Abstract
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.
TopBackground
In the 17th century the ancient Italian term modello became famous in fine arts. In contrast to its former narrow sense, nowadays the term is part of everyday language. “Models can be developed based on natural artifacts or things, on hypotheses, on theories, or even based on pure fiction. The modern interpretation of model is: the object which is the result of a construction process” (Martens, in press). However, the broad usage of the notion of model makes it difficult to exactly define the term. Mueller summarizes: “Each definition of ‘model’ is insufficient: It covers only a small range of the reach of use” (Mueller, 2005). Accordingly, the aim of the following sketch is not to give a definition of the term model, but to describe some perspectives on models and characteristics of models. Model is a cross-disciplinary concept – moreover, most models are inherently crossdisciplinary. Generally, models have in common that they are abstractions and interpretations. A model abstracts parts of the real world, or it sketches something new, which did not exist before. The model is always a summary of the main aspects of an original, as it abstracts from special parts and only takes into account what can be perceived as the generalization. Mathematically spoken, a model is a subset of a set of originals. Thus, a model is also a simplification and a reduction on the parts which are the most important for the model developer. As a model is an interpretation, the modeler’s viewpoint, intention, and the purpose of the model also influence the model. A simple example might be the model of an ape—the designer of toy apes will use a completely different model of an ape than a scientist investigating ape behavior. Mueller (2005) describes the basic meaning of the term model as: “A model is a simplified part of reality or potentiality. It can be material or idealistic, graphic or abstract and describes a has-been, actual or future state”. Stachowiak (1973) has summarized this in the three main characteristics of models, which are representation, reduction, and pragmatics. The representation characteristic of a model means that each model represents an original. This does not mean that a model must have its counterpart in reality (or the physical world). The original of a model can also be an assumption, a hypothesis, a theory, or a product of fantasy. The reduction characteristic implies that the model’s attributes are a real subset of the attributes of the original. A model never comprises all attributes of the original. The pragmatic characteristic is that the model’s purpose is to replace the original in a certain context, for example, to answer questions, for investigations, experiments, or under certain conditions.
Key Terms in this Chapter
Educational Models: Abstract from real human behavior in teaching and training. They are related to pedagogical or educational research, and can represent theories of learning, pedagogic, and didactic. They are used for communication and system design at the educational level.
Models of the Application Domain: Abstract from real content, and provide structures and relations in the teaching and training field of the e-learning system. They are used to communicate about underlying content related knowledge structures in the application domain.
Models for E-Learning System Development: Abstract from programming and realization, provides for content and implementation independent descriptions, and is used for communication about technical aspects of the e-learning system. Included are standards, formal models, patterns, and software engineering models.
Descriptive Model: Depicts something existing. It reproduces or represents a part of the real world.
E-Learning System: Is in the context of this chapter focused on computer-based teaching and training systems. Usually, the term covers a broad range of systems and techniques which are used in educational settings, for example, Peer Help Systems, Teleteaching, virtual classrooms, to name but a few. A more detailed definition can be found in Kaplan-Leiserson (2002) .
Prescriptive Model: Describe something new, which does not exist before the model.
E-Learning: Electronically supported learning.
Transient Model: Starts as a descriptive model, which is performed to become prescriptive model.