Dominant misconceptions and alluvial flows between Engineering and Physical Science students

TL;DR

This study compares physics misconceptions between Engineering and Physical Science students, revealing persistent misconceptions and differences in learning patterns using graphical analysis of pre- and post-test data.

Contribution

It introduces a graphical approach with alluvial diagrams to track misconceptions and learning progress among students in different science disciplines.

Findings

Engineering students outperformed Physical Science students on average.

Persistent misconceptions remained after instruction.

Physical Science students showed more chaotic learning choices.

Abstract

In this article we assess the comprehension of physics concepts by Physical Science and Engineering students enrolled in their first semester at the University of Johannesburg (UJ), South Africa ($2022$). We employ different graphical measures to explore similarities and differences using the results of both pre- and post-test data from the Force Concept Inventory assessment tool, from which we calculate dominant misconceptions (DMs) and gains. We also use alluvial diagrams to track the choices made by these two groups of students from pre- to post-test stages. In our analysis, we find that DM results indicate that participating Engineering students outperformed Physical Science students on average, however, the same types of normalised DMs persist at the post-test level. We call these DMs "persistent misconceptions." This is very useful when tracking persistent misconceptions, where when using repeated measures and alluvial diagrams with smaller groups of students, we find that Physical Science students tend to make more chaotic choices.