Figure 2 Concept structure (a) and structure on activities (b)
Related Figures (4)
rable 1 The six categories of cognitive processes igure 1 Example of a prerequisite relation on a set of problems Q illustrated as a Hasse diagram (a) and corresponding knowledge structure (b) with the dashed arrows representing a possible learning path Figure 3. Example of the prerequisite relation induced by the structures shown in Figure 2 If learning objectives are formulated at the level of skills, and skills are associated with the problems and learning objects of a knowledge domain, it can easily be assessed whether the respective learning objectives have been achieved by learners. This may provide the basis for identifying the gaps that are to be filled, by devising a personalised learning path. Moreover, the association of skills to a sound taxonomy may also provide a method for describing skills in an aggregated form. In the next section the practical implications for using taxonomies and a skill characterisation, as outlined above, within a virtual learning environment will be outlined. For illustrating this information at a glance, histograms or pie charts seem to be favourable. In the diagram shown in Figure 4, each slice corresponds to one category of the taxonomy (i.e., skill level, remember, understand, apply, etc.). The fraction per slice shows how many of the available skills per category have already been covered by a teacher or achieved by a learner. For example, according to Figure 4, a learner has achieved six out of a total of eight skills that are associated with the first level (Ze., remember) of the taxonomy and three out of the five skills that are contained in the category apply. The information on the skills can be provided either for a particular concept, closely interrelated concepts, or even a whole UoL. In each case the aim is to increase the number of covered and/or achieved skills for each skill level of the taxonomy.
