2025 ASEE Annual Conference & Exposition

One of the most fundamental skills in the domain of civil engineering is the ability to define a problem and draw a free-body diagram to represent it. These techniques involve abstraction, transforming a complex system from reality into a solvable and comprehensible set of forces and moments. This connection allows students to translate theoretical knowledge into practical application. As a result, fostering this abstract thinking is crucial in developing future engineers capable of identifying, formulating, and solving complex engineering problems, which is an ABET student outcome criterion. However, problems posed in current engineering courses do not always require students to perform these abstraction steps on their own. A well-structured, pre-abstracted problem reduces the cognitive load required to solve it and allows space for students to build other content knowledge, but it can limit students’ ability to develop essential abstract thinking skills.

In this study, we redesigned a sophomore-level engineering statics course that primarily relies on real-world, non-abstracted problems. The curriculum also emphasizes teamwork to help students engage with and solve problems of increasing complexity. Problems were written by the course instructor based on real-world contexts from the surrounding geographic area and from contexts and questions proposed by students in another mechanics course. We examined how varying levels of abstraction, as determined by the course instructor and students’ self-reported perceptions of the problems, influenced student performance and self-reported problem-solving self-efficacy (PSSE). PSSE was measured through a survey developed based on a problem-solving rubric that assesses various steps in the problem abstraction and solving process, for example, problem statement and visual representation. The PSSE survey was completed by students in groups for each problem set. In parallel, the authors rated the difficulty of each problem using a similar rating scale to the students and an assessment of the complexity, structuredness and clarity of each problem.

Descriptive statistics were calculated for the different sub-constructs of PSSE, test scores, and homework grades. Correlations were calculated between PSSE sub-constructs and student performance outcomes. Early results indicate that students report higher levels of discomfort on problems requiring a higher level of abstraction, but this discomfort has little to no correlation with group performance.