Improving Causal Reasoning in Pre-University Biology Education: A Design Study

Abstract

Biology students need causal reasoning to understand complex systems, but their causal reasoning is underdeveloped. In this study, causal reasoning is defined as a set of skills to explain phenomena, draw conclusions and implications, and make predictions. A promising strategy to enhance causal reasoning is developing tools that help students to construct a causal map. Systems modelling tools is a class of tools that integrates all three principles of causality (priority, covariance, mechanism) and the four causal dimensions to explain a causal process (agency, interaction pattern, probability, and mechanism). The aim of this study is to evaluate the utility of systems modelling tools in enhancing causal reasoning of pre-university biology students. An intervention was designed and enacted during biology lessons in a Dutch secondary school (grade 11) in a treatment-control group experimental design. The treatment class performed a lesson activity with a causal map, while the control class did a similar activity, but without a causal map. The use of the causal dimensions was monitored with a pretest and posttest, combined with interviews. The treatment class did not improve significantly more than the control class for the agency and interaction pattern, but there was a trend visible. The treatment group showed a little improvement of the probability and mechanism during the lesson activity. It is concluded that it is worthwhile to improve the design of the lesson activity in order to enhance causal reasoning in biology students.