Are sport and exercise sciences students getting feedback they can use?
Mostly, not yet. Across the National Student Survey (NSS), Feedback comments skew negative overall, with 57.3% Negative and 33.5% Positive (sentiment index −10.2). In the biological and sport sciences cluster the tone is weaker at −16.6, even though within sport and exercise sciences students rate teaching highly while frustration centres on marking criteria (−38.4). Feedback here refers to the sector-wide theme in the NSS that captures how students experience assessment comments; sport and exercise sciences is the subject grouping used in benchmarking and programme review. These patterns shape what follows: practical disciplines need timely, specific feed-forward that students can apply immediately, and transparent criteria they can understand and use.
What are the unique feedback needs in sport and exercise sciences?
Students need feedback that addresses both theory and performance. Verbal guidance during coaching and laboratory work enables immediate adjustment; written commentary anchors reflection and planning. Effective practice prioritises specificity, alignment to the assessment brief and marking criteria, and a direct line of sight to what to do next. Staff should calibrate how they pitch feedback across classroom, lab, and field settings so students can translate comments into concrete changes in technique and academic work.
How do current feedback practices affect learning?
Where feedback arrives quickly and focuses on action, students correct techniques and refine academic work within the same teaching cycle. Where comments are generic or delayed, students disengage and repeat errors. Programmes that adopt consistent structures (criteria-referenced comments plus feed-forward) and standardise turnaround create a predictable rhythm students can rely on. Regular calibration of marking and spot checks on specificity tighten practice and reduce variability across modules.
What feedback do students in sport and exercise sciences expect and prefer?
Students prefer a blend: on-the-spot verbal advice during practicals, short written notes that map to criteria, and artefacts they can revisit, such as annotated exemplars or short clips. Video analysis supports self-correction between sessions, while concise rubrics reduce ambiguity and prompt questions. Personalised, technique-specific comments outperform generic statements and drive faster improvement.
What gets in the way of effective feedback?
Inconsistency across markers and variable turnaround times undermine trust. Students report difficulty applying feedback that does not reference the marking criteria or fails to indicate next steps. A programme-level framework helps: publish a feedback service level by assessment type, require feed-forward, and use a single template for comments. Quick calibration sprints before major assessment points align standards and language, and small “how to use your feedback” prompts inside modules make application routine.
How can technology enhance feedback?
Digital tools extend immediacy and precision. Online platforms streamline turnaround and make audit trails visible. Video analysis shows form and execution, turning tacit coaching advice into visible prompts. Sensors and performance trackers add quantitative markers that sit alongside qualitative comments. Analytics dashboards help staff tailor guidance to individual needs and spot patterns where students misinterpret criteria or underuse comments.
Which feedback models work well?
Integrated models blend real-time coaching cues with short, structured post-session reflections. For example, combining live video capture with follow-up clips annotated against the marking criteria supports both instant correction and deeper understanding. Mobile tools that deliver sprint splits and biomechanical cues during track sessions encourage self-regulation and reduce reliance on staff between taught sessions. In each case, the common features are timely delivery, actionable next steps, and a tight link to the assessment brief.
What should higher education staff do now?
- Reset the basics: publish turnaround expectations, track on-time rates, and make feed-forward mandatory alongside criteria-referenced comments and annotated exemplars.
- Target the cohorts most likely to struggle with feedback use by building short “how to use your feedback” guides into modules and standardising comment structures.
- Calibrate where tone is weakest by running shared marking of samples and adding spot checks on specificity, actionability and alignment to criteria.
- Lift practice from provision that already works well (e.g. staged feedback and dialogic sessions) and adapt for high-volume full-time modules.
- Close the loop visibly with “you said → we did” updates that show changes and on-time performance.
How Student Voice Analytics helps you
Student Voice Analytics turns open-text feedback into trackable priorities for sport and exercise sciences. It surfaces sentiment and topics over time, with drill-downs from provider to school and programme, and segment differences by age, mode, disability, domicile, and subject grouping. You can compare like-for-like with the wider subject cluster, export concise anonymised summaries to module teams and boards, and monitor on-time rates and feedback quality indicators. The platform helps you focus on timeliness, usefulness and criteria clarity, and evidence progress through visible “you said → we did” updates.
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