Accurate assessment of student workload is vital for competence-oriented higher education and fair ECTS allocation. Yet, standard estimates based on average working hours overlook students’ subjective workload experience. This preregistered study adapts the multidimensional NASA Task Load Index for university courses to examine how workload expectations at term start and experienced workload judged at term end predict course evaluations, objective learning goal achievement (course grade), perceived ECTS appropriateness, and global study satisfaction. Both students and their lecturers independently assess the subjective workload of their university courses at term start (T1, expected) and at term end (T2, experienced). Our planned analyses (Bayesian linear mixed models) focus in particular on expectation-experience discrepancies between students’ subjective workload judgements at term start and end as well as between student and lecturer assessments. We hypothesize that discrepancies in subjective workload expectations and/or experiences negatively impact on course evaluations and ECTS appropriateness ratings, predict lower learning goal achievement (worse course grades), and lead to reduced global study satisfaction. The study integrates multi-informant subjective workload measures and outcome measures to derive evidence-based recommendations for ECTS allocation, course design, and instructor–student workload communication.