549
Views
16
CrossRef citations to date
0
Altmetric
Articles

Virtual Field Sites: losses and gains in authenticity with semantic technologies

&
Pages 213-230 | Received 16 Jul 2011, Accepted 24 Feb 2012, Published online: 06 Jul 2012
 

Abstract

The authors investigate the potential of semantic web technologies to enhance ‘Virtual Fieldwork’ resources and learning activities in the Geosciences. They consider the difficulties inherent in the concept of Virtual Fieldwork and how these might be reconciled with the desire to provide students with ‘authentic’ tools for knowledge construction evident in existing Virtual Field Sites. Following the progress in design and use of Virtual Field Sites in one UK university, the authors investigate how emerging technologies might produce a shift in thinking about the nature and role of Virtual Field Sites from being primarily visual representation tools to sites for the development of skills necessary in practice. This would represent the integration of such online tools into an expanding and evolving set of discourses and practices, rather than replacing or contributing to the loss of traditional disciplinary activities such as the collection by students of their own field data.

Acknowledgements

The work reported in this paper was funded under ESRC/EPSRC Research Grant RES-139-25-0403 (‘Ensemble: Semantic Technologies for the Enhancement of Case Based Learning’), part of the Technology Enhanced Learning Programme. Further details are available at: http://www.ensemble.ac.uk.

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 327.00 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.