Models are everywhere. Terms like “modeling” and “model” are part of everyday language. Even in research, no overall valid definition of what a model is exists. Different scientific fields work with different models. Usually, the term “model” is used intuitively to describe something which is sort of “abstract”. This is a rather vague concept, but all models have in common that they are abstractions in a broad sense and that they are developed for a certain purpose, for example, for testing and investigating parts of reality, theories or hypotheses, for communication, or for reuse. In e-learning the notion of models is frequently used in a rather naive and uncritical way. The main purpose of developing models seems to be lost in the overwhelming amount of available models. A situation has emerged where the development of a new special purpose model often seems to be much easier than the reuse, validation, or revision of existing ones. In the following section approaches to define the term “model” will be sketched to provide a (historical) background in relation with computer science. Afterwards, an overview over existing models and different approaches to categorize e-learning models will be given. A future trend suggests a new categorization of e-learning models. The chapter closes with a conclusion.
Towards automated assessment generation in e-learning systems using combinatorial testing and Formal Concept Analysis
