User Adaptation in Supporting Exploration Tasks in Virtual Learning Environments
In the increasing heterogeneous student population in both the academic and corporate training environments, the need of a customized instructional design is becoming more and more obvious. There are a variety of factors, including the past experience, cognitive abilities, and personal preference, that could influence the knowledge transfer, acquisition, and construction during the learning process.
The ideal learning environment described by Gilbert and Han (1999) consists of many (or more exactly “infinite”) instructors, each having their unique teaching styles, available for every learners where the learners could choose the instructor that perfectly matches their own learning styles. Forbus and Feltovich (2001) even added that the instructors or assistants should be at every learner’s elbow whenever they are ready to learn, and for however long it takes. Aptitude-Treatment Interaction theory (Cronbach & Snow, 1989) also suggests that the best learning results when the instruction matches the learner’s aptitude.
Virtual learning environments (VLEs), which are defined in the context of our research as sets of computer/internet-based tools created to enhance learners’ learning experiences, attempt to provide individualized instruction by means of customizing the domain content and appearance of the learning environment, hence matching the instruction to the learner’s attributes. In the VLEs, customization could be within users’ control (adaptable), or achieved without users’ intervention (adaptive). Nonetheless, the generalized term “adaptivity” supersedes both of them and is used to cover the idea in the following discussion. Systems equipped with adaptivity have been proven more effective and efficient than traditional nonadaptive systems (De Bra et al., 1999). Sampson et al. (2002) provide an extensive discussion and examples of VLEs that are built with the idea of adaptivity.
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