Abstract
SUMMARY In this paper an attempt is made to identify factors which affect the behaviour of pupils in terms of academic survival. Structural features are included in the analysis. The data analysed are taken from a longitudinal national sample survey which makes it possible for each pupil to be classified by the educational criteria and by a number of different exogenous factors simultaneously. The method of analysis is based on a multivariate technique developed for initial exploration of simultaneous effects, by which no functional model is imposed and no additivity of effects assumed. 1.1. Purpose THE present study examines the ways in which factors exogenous to the formal structure of the education system affect the flow proportions of pupils from one stage of academic studies to the next. This investigation was undertaken as part of a larger study attempting to build a model of the system (Armitage et al., 1970). The basic model is being built with the forecasting of future trends and outputs in mind, and special attention is focused on the upper section of secondary education, from the statutory leaving age to higher education entry, in which opportunity and choice determine the type and level of education attained by individuals. A sub-model dealing in some detail with this section is worked on, the detail being in terms of school types, subject specialization, or bias, and sex. Although the use of model-building techniques in educational research is relatively new, the work done hitherto has necessitated a critical appraisal. Forecasts, even short-term ones, have turned out to be far from what actually happened in reality, suggesting that insufficient information concerning the underlying factors which affect pupils' behaviour and change over time is fed into the model. The attempt here is to identify some of these underlying factors by examining a number of personal, social and school features together with the structural divisions of the school system. It is a first step towards incorporating in a 15-19-year-olds model those factors which account most for differences in the behaviour of pupils, in order to increase its predictive power. Operationally, the following questions to be answered by the study were formulated:
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More From: Journal of the Royal Statistical Society. Series A (General)
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