Institutional arrangements for evaluation

Summary Evaluations should be independent in terms of being able to arrive at impartial conclusions. They must be seen as being credible if they are to fulfil this function. Their impartiality is derived from using appropriate scientific methodology and by being protected from political interference. Within the government, evaluation offices should be lodged in independent agencies located close to decision makers, but not in the same office as the programme being evaluated. Scientific methods that protect against various forms of bias should be derived with assistance from the professional evaluation community. Original language: English Ernest R. House (United States of America) Professor at the School of Education, University of Colorado, Boulder. His interests are in evaluation and policy. He has been a visiting scholar at UCLA, Harvard and New Mexico, as well as at universities in Australia, Austria, Spain, Sweden and the United Kingdom. Recent publications include;Professional evaluation (1993), Schools for sale (1998) andValues in evaluation and social research (with K. Howe). He has been a recipient of the Lasswell Prize (1989) for the article contributing most to the theory and practice of the policy sciences and of the Lazarsfeld Award (1990) for Evaluation and Theory, presented by the American Evaluation Association.     

Examining Effects of Poverty,Maternal Depression,and Children’s Self-Regulation Abilities on the Development of Language and Cognition in Early Childhood: An Early Head Start Perspective

Early childhood poverty is a prevalent social issue, both in the United States and in the wider international community. It has been well established that factors associated with poverty, including familial income and parental education level, can negatively affect children’s language and cognitive development, which can result in academic achievement deficits that compound across the lifespan. Additional environmental factors, specifically maternal and children’s own social–emotional development, have also been shown to impact these sensitive early childhood developmental processes. Although individual components that relate to language and cognitive development in young children have been identified, additional examination of potential associative relationships between these components is warranted. Therefore, this study explored socio-economical, health, and developmental relationships between 122 caregiver–child dyads enrolled in an Early Head Start Program where children were 1–36 months old. Results indicated strong bidirectional correlations between children’s cognitive and language development. Multiple linear regression path analysis indicated that children’s cognition and social–emotional wellbeing have a significant direct effect on their language development. Additionally, language and fine motor development were found to have a significant direct effect and social–emotional wellbeing mediated an indirect effect through language on children’s cognitive development. In light of socioeconomic and sociocultural challenges, the importance of nurturing children’s social–emotional development in relation to language and cognitive development is discussed.     

Confirmatory factor analysis of the Child Abuse Potential Inventory: results based on a sample of Chinese mothers in Hong Kong

OBJECTIVES: To evaluate whether or not the original six-factor structure of the Child Abuse Potential (CAP) Inventory suggested by [Milner, J.S. (1986). The Child Abuse Potential Inventory: Manual (2nd ed.). DeKalb, IL: Psytec. Inc.] can be confirmed with data from a group of Chinese mothers in Hong Kong. METHOD: Eight hundred and ninety-seven mothers from 13 child care centers in Hong Kong successfully completed a set of structured questionnaires consisting, among others, of the 77-item Abuse Scale of the CAP Inventory. A confirmatory factor analysis (CFA) was performed to determine whether the data fits the factorial structure of the CAP Inventory identified by Milner (1986). RESULTS: The root mean square error of approximation (RMSEA) of the model epsilona) is 0.031, indicating a close fit of the model in relation to the degrees of freedom. On testing the close fit against the null hypothesis that Ho: epsilona相似文献