Clarifying the unseen: Assessment workload and time expectations for students in higher education

Abstract Transparency in assessment workload in higher education remains underexplored in research and policy. Students can only develop deep learning strategies and avoid surface learning when they have clear expectations about distribution of assessment workload and the required time investments. This study combines a scoping review of 50 articles to identify how assessment workload is measured with a document analysis of assessment practices in economics and business programmes at a Dutch university. The scoping review identified seven dimensions of assessment workload: quantity, weight and grading, difficulty, redundancy, types and variety, clarity of information, and distribution patterns. Together these dimensions shape students' time allocation and their psychological responses, such as stress and demotivation. Framing assessment workload through these dimensions enables academic staff to communicate expectations and identify gaps between intended and perceived assessment workload. The document analysis shows high reading loads, high clustered assessments quantity, and reliance on multiple high‐stakes exams which may contribute to student stress and ineffective time management. The findings suggest the need to optimize assessment workload at the programme level by improving distributions and enhancing transparency in expectations. Context and implications Rational of this study: This study further develops the concept of assessment workload in higher education to enable transparency in assessment. It highlights the need to optimize workload distribution and to be transparent about it to students to promote learning. Why the new findings matter: By identifying seven assessment workload dimensions and revealing uneven assessment workload across study units, this study highlights the need for greater attention to assessment workload in order to improve fairness, learning quality, and student well‐being. Implications for policymakers, educational experts, programme managers: Optimizing assessment workload requires a multilevel approach to ensure transparency within programmes and courses, enabling students to understand expectations, cognitive demands, and assessment workload distribution. Students and teachers need a shared understanding of expectations, rationales, and effort. A systemic approach is needed to provide students with sufficient time for meaningful learning, reduce stress, and promote well‐being, engagement, and balanced progress throughout the academic year. Our methodology offers a cost‐effective way to map assessment workload at programme level and to identify courses that may require closer review.