A logistic learning curve applied as a compendium method for student classification

Teaching effectiveness can be improved through the categorical organisation of course plans. Allocating students to appropriate courses helps to reduce variations in learning activities and thereby enhances the capability and efficacy of an education programme. How much students benefit from a course should be treated as the most crucial criterion for judging the workability of any course arrangement. Pre-course test scores (t) and post-course score changes (d) are of crucial significance for student classification because they offer evidence for teachers' judgements in the selection of teaching material and pedagogical methods by indicating the knowledge that students have before the course study begins and the potential scholastic progress to be achieved. This paper presents a quantitative study of students' t and d in a remedial English programme. It demonstrates a reciprocal algorithm between these two exposures and justifies a modified logistical model as the applicable learning curve, with the hope of explaining their interaction more accurately.