Learner typing for electronic learning systems

e-Learning systems will provide new pathways to knowledge and skills acquisition. To increase their quality using a parametric learner model is proposed. Tailoring the learning material presented to the respective parameter values may fit this material to the actual learner´s needs. We use a stereotype user model. Our learner characteristics complement the IMS UP. We first represent learners by points in a learner space. Then we propose increasingly generic ways of grouping together such points to form learner types. The less generic one models learner types using convex regions in the learner space. The more generic one models learner types using characteristic functions. While the latter approach allows for more flexible learner type combination the former approach allows for convincing definition of initial learner types. Combining both approaches thus may result in a reasonable number of useful learner types.