Jennifer Richardson

This paper reports ongoing development research into ways that ICT can be used to enhance distance education materials in image-based subjects. The work has been focussed around a unit of study called Veterinary Diagnostic Imaging, where Master 19s students learn to acquire, read and make diagnoses from radiographs and ultrasound images. ICT was used in five ways in this work: digital interactive images in QTVR format; interactive self-tests implemented in Microsoft Word; submission of assignments through WebCT; asynchronous discussion of problems using WebCT; and a synchronous electronic whiteboard developed using the Macromedia Shockwave multi-user server. A plan was developed to formatively evaluate each tool, and determine its usability and potential improvements. In the body of the paper, each tool is described, and evaluation evidence is discussed. Overall, the use of ICT was found to be effective for students. However, there is still scope for a number of improvements.

This paper reports on the preparation of a technology-mediated alternative to print-based external study of a postgraduate unit in veterinary diagnostic imaging. A number of innovative uses of technology had to be developed in order to meet the educational requirements. Large radiograph images were converted into QuickTime VR format, which enabled them to be zoomed into and navigated, with significant savings in file size. An electronic whiteboard was developed using multi-user ShockWave, which enabled users to share and annotate QTVR images across the internet, while still retaining the QTVR navigation functions. A FileMaker Pro database was used to maintain details of images and associated clinical information. Finally, web pages were generated from the database as interactive case studies, delivered on CD. The paper outlines how these technologies are linked together in new ways to meet the learning needs of students.

The result of the project described in this paper is an innovative use of Quicktime Virtual Reality (QTVR) for display and manipulation of veterinary radiographs and ultrasound images, within a database developed for use in the Veterinary Diagnostic Imaging unit of the Master of Veterinary Studies at Murdoch University. One of the aims of this project was to find an alternative for the bulky sets of radiographs used by external students for their case-based coursework and assessment activities. The QTVR solution provides a means by which students can move and zoom within images, resize images and compare images side-byside. QTVR also allows important areas of images to be highlighted by hotspots, allowing annotation of images, which is helpful for assisting external students. Some of the priorities of this project were to maintain the detail and the depth of the hard copy radiographs in the QTVR images, to simulate the problem-solving process used in reading radiographs, and to improve the learning outcomes by highlighting and annotating important areas of images. It was hoped that this solution would provide a more cost-effective and convenient method of delivery of large numbers of images to external students. In the subsequent cost-benefit analysis, it was found that the innovation described here offers many economic advantages to the School of Veterinary Clinical Science.