Abstract:

Course syllabi play a central role in higher-education degree programs, as they formalize learning objectives, workload allocation, and assessment strategies that ultimately determine students’ progression and achievement. Within the European Higher Education Area (EHEA), continuous assessment has become a widely adopted pedagogical approach, intended to promote sustained engagement and formative learning while aligning assessment practices with the principles of student-centered education. However, the cumulative effects of multiple assessment components and their relative weightings on grade formation are rarely examined from a quantitative, system-level perspective.

In this study, we develop and analyze a statistical simulation model of grade formation under a continuous assessment framework applied to an 8-ECTS Physics course within Engineering programs at the School of Aerospace Engineering and Industrial Design (ETSIADI), Universitat Politècnica de València. The course evaluation system integrates four assessment components—open-ended written examinations, online assessments, laboratory sessions, and a team-based academic project—each contributing differently to the final grade. Treating the overall course grade as a random variable, we perform large-scale Monte Carlo simulations to characterize the probability distributions of final grades at successive stages of the academic term, both independently of empirical performance data and under constraints informed by observed student outcomes from previous cohorts.

The results reveal that, under the current weighting scheme, a non-negligible probability exists for students to reach the passing threshold well before completing the full course workload, particularly when assessment components with low failure rates are included. Further simulations show that students may retain a realistic chance of passing even when omitting an entire assessment component, except for the highest-weighted written examinations. These findings highlight structural features of continuous assessment systems that may unintentionally weaken the alignment between declared credits, effective workload, and demonstrated learning.

The proposed simulation framework offers a flexible and generalizable tool for evaluating and redesigning continuous assessment systems. By enabling systematic exploration of assessment weightings and performance constraints, it supports evidence-based decisions in course design, credit allocation, and quality assurance, contributing to ongoing institutional efforts to improve curricular coherence and academic standards.

Keywords:

Academic credit, course syllabus, assessment system, statistical simulation.