Developing an Innovative Program for First Year Engineering Statistics Students at an Open Distance University

Richard Naidoo
University of South Africa (Unisa)
naidor@unisa.ac.za

Mosia Ngaka
University of South Africa (Unisa)
mosian@unisa.ac.za

Abstract

A study was performed on a first year industrial engineering statistics course to improve the statistics pass rate. Statistics is a requisite for other engineering courses. The pass rate for the statistic course was below 50%. The primary purpose is to enable learners to build a capacity to comprehend module content and establish a deeper level of learning that will enable learners to achieve goals and objectives of T&L lessons. An intervention program was instructionally designed to develop a personalized and differentiated learning process that breaks down lessons into lower and basic cognitive components, for struggling learners. The program improves e‑learning lessons to a complex higher cognitive level and advances challenging activities for excelling students. Forty students were considered for the study. Moore’s theory of transactional distance was used as a theoretical framework. A quantitative method was used to analyse the data. The data consisted of assignment scores. Hypothesis testing at a 95% level of significance suggests that the intervention program made an impact. The overall pass rates improved by 25%.

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