Updated Sep 07, 2026
assessment methodsfeedbackAdvance HE's new assessment and feedback compendium is worth attention because it gives universities current, concrete examples of how to respond when students keep raising the same assessment problems. On 25 June 2026, Advance HE announced its case study collection on assessment and feedback and highlighted the linked Assessment and Feedback Case Study Compendium 2026. For teams collecting student voice through module evaluations, NSS, PTES, or local surveys, the practical value is simple: this is a ready-made set of live sector examples for turning recurring comments about assessment into clearer design and governance decisions.
This is not a regulatory change or a new national survey rule. It is a sector-facing Advance HE resource, available now, that brings together 22 case studies across four volumes. The collection covers creating inclusive assessment and feedback design, engaging students with feedback, developing authentic assessments for an AI-enabled world, and designing sustainable and workload-aware assessment practices. That breadth matters because it treats assessment and feedback as a connected institutional problem, not as a set of isolated tactics.
The case studies developed from sessions at the November 2025 Assessment and Feedback Symposium, according to the announcement.
The Engaging students with feedback volume is listed with a 17 June 2026 publication date. Its contents page identifies five contributions: structured self-assessment with dialogue; self- and peer feedback in assignments; a multi-part feedback strategy; reflection and agency in a learning community; and AI-generated process mapping in simulation-based learning. Contributors include institutions in the UK and Australia, with a US co-author in the final case study.
This briefing checks the release, collection page and volume contents, rather than independently verifying the findings of all 22 case studies. Read the relevant case's method and limitations before adopting it. A compendium presents examples from particular settings, not a single tested intervention with guaranteed results elsewhere.
The first implication is that assessment comments should be treated as design evidence, not only as satisfaction evidence. If module evaluations, NSS comments, or taught postgraduate surveys keep surfacing unclear briefs, inconsistent marking, weak feedback uptake, or assessment bunching, the next step should not be another generic action note. It should be a more specific redesign question. That is why this compendium is useful. It gives teams examples they can test against the issues students are already raising, much like Advance HE's inclusive assessment tool gave teams a more structured way to read recurring assessment concerns earlier this month.
The second implication is that institutions need a tighter bridge between collection and action. A broad dissatisfaction score alone does not identify which part of the assessment process needs attention. The compendium points towards a more disciplined approach: separate issues with task design, preparation, workload, marking, feedback dialogue, and AI-related expectations before deciding what to fix. Our discussion of feedback expectations offers a related reading route; local students should help define the problem to solve.
The third implication is about evidence for quality and enhancement teams. Because the collection spans co-design, AI-enabled assessment, and workload-aware practice, it gives institutions a way to connect local action to wider teaching and enhancement themes. The practical takeaway is to use the compendium as a structured prompt: which assessment problems are students describing, which type of intervention fits those problems, and how will the institution know whether the change actually improved the student experience?
This is where open-text analysis becomes more useful. Students rarely describe assessment problems in one clean category. A single comment may mix unclear instructions, poor timing, inconsistent criteria, slow turnaround, and frustration that the feedback could not be used on the next task. A structured method such as our NSS open-text analysis methodology helps teams separate those strands before they map them to a case-study response from the compendium.
Our suggested approach is to turn comment themes into specific design questions, then check those interpretations with the people affected. This is editorial advice, not an outcome demonstrated by the compendium release. If your institution wants to use the compendium without relying on anecdote or a handful of memorable quotes, our student comment analysis governance checklist is a practical place to start. One reproducible method makes it easier to compare module feedback, annual surveys, and local assessment pilots, and to show why a particular intervention was chosen.
Q: What should institutions do now with Advance HE's assessment and feedback compendium?
A: Start with the last full cycle of assessment-related comments from module evaluations, NSS, PTES, or local surveys. Group them into a small number of design issues, such as briefing clarity, workload, marking consistency, feedback usefulness, or AI-related expectations, then match those issues to the most relevant volume in the compendium. The goal is to move from a generic "feedback problem" to one or two specific interventions that can be tested in the next review cycle.
Q: What is the timeline and scope of this change?
A: Advance HE published the announcement on 25 June 2026, and the compendium page was published on 17 June 2026. There is no phased implementation or mandatory adoption date because this is sector guidance rather than regulation. The intended audience is higher education practitioners, especially teams reviewing assessment and feedback practice, and the case studies include UK and Australian examples.
Q: What is the broader implication for student voice?
A: The broader implication is that student voice on assessment is only useful if institutions can translate repeated comments into named design choices, owners, and review points. That is a proposed improvement process. Whether it improves experience or trust requires local evaluation.
Correction, 7 September 2026: the feedback volume's case-study topics have been corrected against its contents page. An unverified quotation and implied outcome guarantees have been removed; this briefing does not claim to verify all case-study findings.
[Advance HE]: "Case study collection on assessment and feedback published" Published: 2026-06-25
[Advance HE]: "Assessment and Feedback Case Study Compendium 2026" Published: 2026-06-17
[Advance HE]: "Engaging students with feedback" Published: 2026-06-17
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