and care; Licensing, accreditation, and quality rating systems can help improve the market; Empirical research is useful for measuring what works; Teacher action research (reflective practice) is necessary for fostering continuous quality improvement. The tower of quality.