JISC

Start date: 1 May 2001

End date: 30 April 2003

Funding programme: Learning and Teaching (5/99) programme

Project website: http://www.filter.ac.uk/

This project is part of the images project cluster in this particular programme. The main focus for projects in this cluster is on the creation and use of still image collections for learning and teaching.

Background

Digital images have a rich potential as learning and teaching resources and are currently under utilised in the support of pedagogical activities. The FILTER project aims to address this under use and encourage uptake of visual resources by mapping different types of images and defining the ways in which those images can be used to enhance the learning and teaching process. These categorisations will form the basis of the main project deliverables: a generic image dataset; a set of subject specific image datasets; and supporting documentation such as “How-to” guides and case studies.

Aims and Objectives

The overall project aim is to enable the use of digital image datasets to support learning and teaching and to facilitate the integration of image resources with pedagogical practice. The project will focus on developing and promoting a better understanding of image use in learning and teaching thereby empowering potential users to make more effective and appropriate use of images.

The project objectives are to:

• Define categories of images (eg 3D, photographic, graphical, schematic representation) in consultation with targeted focus groups; map the categories of images and outline the ways in which they can be used to support the learning and teaching process; and create a generic image set
• Develop a series of image datasets of subject specific images and build a suite of subject specific “How-to” guides and case studies on the use of images
• Develop standards and methods for providing descriptive, subject specific and learning and teaching related metadata that will enhance retrieval and ease-of-use of the datasets
• Provide an additional 10 datasets generated from a call to the wider HE community targeting image types which are currently under utilised and subject areas in which use of images is not common
• Collate the 16 datasets to form an exemplar database of images and their use in learning and teaching
• Disseminate all resources and existing good practice for the use of images in learning and teaching via the JISC-funded Technical Advisory Service for Images (TASI)

Project design

It is known that a high level of expertise in image use already exists in certain subject areas, but possibly using a limited range of image types. The FILTER project aims to enable, through working closely with a variety of Learning and Teaching Support Network (LTSN) Subject Centres (http://www.ltsn.ac.uk/) , a cross-fertilisation of this knowledge across subject disciplines ensuring multiple learning opportunities for all involved. This transferring of expertise will have a major role in the development of project deliverables. This approach will permit the identification and exploration of the factors of image use that are common to a number of subjects. The synthesis of this cross-domain knowledge sharing in the form of the exemplar database will ensure maximum benefit to the widest possible potential FE and HE user base. An important part of the project work is to identify, investigate and establish standards for issues underlying the creation and use of image databases: technical infrastructure; metadata schema; and best practice for image use.

Outcomes

The creation and delivery of more and more large digital image datasets via the Web provides the education community with potentially easy, quick and cheap access to high quality images for learning and teaching. To benefit from such resources, however, there is a need to ensure that the community knows how best to utilise fully the different image resources available and understands the nature of the primary factors currently hindering the use of images. FILTER project research will provide the education community with an understanding of what image resources are available and practical examples of how they are best incorporated with existing and any future learning materials.