In this paper we present our e-learning approach and describe the technical and instructional design of an adaptive learning environment. In order to avoid several reasons for distrust or frustration on the learner’s side, we developed an approach called configurable adaptation including the concept of individualized and adaptive learning paths. In cases where a course is offered in various (media) forms, the learner should be able to decide on its own, which one to use for the acquirement of the learning material. We demonstrate different approaches for a holistic learning experience using several learning scenarios like classroom participation and e-learning in a virtual learning environment. A special focus will be set on the description of the didactical paradigm synchronized blended learning, which allows the combination of different learning scenarios and the usage of learning material within all settings. Furthermore, we demonstrate examples how a (virtual) learning environment can be integrated into the course allowing dynamic and adaptive presentation of learning material as well as the direct inclusion of new – generated by algorithms or written by the learner or tutor – content on-the-fly.
Key Terms in this Chapter
Synchronized Blended Learning: The combination of different learning methods and didactical?concepts allowing the learner to select the most promising form of learning for a successful learning experience, whereas the choices have to be correlate on the fly.
Adaptive Learning System: Address the fact that individuals learn differently by adapting the presentation of learning content to meet the varying needs and learning preferences of different individual learners.
Learning Material Encoding: Describes in what format the content is internally stored (i.e., which standard is used). Even though semantic encoding belongs to this, the term encoding is generally used for the syntax.
Configurable Adaptation: Realized by means of so-called redundant learning objects. These objects can be described as alternatives, which differ in certain specific criteria and provide the opportunity to generate content pages on the fly to support different needs, learning styles, and strategies.
SmartFrame: The name of a virtual learning environment developed at the University of? Hamburg (http://www.smartframe.de).
Virtual Learning Environment: Can be (1) a learning scenario, (2) an application to provide access to the learning material over a network, or (3) a (Web-based) application to administrate the courses.
Content Pool: Stores the learning material in form of objects, their meta-data, as well as the relations between them. The content pool is either realized using a database or the file system.
Object Substitution: Describes the process that one object from a set is replaced by another one. For example, a?module from the learning material is built using individual objects of which a? certain image can be exchanged depending on the field of study of the learner.
Learning Material Presentation: How the learning material (i.e., the content) will be visualized from a (1) technical, (2) semantical, or (3) visual point?of view. (1) is about hard- and software used to transform the data for the visualization, (2) is about the choice of data, which needs to be shown, and (3) is about colors or fonts.
Meta-Data: Used to describe data using a standardized and well-structured format.
Authoring of Learning Material: The creation of learning material considering all characteristics like modular structure, meta-data, or composition.
Learning Scenarios: Describes the components influencing the learning experience of the learner. Examples for learning scenarios are classroom (a physical room where the teacher is presenting the material to the learners) or virtual learning environment (where the learner is using a computer to access the learning material).
Adaptive Learning Path: Allows to define individual paths through the learning material that consider individual characteristics of the learner.
Learner Types: A term describing the characteristics of learners defining specific categories.
Meta-Data Substitution: Describes the process that the meta-data of an object is completely or partly replaced by other elements.