Adaptive e-Learning in Knowledge Grid Environment
نویسندگان
چکیده
Knowledge Grid is a platform that enables uniform and effective knowledge sharing and management across the Internet. Based on it, this paper proposes an adaptive e-Learning in China Knowledge Grid environment (CKG-AL for short), which supports the learner-centered, highly interactive and on-demand eLearning with dynamic courseware construction. By incorporating ontology-based metadata for knowledge representation, learning objects for courseware construction and semantic link network for knowledge interconnection, CKG-AL can separate learning materials from its contents, which would in turn improves the efficiency and effectiveness for constructing and reusing courseware, and provides the basis for adaptive learning. By absorbing the ontology and intelligent agent technologies, CKG-AL constructs four level Knowledge Nets to support adaptive eLearning, namely, KGDomain Knowledge Net, KGCourse Knowledge Net, KGTutor Knowledge Net, and KGLearner Knowledge Net, which are respectively corresponding to domain concept, course materials, learner static model, and learner dynamic model.
منابع مشابه
Adaptive Knowledge Services Based on Grid Architecture
Grid Technology has proven to be a suitable means for the efficient sharing of various resources within a well–defined community. The EC–funded projects LeGE–WG and e–LeGI have set out to apply this technology for technology enhanced learning services. Previously, the applicability of distributed skill maps for adaptive e–Learning within a grid network has been discussed. In this paper, we prop...
متن کاملAn Adaptive Personalized E-learning Model Based on Agent Technology
Due to overall popularity of the Internet, E-learning has become a lot methods of learning in recent years. Through the Internet, learners can freely absorb new knowledge without the restriction of time and place. Based on individual difference of learner’s abilities and preferred learning styles in hypermedia environment, the learning outcomes vary essentially. Meanwhile, with the development ...
متن کاملMini/Micro-Grid Adaptive Voltage and Frequency Stability Enhancement Using Q-learning Mechanism
This paper develops an adaptive control method for controlling frequency and voltage of an islanded mini/micro grid (M/µG) using reinforcement learning method. Reinforcement learning (RL) is one of the branches of the machine learning, which is the main solution method of Markov decision process (MDPs). Among the several solution methods of RL, the Q-learning method is used for solving RL in th...
متن کاملA Novel Type-2 Adaptive Neuro Fuzzy Inference System Classifier for Modelling Uncertainty in Prediction of Air Pollution Disaster (RESEARCH NOTE)
Type-2 fuzzy set theory is one of the most powerful tools for dealing with the uncertainty and imperfection in dynamic and complex environments. The applications of type-2 fuzzy sets and soft computing methods are rapidly emerging in the ecological fields such as air pollution and weather prediction. The air pollution problem is a major public health problem in many cities of the world. Predict...
متن کاملCase study of virtual organization learning and knowledge testing environments Case study of virtual organization learning and knowledge testing environments
The proposed web-based knowledge assessment is based on flexible educational model and allows to implement adaptive control of learning process as well as to implement knowledge testing environment according to the requirements of student’s knowledge level, their personal abilities and his subject learning history. The learner knowledge model can be constructed as a sub graph of the global know...
متن کامل