Assessing Engineering Students’ Systems Thinking and Modeling Based on Their Online Learning

Abstract

Contribution: Model-based learning improves systems thinking (ST) based on students’ prior knowledge and gender. Relations were found between textual, visual, and mixed question types and student achievements. Background: ST is essential to judicious decision-making and problem-solving. Undergraduate students can be taught to apply better ST, and analysis of their online systems modeling processes can improve their ST. Research Questions: 1) What is the effect, if any, of online learning on the ST and conceptual modeling skill levels of undergraduate engineering students? 2) What differences are there, if any, between students’ ST, conceptual modeling, and scores in textual, visual, and mixed question types based on their prior knowledge levels? and 3) Are there any gender differences in student performance, and if so, what are they? Methodology: The research participants were 157 undergraduate engineering students who took part in a mandatory second-year course, during which data were collected and analyzed quantitatively. Findings: Students with disparate prior knowledge differed significantly from each other in their overall ST mean score and in the mean scores of the various question types. Gender differences in ST and its relative improvement were also found.