Open AccessDeveloping an Innovative Program for First Year Engineering Statistics Students at an Open Distance University
Author(s) -
Richard Naidoo,
Ngaka Mosia
Publication year - 2020
Publication title -
european distance and e-learning network (eden) conference proceedings
Language(s) - English
Resource type - Journals
ISSN - 2707-2819
DOI - 10.38069/edenconf-2020-ac0039
Subject(s) - statistic , mathematics education , computer science , statistics education , process (computing) , engineering education , distance education , statistics , cognition , open source , intervention (counseling) , psychology , engineering , mathematics , engineering management , neuroscience , psychiatry , operating system , software , programming language
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 TL 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%.