| Summary: | Maximizing national productivity through nurturing individual growth is a primary concern of developing nations like Malaysia. One corollary of this concern is the need to detect failing and 'at risk' pupils so that correct and timely intervention can be given to them. The primary purpose of this study is (1) to contribute to this by finding out and critically evaluating the existing system of monitoring poor performance and providing remedial treatment (2) to use the data gathered to build a checklist for preliminary identification and categorization of 'poor learners' and finally (3) to use the factors included in the checklist to develop a simple, useful and convenient mathematical model that can be used to predict 'at risk' pupils in Malaysian primary schools. In order to address the above research issues, an in-depth study of four Malaysian primary schools was carried out. The research was conducted in two stages. During the preliminary stage, the researcher used interviews, questionnaires, and document study to obtain, from school administration and teachers, information on the larger issues of the educational infrastructure. A sample of pupils' academic performance data was also done. The second stage of the study comprised of (1) a descriptive statistical analysis of survey data obtained via the teacher, pupil, and parent questionnaires (2) an inferential statistical analysis of the more pertinent survey data in relationship to pupils' performance in school-based assessments over three years covering Standards 4, 5, and 6 of their upper primary education, as well as in the standardized national Primary School Assessment Test. The study found that most "poor learners" are self-professed monolingual boys of Malay ethnicity from low socioeconomic family backgrounds, who have particular attitudes towards learning. Two main products resulted from this study: a checklist that characterizes the poor learners and a logistic regression model, which uses a mathematical equation to predict 'at risk' pupils.
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