Using Computational Modeling to Teach Experimental Design

Abstract

In many laboratories during an undergraduate science education, students are given a set of procedures to follow to obtain a pre‐determined outcome. Often students give little thought to the underlying scientific principles and lack a true understanding of the experimental protocol. Not only does this laboratory format not represent ‘real’ science, it leaves students unprepared for the often unpredictable and intimidating nature of experimental design. Here we have chosen classic biochemical experiments paired with computational modeling approaches to help students navigate the process of designing an experiment, from initial planning to hypothesis development to data analysis. Students can use the modeling mechanisms to help predict experimental outcomes and gain a better understanding of scientific concepts.