Progress at school and school effectiveness: non-cognitive dispositions and within-class markets

The New Zealand Progress at School project, designed to investigate school effects, found that individual progress at school is associated with a set of non-cognitive dispositions, most importantly, aspiration, self-concept, and acceptance of the institutional regime. The few schools identified as over-and under-performing were distinguished by the favourable and unfavourable dispositions of their students. School composition - or mix - effects proved in this study to be minor and relative to the output criterion, and some implications of that, including the selective effects of within-class markets, are discussed with particular reference to another contemporary New Zealand study, the Smithfield project. It is concluded that the study of school effectiveness might usefully include in its models the relationship between the properties of systems, the level of disposition, and the forms of practice they generate.     

A Structural Equation Modeling of the Factors Affecting an Age-friendly Workplace

There has been a growing trend recently to examine the various factors affecting an age-friendly workplace. Through structural equation modelling (SEM), this study purports to test a model that shows the interaction between and among declining memories, wisdom, age discrimination, and an age-friendly workplace in Filipino elderly in a government setting. Two hundred elderly from a large government bank in the Philippines participated in this study. Data were obtained through a self-completion questionnaire and a one-on-one interview. Surprisingly, results revealed that declining memory has no significant effect on wisdom. However, wisdom has a positive impact on age discrimination as does age-discrimination on an age-friendly workplace. The authors discuss the implications of these results and highlight directions for future research.     

Mining knowledge from natural language texts using fuzzy associated concept mapping

Natural Language Processing (NLP) techniques have been successfully used to automatically extract information from unstructured text through a detailed analysis of their content, often to satisfy particular information needs. In this paper, an automatic concept map construction technique, Fuzzy Association Concept Mapping (FACM), is proposed for the conversion of abstracted short texts into concept maps. The approach consists of a linguistic module and a recommendation module. The linguistic module is a text mining method that does not require the use to have any prior knowledge about using NLP techniques. It incorporates rule-based reasoning (RBR) and case based reasoning (CBR) for anaphoric resolution. It aims at extracting the propositions in text so as to construct a concept map automatically. The recommendation module is arrived at by adopting fuzzy set theories. It is an interactive process which provides suggestions of propositions for further human refinement of the automatically generated concept maps. The suggested propositions are relationships among the concepts which are not explicitly found in the paragraphs. This technique helps to stimulate individual reflection and generate new knowledge. Evaluation was carried out by using the Science Citation Index (SCI) abstract database and CNET News as test data, which are well known databases and the quality of the text is assured. Experimental results show that the automatically generated concept maps conform to the outputs generated manually by domain experts, since the degree of difference between them is proportionally small. The method provides users with the ability to convert scientific and short texts into a structured format which can be easily processed by computer. Moreover, it provides knowledge workers with extra time to re-think their written text and to view their knowledge from another angle.     

Effects of race and social class on preschool performance on the developmental test of visual-motor integration

The visual-motor integration of preschool children who varied in terms of race, sex, and socioeconomic status was assessed using the Beery-Buktenica Test of Visual-Motor Integration (VMI). An analysis of covariance revealed that there were significant main effects for race, sex, and socioeconomic status. Since, at the three- and four-year level, the VMI was normed only on white suburban children, the results of this study seemed to indicate the need for norms for black children at the preschool level. Thus, the second part of this paper reports normative data for black preschool children on the VMI.