What do economics students need from feedback?
Economics students need feedback that is timely, criteria‑referenced and oriented to next steps, with explicit links between models, marking criteria and assessed outcomes. Across the National Student Survey (NSS) open‑text for the Feedback theme, comments skew negative, with 57.3% negative and a sentiment index of −10.2, so timeliness and usefulness remain the basic test. In the sector’s economics grouping, feedback occupies 9.8% of all comments and carries a −21.2 tone, with the steepest pain points around marking criteria at −48.1. These patterns shape the 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 fosters a deeper understanding of concepts and models, and equips students to 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 understand how their work is judged. Feedback that bridges theory and practice, and that explains how to improve against the criteria, strengthens both comprehension and performance.
What do economics students expect from feedback?
Students expect comments they can act on before the next assessment: specific to their work, mapped to learning outcomes, and showing what “meets” versus “exceeds” looks like. They value timely responses that link models to current economic issues and to the assessment rubric. Vague or late comments reduce confidence and make it harder to adjust approach in modules where concepts build quickly.
What makes delivering quality feedback difficult?
Large cohorts and diverse mathematical preparation require personalisation at scale. Staff face pressure to provide detailed, criteria‑referenced comments across many submissions while managing workload and turnaround expectations. Economics spans abstract theory and applied analysis, so feedback must both correct errors and explain implications. Delays reduce usefulness because students move rapidly to new material.
What happened when feedback targeted models and theories?
A recent case study with undergraduate economists showed 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 improved subsequent work. Where feedback was brief or lacked examples, progress stalled. Timely post‑assessment comments reduced misconceptions before students advanced 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, using “you said → we did” updates to close the loop. Calibrate markers with short sprints using shared samples to improve consistency across modules. Lift what works in settings with strong 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. 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 metrics for feedback, with sentiment, volume and segment differences by age, mode, disability, domicile and subject.
- Shows how economics compares with the wider institution and with like‑for‑like subjects, so programme teams can prioritise assessment clarity, calibration and turnaround where tone is weakest.
- Enables drill‑downs from provider to school and programme, and exports concise, anonymised summaries for module teams and boards to act on.
- Evidences improvement over time through consistent measures, making it straightforward to share priorities and progress with students and staff.
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