Page 147 - Teaching Innovation for the 21st Century

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The UJ teaching and learning strategy emphasises the ‘learning to be’ philosophy, enhancing the quality of students’ learning, and driving excellence in teaching and learning. The UJ team sought to use Design-Expert® in the CELCHB3 module to improve the students’ learning environment, making provision for facilities and services in the design of laboratory experiments. In addition,
the exercise would enable the lecturers to demonstrate clearly to an ECSA panel the achievement of the GA4 in the students’ work.
Problem statement
Chemical Engineering undergraduate students are introduced to fundamental experimental skills in the first year in modules such as Chemistry and Physics. In the second year, they are introduced to chemical engineering- oriented experiments in Chemical Engineering Laboratory 2A and 2B, where they also learn data collection and interpretation. The CELCHB3 module, in the third year, has the specific goal of improving experimental design and analysis for GA4. Effective experimental design depends on a combination of mathematics principles including permutation, combination, blocking, factorial, square, Latin etc. (Lu 2011). Experimental analysis uses principles from statistics such as ANOVA, T-test, hypothesis, etc.
Students find it difficult to design experimental layouts manually, especially if they lack pre-knowledge of combinatorial mathematics. Although students are able to grasp the statistical analysis theories, the calculations can be laborious. As Lu (2011) notes, these challenges shift student attention away from experimentation, negatively impacting on their interest in experiment design. The integration of Design-Expert® into the CELCHB3 module, it was proposed, would assist UJ students in acquiring DOE skills.
in-depth knowledge of the design of experiment and the process analysis;
the ability to design, conduct and analyse experiments using up-to-date principles and computer software;
understanding of elementary probability essential for modelling data variability;
the know-how of statistical tests to analyse and interpret experimental data; and
the practical skills in conducting laboratory experiments and field surveys for data collection (Lu 2011).
Teaching Innovation for the 21st Century | Showcasing UJ Teaching and Learning 2021
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Students find it difficult to design experimental layouts manually, especially if they lack pre-knowledge of combinatorial mathematics.