Investigating engineering students’ performance, self-efficacy and underlying difficulties in mathematical modelling tasks

The complex nature of the modelling process may make it difficult for students to build mathematical models. Previous studies mainly focused on students’ difficulties in iterative modelling processes, while limited attention has been given to difficulties during the formulation and construction of mathematical models, particularly optimisation-based models. Therefore, this study investigates the underlying reasons for challenges encountered by engineering students in modelling tasks requiring optimisation-based models. The study included 116 industrial engineering students enrolled in the ‘Modeling in Industrial Engineering’ course. Students’ performance in four modelling tasks was evaluated across the model-construction steps of identifying the variables, constructing the objective function and stating constraints. Students’ modelling self-efficacy, perceptions of task difficulty and underlying reasons for difficulties were also examined. The results indicated that students performed weakest in maximum-minimum objective functions and variables as fractions of other variables and reported moderate-to-high (3.84) modelling self-efficacy. These tasks were also perceived as most difficult. The most frequently identified reasons included problem misinterpretation, excessive number of variables, inadequate mathematical expression skills, overwhelming constraints and insufficient integration of prior problem-solving experiences. In total, 19 codes were identified across five themes: understanding the problem, identifying the variables, constructing the objective function, stating the constraints and other reasons.