Graduate programs have placed an increasing emphasis on the importance of interdisciplinary education, but barriers to interdisciplinary training still remain. We present a new model for interdisciplinary, cross-institution graduate teaching that combines the best of local teaching, distance learning, and experiential learning to provide students and faculty with a unique collaborative learning experience and interdisciplinary research skills. We summarize the lessons learned from a highly successful implementation of this course model in the new field of landscape genetics, which integrates concepts and methods from population genetics, landscape ecology, and spatial statistics. The distributed nature of the course allowed sections to be offered locally that would not have been offered otherwise because of the lack of complementary expertise at local institutions. Students gained hands-on experience in interdisciplinary, Web-based and international research collaboration with group projects. A final synthesis meeting was invaluable for course assessment, manuscript development for group projects, and professional networking.
End of preview. The entire article is 7 pages. To view the full-text, please rent this article to continue.
/lp/university-of-california-press/developing-an-interdisciplinary-distributed-graduate-course-for-twenty-ema0hh3hCb
Welcome to DeepDyve! Rent Premier Research Articles and Save Up to 90%
Developing an Interdisciplinary, Distributed Graduate Course for Twenty-First Century Scientists
Follow BioScience
, Volume 62 (2)
University of California Press – Feb 1, 2012
More Info
More Like This Article
View All dataSource[]=actageo&dataSource[]=aspet&dataSource[]=aaos&dataSource[]=aacc&dataSource[]=aacr&dataSource[]=aea&dataSource[]=aip&dataSource[]=ajnr&dataSource[]=ams&dataSource[]=aps_physical&dataSource[]=appi_book&dataSource[]=appi_journal&dataSource[]=apha&dataSource[]=asip&dataSource[]=asm&dataSource[]=asn&dataSource[]=aspb&dataSource[]=avs&dataSource[]=annual_reviews&dataSource[]=arxiv&dataSource[]=acm&dataSource[]=berghahn&dataSource[]=cabi&dataSource[]=clinical_trials&dataSource[]=dailymed&dataSource[]=degruyter&dataSource[]=du_press&dataSource[]=esa&dataSource[]=eu_press&dataSource[]=elsevier&dataSource[]=emerald&dataSource[]=ejtr&dataSource[]=emea&dataSource[]=epo&dataSource[]=faseb&dataSource[]=gsa&dataSource[]=health_affairs&dataSource[]=hindawi&dataSource[]=imanager&dataSource[]=imedpub&dataSource[]=informa_healthcare&dataSource[]=informs&dataSource[]=iop&dataSource[]=iucr&dataSource[]=iospress&dataSource[]=jbjs&dataSource[]=leftcoast&dataSource[]=lu_press&dataSource[]=mesharpe&dataSource[]=mary_ann_liebert&dataSource[]=medline&dataSource[]=mit_press&dataSource[]=nature&dataSource[]=oxford&dataSource[]=pier_professional&dataSource[]=pnas&dataSource[]=portlandpress&dataSource[]=psyc_articles&dataSource[]=psyc_books&dataSource[]=psyc_critiques&dataSource[]=plos_journal&dataSource[]=pubmed_central&dataSource[]=rsna&dataSource[]=rockefeller&dataSource[]=rcn&dataSource[]=ria&dataSource[]=rsc&dataSource[]=sage&dataSource[]=spie&dataSource[]=springer_journal&dataSource[]=springer&dataSource[]=taylor_francis&dataSource[]=aps&dataSource[]=the_scientist&dataSource[]=uc_press&dataSource[]=uspto_abstract&dataSource[]=wiley&dataSource[]=pct
© 2012 DeepDyve, Inc. All rights reserved.
Terms of Service | Privacy Policy
