The Innovative School: Organization and Instruction

Researchers in the area of educational effectiveness should attempt to develop a new theoretical framework. A critical analysis of the current models of educational effectiveness research is provided and reveals that a dynamic model of effectiveness must: (a) be multilevel in nature, (b) be based on the assumption that the relation of some effectiveness factors with achievement may be curvilinear, (c) illustrate the dimensions upon which the measurement of each effectiveness factor should be based, and (d) define relations among the effectiveness factors. In principle, each factor that refers to the classroom, school, and system, can be measured by taking into account five dimensions: frequency, focus, stage, quality, and differentiation. Examples of measuring effectiveness factors operating at different levels using these 5 dimensions are given. More attention in describing in detail factors associated with teacher behaviour in the classroom is given, since this is seen as the starting point for the development and the testing of the dynamic model. Finally, suggestions for the next steps in the development of other parts of the model are provided.     

On‐screen print: the role of captions as a supplemental literacy tool

Children living in poverty are 1.3 times as likely as non‐poor children to experience reading difficulties and lack key oral experiences that contribute to early literacy development. The purpose of this research was to study the effects of viewing commercially available educational television with closed captions. Seventy second‐ and third‐grade economically disadvantaged children living in urban locations participated in this experimental research design. Children were randomly assigned to view videos with or without closed captions. Captions helped children recognise and read more words, identify the meaning of those words, generate inferences regarding programme content and transfer these skills to a normative code‐related skill task. Risk status moderated word recognition performance: those at risk benefited from captions while those who were not at risk recognised more words when captions were absent.     

Statistical methods for analysing discrete and categorical data recorded in performance analysis

In this paper, we identify appropriate statistical methods for analysing categorical differences in discrete variables or 'performance indicators' resulting from performance analysis. The random mechanisms associated with discrete events do not follow a normal distribution; that is, the normal distribution is a continuous not a discrete probability distribution. We propose appropriate statistical methods based on two key discrete probability distributions, the Poisson and binomial distributions. Two approaches are proposed and compared using examples from notational analysis. The first approach is based on the classic chi-square test of significance (both the goodness-of-fit test and the test of independence). The second approach adopts a more contemporary method based on log-linear and logit models fitted using the statistical software GLIM. Provided relatively simple one-way and two-way comparisons in categorical data are required, both of these approaches result in very similar conclusions. However, as soon as more complex models or higher-order comparisons are required, the approach based on log-linear and logit models is shown to be more effective. Indeed, when investigating those factors and categorical differences associated with binomial or binary response variables, such as the proportion of winners when attempting decisive shots in squash or the proportion of goals scored from all shots in association football, logit models become the only realistic method available. By applying log-linear and logit models to discrete events resulting from notational analysis, greater insight into the underlying mechanisms associated with sport performance can be achieved.