Comparing predictive, simulation-based and hybrid assessments in undergraduate process engineering

Engineering education increasingly seeks assessment designs that preserve conceptual reasoning while supporting applied problem-solving. This study reports a classroom-based within-subject implementation in which the same cohort of second-year undergraduate process engineering students completed three assessment formats—predictive (theory-based), simulation-based, and hybrid (integrating predictive reasoning with simulation-supported testing and interpretation)—in a fixed order across two modules delivered within one academic year. Student performance was recorded as course marks on a 0–5 scale. A repeated-measures analysis indicated differences in marks across formats in both modules, with higher mean marks observed under the simulation-based and hybrid formats than under the predictive format; hybrid marks were also higher than simulation-based marks. Mark dispersion was lowest under the hybrid format and is reported descriptively as a consistency pattern rather than evidence of equity or fairness. Students also completed a purpose-developed questionnaire administered at the end of the study period, reporting perceived benefits related to adapting to the simulation environment, linking theory with simulated process scenarios, and increased confidence in problem-solving-related skills. Because formats were implemented sequentially without randomization, counterbalancing, or a comparison cohort, findings should be interpreted as associations observed under the implemented instructional sequence rather than causal effects attributable to the hybrid format. Future work should test assessment-format effects using controlled or counterbalanced designs and validated engagement and motivation measures.