3. Personalized Learning Personalized learning is the tailoring of pedagogy, curriculum and learning support to meet the needs and aspirations of individual learners. Data personalization [22] is to facilitate the expression of the need of a particular user to enable him to obtain relevant information when he accesses an information system. The data describing the user’s interests and preference is often gathered in the form of profile. One can identify business and /or ordinary customers, and monitors their behavioural profile over different providers through intelligent techniques [23]. Personalization [24] can also be achieved through navigate the documents of data sources, so that content is extracted from the Learning object repository. Following are the few methods of personalization. 3.1 Knowledge driven model for personalization E-learning solutions should be more than just a collection of technological solutions. Apart from sophisticated, stylish multimedia delivery, it should focus on enhancing the learning and intellectual interaction at the cognitive, behavioral, and physiological levels.
Another impediment to the successful adoption of Elearning is the lack of learning personalization. The learner-centric aspect of E-learning is often neglected. All the learner has to do is to simply follow the prescribed paths through the whole courseware (dictated SME’s subject matter experts) right from pre-assessment to postassessment. Another problem is that most of the courses are offered within the time frame of an academic semester, without consideration of the learners preferred pace and expertise. The future direction of E-learning is shifting from a content-oriented approach to a knowledge synthesis approach. Knowledge model [11] and concept map approach are used to enrich the learning experience by creating a platform to provide continuous dialogue between the learners and the knowledge resources. Concept maps are used as the graphical representations of knowledge to depict both the learning concepts and the salient relationships between them with a human oriented approach. The learning continuum models decide the type of knowledge structures and relationships within which Elearning content resources can be held. The system has been designed by using a modified concept map approach to model aspects of tacit knowledge into either business or technical processes or procedures. Tacit knowledge is highly subjective in nature, as it is developed by an individual based on his cognitive and conceptual models of external processes. Tacit knowledge exists randomly in society and is related to the context of a specific problem.
The Tacit(T)-model is used to capture the sequential set of steps, that a subject matter expert (SME) would treat to accomplish a task or to make a decision. Given a particular situation, the actions within a procedure are done the same way each time. A process T-model, on the other hand, is used to capture the “tacit” flow of events (seen through the eyes of the SME) that describes how something works. From the T-model, important conceptual structures among the data sets that are identified are restructured and formalized through the use of formal concept analysis (FCA).
Formal Concept Analysis (FCA) is a method of data analysis, knowledge representation, and information management, based on mathematical theory. FCA’s rich mathematical semantics are coupled with the modified concept map approach, and extend its application to Formal Concept Analysis (FCA) is a method of data analysis, knowledge representation, and information management, based on mathematical theory. FCA’s rich mathematical semantics are coupled with the modified
concept map approach, and extend its application to E- learning.
Explicit knowledge is the knowledge that is objective in nature, easily expressed and shared. Explicit knowledge is modeled in the subject domain master map (M-map) which can be hyper linked to each knowledge node in the T-map. The M-map is formulated on the concept of learning dependency, which is defined as a dynamic cognitive and pedagogical centered approach for the mapping of a course structure. It is devised from the fundamental principles underlying both cognitivist and constructivist theorems that place utmost emphasis on the internal mental processes of the learner’s mind and how it can be utilized to promote effective learning.
The essence of methodology lies in first extracting the tacit knowledge (usually part of the SMEs’ accumulated learning process) into a subjective T-map, where the proximity and connectivity of concepts provide the structure for effective ways of searching and viewing learning resources. The manifest of the T-map (nodes and relationships) is used to enable a more systematic and scientific understanding and learning process. With the Tmap and the M-map manifests, learning personalization can be executed using agent technologies. The former generates the exact learning paths that the learner must take to master a particular concept. The learning