Undergraduate research internships: Veterinary students’ experiences and the relation with internship quality

Abstract

Background and aims: The learning environment of undergraduate research internships has received little attention, compared to postgraduate research training. This study investigates students’ experiences with research internships, particularly the quality of supervision, development of research skills, the intellectual and social climate, infrastructure support, and the clarity of goals and the relationship between the experiences and the quality of students’ research reports and their overall satisfaction with internships.

Method: A questionnaire (23 items, a 5-point Likert scale) was administered to 101 Year five veterinary students after completion of a research internship. Multiple linear regression analyses were conducted with quality of supervision, development of research skills, climate, infrastructure and clarity of goals as independent variables and the quality of students’ research reports and students’ overall satisfaction as dependent variables.

Results: The response rate was 79.2%. Students’ experiences are generally positive. Students’ experiences with the intellectual and social climate are significantly correlated with the quality of research reports whilst the quality of supervision is significantly correlated with both the quality of research reports and students’ overall satisfaction with the internship.

Conclusion: Both the quality of supervision and the climate are found to be crucial factors in students’ research learning and satisfaction with the internship.

Notes

Notes

1.  MGM reports on the percentage of observed variance that is explained by the tested item grouping and on the item-rest correlations after correction for test length and self-correlation. Based on the correlations of items with the sum scores of the clusters of items, it is possible to analyse whether items are in ‘the right cluster’, i.e. show high correlations with the pre-assigned cluster and low correlations with other clusters.

2.  In hierarchical regression independent variables are based on past work and the researcher decides in which order to enter these variables into the model. As a general rule, known independent variables (from other research) should be entered into the model first in order of their importance in predicting the outcome. After known variables have been entered, the researcher can add any new variables into the model (Field 2005).

Additional information

Notes on contributors

Debbie A. D. C. Jaarsma

DEBBIE (A.D.C.) JAARSMA, DVM, PhD is a veterinarian and assistant professor at the Faculty of Veterinary Medicine, Utrecht University, The Netherlands.

Arno M. M. Muijtjens

ARNO (A.M.M.) MUIJTJENS, MSc, PhD, is a statistician and associate professor in the Department of Educational Development and Research, Maastricht University, The Netherlands.

Diana H. J. M. Dolmans

DIANA (D.H.J.M.) DOLMANS, MSc, PhD, is an educational psychologist and associate professor in the Department of Educational Development and Research, Maastricht University, The Netherlands.

EVA M. Schuurmans

EVA (E.M.) SCHUURMANS, BSc, is a veterinary student at the Faculty of Veterinary Medicine, Utrecht University, The Netherlands.

Peter Van Beukelen

PETER VAN BEUKELEN, DVM, PhD, is a professor in quality improvement in veterinary medical education at the Faculty of Veterinary Medicine, Utrecht University, The Netherlands.

Albert J. J. A. Scherpbier

ALBERT (A.J.J.A.) SCHERPBIER, MD, PhD, is a professor in quality improvement in medical education and scientific director of the Institute for Education, Faculty Health, Medicine and Life Sciences, Maastricht University, The Netherlands.