An Information Visualisation Framework for Accessing Learning Objects Repositories Joris Klerkx, Michael Meire, Stefaan Ternier, Katrien Verbert, Erik Duval Dept. Computerwetenschappen, Katholieke Universiteit Leuven Celestijnenlaan 200A, B-3001 Heverlee, Belgium {joris.klerkx, stefaan.ternier, michael.meire, katrien.verbert, erik.duval}@cs.kuleuven.ac.be Abstract: In this paper, we discuss the use of Information Visualization techniques to improve the access to learning object repositories. We elaborate on a framework that was developed for this goal and on a prototype that was designed to enable users to access learning object repositories in a more flexible way than filling out electronic forms. In a second part, we present a case study in which we used the developed framework to visualize all the proceedings of the EdMedia. Users can use this application to find publications that were presented at the EdMedia conference over time. In the last part we try to elaborate on our ideas to visualize the internal components of learning objects and how we will try to visualize networks of interoperable learning object repositories. Introduction We would like to discuss the ongoing research of the use of Information Visualization techniques to improve the access to learning object repositories (LORs) in our research-group. Information visualization is the use of computer-supported interactive visual representations of abstract data to amplify cognition (Card, Mackinlay, Shneiderman 1999). We believe that applying information visualization techniques can enable users to find learning objects in learning object repositories in a more flexible and effective way than filling out electronic forms, which is the way it is currently done in repositories like Ariadne, Edna, Merlot, Nime & Edusource. First of all, we would like to report on the development of a prototype framework which uses information visualization techniques and aims to enable users to find learning objects in a LOR in a more flexible and effective way. This framework was developed with the requirement to be as extensible as possible. In the second part of this paper, we describe a case study that was created to be a proof-of-context of this requirement. This case-study consisted of the visualization of the proceedings of all EdMedia-conferences. The last part elaborates on ongoing research taking our research and our prototype a step further. Access to Learning Object Repositories In earlier work we described how we could use Information Visualization techniques to improve the access to learning object repositories (Klerkx, Duval, Meire 2004). In this work we presented the use of three information visualization techniques to visualize a complete LOR. These three techniques were tree-maps, hyperbolic trees and Venn-diagrams. This paper discusses how we took this work up to the next level and how we developed a framework and prototype which can be used to find learning resources in LORs. Basically the goal of our prototype is to enable an end user like a teacher or a student to zoom in on a relevant learning objects without requiring him or her to to go through a lengthy process of formulating complex search criteria, evaluating some of the results, refining the search criteria, etc (Duval, Hodgins 2003). We try to accomplish this goal by using Information Visualization techniques and by enabling end users to manipulate controls over the metadata, zoom in on potentially more relevant learning objects and continuously keep an overview of how additional search criteria restrict the remaining number of learning objects.

The prototype (Fig. 2) shows a screenshot of our prototype. The user interface of this prototype consists of three parts. The left part shows a visualization of the learning resources in the Ariadne Knowledge Pool System (KPS). In this figure, a tree-map is used to visualize the semantic hierachical classification of the learning object. A tree-map is a visualization of hierarchical structure that makes 100% use of the available display space. It maps the complete hierarchy onto a rectangular region in a space-filling manner (Shneiderman, Johnson 1991). The semantic hierarchical classification is based on the ARIADNE-metadata, which is an application profile of the Learning Object Metadata (LOM). A path of taxons represents the classification of each learning object in the metadata. For example a possible semantic classification of a learning object about the Fibonnaci numbers is formed by the taxon-path that is illustrated in (Fig. 1). Each classification-taxon is represented in the visualization as a grey rectangle (Fig. 2).
Science Type =>
Exact, Natural and Engineering Sciences
Main Discipline =>
Informatics/Information Processing
Sub Discipline => General/Sundry
Main Concept => Complexity of Algorithms Figure 1: Classification of a learning object about the Fibonacci Numbers In our earlier work (Klerkx, Duval, Meire 2004) we described the advantages of using such a tree-map visualization to visualize the LOR. Among those advantages are the insight they provide in the hierarchical classification and the overview they provide of the entire LOR.
Figure 2: Screenshot of the prototype. The left part consists of a tree-map visualization of all learning objects in the Ariadne LOR; the right part consists of some metadata controls and an information panel.