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J Vet Med Educ ; 34(4): 524-8, 2007.
Article in English | MEDLINE | ID: mdl-18287483

ABSTRACT

Veterinary colleges face difficulties in meeting the demand for rural veterinarians with the scope to practice quality production medicine. Increasing population density around veterinary colleges, retaining the interest of students with a background in animal agriculture, and educating students without a farm background requires that veterinary colleges consider innovative ways to not only teach traditional food-animal practice but give future veterinarians the advanced skills the food industry demands. This article describes a three-year elective program, Beef Records Analysis, in which beef production medicine is taught by teaming a student and a beef producer together early in the student's veterinary education. These producer/student teams complete risk assessments, balance rations, collect financial and production information, and evaluate back-grounding and feedlot enterprises. Students learn how to evaluate their producers using industry benchmarks and past performance records and how to communicate their findings back to their producer. Producers often make management decisions based on the students' findings, and, because the students maintain their relationships with producers for three years, they can assess the outcomes of the producers who follow or ignore their recommendations and interventions. Students share recommendations and outcomes associated with their herd with the entire class. This allows students to learn how to establish best management practices through objective analysis of outcomes of recommended practices of all herds represented in the class. While a formal assessment of the course is needed, the students rate the program very high on evaluations.


Subject(s)
Animal Husbandry/education , Education, Veterinary/methods , Food Industry , Problem-Based Learning , Veterinary Medicine , Animal Welfare , Animals , Animals, Domestic , Benchmarking , Cattle , Humans , Meat/standards , Teaching/methods , Workforce
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