Commentary: Grade The Degree, Not The Module

Assessment is a fixture of higher education. Around the world, the cycle is familiar: students complete coursework or sit exams, collect marks for each module, and graduate with a final degree classification. How assessments should be designed and delivered has always been debated, and AI has lately moved to the center of that debate. The model itself rarely gets questioned. This article does not argue against assessment. It argues that frequent, module-level assessment has reached the end of its useful life.

Universities assume that marks and transcripts give an objective picture of a student’s knowledge, skills and readiness for work. We seldom ask whether the structure we inherited is the only option. Yet two of the biggest operational pressures on modern universities stem directly from how assessment is designed: the administrative burden of continuous assessment and the strain on student mental health.

EMPLOYERS HAVE ALREADY MOVED ON

The share of UK employers screening applicants by minimum degree classification has fallen from 76% to 44%, according to the Institute of Student Employers. When NACE asks employers what they value most, communication and problem-solving consistently outrank technical knowledge. Employers want graduates who can think independently, not graduates who have learned to comply. Are we engineering our programs to maximize metrics the outside world has already discarded? Do we really believe recruiters audit transcripts to see how a student performed in an isolated second-year module?

Today’s model took shape when marking was done by hand, information was scarce and exams were the most efficient way to certify knowledge. Those conditions no longer hold. AI has transformed access to knowledge, and employers increasingly prize transferable capabilities.

Traditional assessment also has unintended consequences. Over time, students learn to prioritize the assessment brief over genuine understanding. They become risk-averse and fearful of failure. With AI now widely used by students and lecturers alike, we also risk building a system in which one AI drafts the assignment and another grades it. 

Put bluntly, the rush to deploy AI-detection software is an attempt to prop up a broken model rather than reimagine it.

WHAT A PROGRAM WITHOUT MODULE GRADES COULD LOOK LIKE

Imagine a program with no module-level grading. Students would still graduate with a classification, but the evidence of their learning would accumulate across the whole program rather than being split into dozens of isolated assessments. Think of the time that could shift away from marking, moderation and exhausting exam boards toward work that adds more value: coaching, industry engagement and professional development.

Such a model would fundamentally change students’ relationship with learning. It would free them to follow their curiosity and take intellectual risks. It would not lack rigor, either. Sustaining qualitative feedback and an ongoing intellectual dialogue with students demands more attention and presence than marking a script against a rubric.

What might replace module marks? One option is a single, comprehensive assessment at the end of the program. A student submits a substantial report and, two weeks later, defends it live before a panel of professors from different disciplines. An authentic assessment of this kind tests a wide range of knowledge and skills, and it is far harder for generative AI to do the work for the student.

To be clear, this is not a call for an assessment-free curriculum. Higher education has reinvented itself repeatedly: whether women could attend university, how degrees are structured, how learning is assessed and whether online delivery could be rigorous. Having navigated those shifts, the sector is well placed to rethink assessment. It is the next logical step.

Rigor does not require quantification. We have overlooked how traditional assessment shapes student behavior and consumes faculty time, perhaps because no one foresaw how quickly AI would advance. Change will not – and should not – happen overnight, and every stakeholder needs a voice in how the transition unfolds.

WHO NEEDS TO ACT

Individual academics, working within rules they did not write, cannot drive this transition. University leaders need the courage to question inherited assessment regulations and create room to experiment with program-level alternatives. Regulators and professional bodies should stop equating academic rigor with the volume of assessment. 

They should instead reward evidence that graduates can think and perform in complex, real-world settings. Accreditation bodies matter just as much. Rather than protecting inherited structures, they should actively encourage schools to challenge them. If universities are expected to innovate, that expectation should extend to how learning is evidenced.

It is time to stop testing memory and start evaluating capability through authentic industry projects, portfolios, continuous peer feedback, live simulations and role plays. If we say we prize curiosity and critical thinking, our assessment structures should reflect that. The future of higher education belongs not to those who preserve today’s assessment systems but to those willing to redesign them.

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Soheil Davari is Director of Accreditations at the University of Bath’s School of Management in the United Kingdom.

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