1,132
Views
27
CrossRef citations to date
0
Altmetric
Original Articles

Student-Produced Podcasts as an Assessment Tool: An Example from Geomorphology

, , &
Pages 117-130 | Received 22 Oct 2010, Accepted 28 Mar 2011, Published online: 30 Aug 2011
 

Abstract

The emergence of user-friendly technologies has made podcasting an accessible learning tool in undergraduate teaching. In a geomorphology course, student-produced podcasts were used as part of the assessment in 2008–2010. Student groups constructed radio shows aimed at a general audience to interpret and communicate geomorphological data within the context of relevant social and environmental issues. Questionnaire results suggest that the novel format engaged students, and promoted group working, IT, language and oral communication skills, and a deeper understanding of the context of geomorphic data. For teachers, podcasting technology offers efficient teaching of oral communication, with opportunities for distance and self-directed learning.

Acknowledgements

David Harrison provided IT support and advice to students and staff involved in the project. Constructive comments from Ian Cook and three anonymous reviewers improved the paper. This project was supported by a UK Higher Education Funding Council Small Projects grant through the Geography, Earth and Environmental Sciences Subject Centre, and by a Northumbria University Applauding and Promoting Teaching Award.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 1,038.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.