What do economics students need from feedback?
Published May 21, 2024 · Updated Feb 24, 2026
feedbackeconomicsIn economics, where modules build quickly, students need feedback they can act on before the next assessment. That means timely, criteria‑referenced guidance that links models, marking criteria, and assessed outcomes.
NSS open‑text suggests that bar is not being met consistently. Across the National Student Survey (NSS) open‑text for the Feedback theme, comments skew negative overall: 57.3% are negative and the sentiment index is −10.2. Within the sector’s economics grouping, feedback makes up 9.8% of all comments and has a −21.2 tone, with the sharpest pain point around marking criteria (−48.1).
Those patterns point to three priorities below: make expectations explicit, give structured feed‑forward, and return feedback fast enough to change what students do next.
Why does appropriate feedback matter in economics?
Targeted, constructive feedback builds deeper understanding of concepts and models and helps students apply theory in real contexts. Without specific, actionable guidance aligned to assessment briefs and marking criteria, students can struggle to connect abstract frameworks to applications and to see how their work is judged. Feedback that bridges theory and practice, and explains how to improve against the criteria, strengthens both comprehension and performance.
What do economics students expect from feedback?
Students expect comments they can use before the next assessment: specific to their work, mapped to learning outcomes, and clear about what “meets” versus “exceeds” looks like. They value timely responses that link models to current issues and to the assessment rubric. Vague or late comments reduce confidence and make it harder to adjust in modules where concepts build quickly.
What makes delivering quality feedback difficult?
Large cohorts and varied mathematical preparation demand personalisation at scale. Staff are expected to provide detailed, criteria‑referenced comments across many submissions while managing workload and turnaround times. Economics spans abstract theory and applied analysis, so feedback needs to correct errors and explain why they matter. Delays reduce usefulness because students move quickly onto new material. The takeaway is that quality has to be designed into the process, not left to individual effort.
What happened when feedback targeted models and theories?
A recent case study with undergraduate economists suggested that context‑specific comments on assignments improved comprehension of advanced concepts more than generic notes. On an econometrics task, feedback that corrected computations and explained their economic meaning helped students connect theory to application and improve subsequent work. Where feedback was brief or lacked examples, progress stalled. Timely post‑assessment comments helped reduce misconceptions before students moved on to more complex topics.
Which strategies improve feedback in economics education?
Prioritise clarity and feed‑forward. Use concise rubrics with annotated exemplars, and require comments to reference criteria and state specific next steps. Publish and track a feedback turnaround service level by assessment type, and use “you said → we did” updates to close the loop. Calibrate markers with short sprints using shared samples to improve consistency across modules.
Borrow what works in settings with stronger sentiment by staging feedback and building short dialogic sessions into tutorials. Integrate worked real‑world examples to anchor abstract models, and use peer review to extend practice without sacrificing quality.
Increasing the number of teaching assistants can expand opportunities for individual guidance in large classes, but the core gains come from consistent structures: mapped outcomes, exemplars, and feed‑forward.
How can technology strengthen feedback?
Digital tools help scale timeliness and consistency. Automated checks on quantitative work can flag common errors quickly, while economic simulation tools let students test assumptions and see implications immediately. Online discussion spaces support rapid clarification and peer learning, and structured templates within virtual learning environments standardise how criteria, exemplars, and next steps are presented. Technology should complement, not replace, the dialogic elements students value.
What should economics departments do next?
Integrate real‑world applications into feedback, and make criteria visible with exemplars. Publish an achievable turnaround promise, monitor it, and intervene where slippage occurs. Run brief calibration exercises in high‑volume modules, and require feed‑forward so students know what to change next. Name an owner for communications and timetabling to reduce friction, and show termly progress on on‑time rates and format changes. Maintain human contact through workshops and tutorials where students can interrogate guidance.
How Student Voice Analytics helps you
- Turns NSS open‑text into trackable feedback metrics, including sentiment, volume, and segment differences by age, mode, disability, domicile, and subject.
- Benchmarks economics against the wider institution and like‑for‑like subjects, so programme teams can prioritise assessment clarity, calibration, and turnaround where sentiment is weakest.
- Enables drill‑downs from provider to school and programme, and exports concise, anonymised summaries for module teams and boards.
- Tracks improvement over time with consistent measures, making it straightforward to share priorities and progress with students and staff.
Want to see what this looks like for your institution? Explore Student Voice Analytics.
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