The first category, Adaptive Interaction, refers to adaptations that take place at the system’s interface and are intended to facilitate or support the user’s interaction with the system, without, however, modifying in any way the learning “content” itself. Examples of adaptations at this level include: the employment of alternative graphical or colour schemes, font sizes, etc., to accommodate user preferences, requirements or (dis-) abilities at the lexical (or physical) level of interaction; the reorganization or restructuring of interactive tasks at the syntactic level of interaction; or the adoption of alternative interaction metaphors at the semantic level of interaction. Although interface adaptations can be thought of as generally independent from the material or “content” delivered through a learning environment, this is not usually the case with learning activities - the major differentiating factor being the emphasis on ensuring and optimising “content” attainment in the former case, versus the emphasis on supporting a process in the case of activities. The dependency of learning activities on interface adaptations is a natural consequence of the fact that the interface encapsulates the very “tools” for carrying out an activity, be it interpersonal communication, collaboration towards problem-solving, etc.
The second category, Adaptive Course Delivery, constitutes the most common and widely used collection of adaptation techniques applied in learning environments today. In particular, the term is used to refer to adaptations that are intended to tailor a course (or, in some cases, a series of courses) to the individual learner. The intention is to optimise the “fit” between course contents and user characteristics / requirements, so that the “optimal” learning result is obtained, while, in concert, the time and interactions expended on a course are brought to a “minimum”. In addition to time and effort economy, major factors behind the adoption of adaptive techniques in this context include: compensating for the lack of a human tutor (who is capable of assessing learner capacity, goals, etc., and advising on individualized “curricula”), improving subjective evaluation of courses by learners, etc. The most typical examples of adaptations in this category are: dynamic course (re-)structuring; adaptive navigation support; and, adaptive selection of alternative (fragments of) course material (Brusilovsky, 2001).
The third category, Content Discovery and Assembly, refers to the application of adaptive techniques in the discovery and assembly of learning material / “content” from potentially distributed sources / repositories. The adaptive component of this process lies with the utilization of adaptation-oriented models and knowledge about users typically derived from monitoring, both of which are not available to non-adaptive systems that engage in the same process. At this point, we would like to make an explicit distinction between the perspective of the individual learner wishing to locate relevant material within a (possibly constrained) corpus, and the perspective of the author or “aggregator” who undertakes the task of putting together a course from existing materials and targeting a specific audience – or, seen differently, collecting and tailoring material for accommodating specific user / context characteristics. Although adaptation may very well be suitable in both perspectives, in the context of this paper we will be focusing on the first one, i.e., the assembly and contextualisation of material that is intended for an individual learner. This allows us to consider the more complex scenaria that emerge when one’s personal learning and interaction history can be utilized to infer criteria for content selection and processing.
The fourth and final category, Adaptive Collaboration Support, is intended to capture adaptive support in learning processes that involve communication between multiple persons (and, therefore, social interaction), and, potentially, collaboration towards common objectives. This is an important dimension to be considered as we are moving away from “isolationist” approaches to learning, which are at odds with what modern learning theory increasingly emphasizes: the importance of collaboration, cooperative learning, communities of learners, social negotiation, and apprenticeship in learning (Wiley, 2003). Adaptive techniques can be used in this direction to facilitate the communication / collaboration process, ensure a good match between collaborators, etc.
The second category, Adaptive Course Delivery, constitutes the most common and widely used collection of adaptation techniques applied in learning environments today. In particular, the term is used to refer to adaptations that are intended to tailor a course (or, in some cases, a series of courses) to the individual learner. The intention is to optimise the “fit” between course contents and user characteristics / requirements, so that the “optimal” learning result is obtained, while, in concert, the time and interactions expended on a course are brought to a “minimum”. In addition to time and effort economy, major factors behind the adoption of adaptive techniques in this context include: compensating for the lack of a human tutor (who is capable of assessing learner capacity, goals, etc., and advising on individualized “curricula”), improving subjective evaluation of courses by learners, etc. The most typical examples of adaptations in this category are: dynamic course (re-)structuring; adaptive navigation support; and, adaptive selection of alternative (fragments of) course material (Brusilovsky, 2001).
The third category, Content Discovery and Assembly, refers to the application of adaptive techniques in the discovery and assembly of learning material / “content” from potentially distributed sources / repositories. The adaptive component of this process lies with the utilization of adaptation-oriented models and knowledge about users typically derived from monitoring, both of which are not available to non-adaptive systems that engage in the same process. At this point, we would like to make an explicit distinction between the perspective of the individual learner wishing to locate relevant material within a (possibly constrained) corpus, and the perspective of the author or “aggregator” who undertakes the task of putting together a course from existing materials and targeting a specific audience – or, seen differently, collecting and tailoring material for accommodating specific user / context characteristics. Although adaptation may very well be suitable in both perspectives, in the context of this paper we will be focusing on the first one, i.e., the assembly and contextualisation of material that is intended for an individual learner. This allows us to consider the more complex scenaria that emerge when one’s personal learning and interaction history can be utilized to infer criteria for content selection and processing.
The fourth and final category, Adaptive Collaboration Support, is intended to capture adaptive support in learning processes that involve communication between multiple persons (and, therefore, social interaction), and, potentially, collaboration towards common objectives. This is an important dimension to be considered as we are moving away from “isolationist” approaches to learning, which are at odds with what modern learning theory increasingly emphasizes: the importance of collaboration, cooperative learning, communities of learners, social negotiation, and apprenticeship in learning (Wiley, 2003). Adaptive techniques can be used in this direction to facilitate the communication / collaboration process, ensure a good match between collaborators, etc.
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