Academic Feedback: the Students’ Story: Presentation on Masters research on student academic feedback.

Research output: Contribution to conferenceAbstractpeer-review

Abstract / Description of output

Background: Academic feedback is widely regarded as an essential part of student learning yet is consistently rated poorly in the National Student Survey across UK veterinary and medical schools. This project was designed to explore the underlying issues by analysing expectations and experiences in students on a 5 year undergraduate and 4 year graduate entry veterinary programme.
Summary of work: Qualitative and quantitative methodology was used to explore new students’ expectations and prior experiences of feedback. Experiences were also tracked across one academic year and through sampling the third and final year cohorts.
Summary of results: Both school and graduate entry first year veterinary students expect no less feedback at university than at school. Verbal feedback and specimen answers were seen as the most useful forms of feedback. Students’ experiences of the course highlighted themes of not knowing what is expected; feedback timeliness and a perceived need for more guidance. Perceptions of feedback being insufficient were also prevalent in later years.
Conclusions: Students entering vet school have a good understanding of the varied forms of academic feedback and clear ideas about what they expect; these expectations in general are not being met.
Take-home messages: This study confirms a mismatch in student expectations versus experience. Further work is exploring staff perceptions with the aim of developing mechanisms to bridge the expectations/experiences gap.
Original languageEnglish
Publication statusUnpublished - 2009
EventAssociation for Medical Education in Europe (AMEE) Conference - Malaga, Spain
Duration: 31 Aug 20092 Sept 2009

Conference

ConferenceAssociation for Medical Education in Europe (AMEE) Conference
Country/TerritorySpain
CityMalaga
Period31/08/092/09/09

Keywords / Materials (for Non-textual outputs)

  • VMED

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