A knowledge-based framework for e-learning in heterogeneous pervasive environments
نویسندگان
چکیده
We propose a ubiquitous learning approach useful not only to acquire knowledge in the traditional educational meaning, but also to solve cross-environment everyday problems. By formalizing user request and profile through logic-based knowledge representation languages, a lightweight but semantically meaningful matchmaking process is executed in order to retrieve the most suitable learning resources. Standard formats for distribution of learning objects is extended in a backward-compatible way to support semantic annotations in our framework. Framework and algorithms are absolutely general purpose, nevertheless an application has been developed where the semantic-based Bluetooth/RFID discovery protocols devised in previous work, support users –equipped with an handheld device– to discover in the environment learning objects for satisfying their needs.
منابع مشابه
Interfirm Alliance Interactions and knowledge Learning: A Conceptual Research Model
Alliance raises many knowledge transfer and interfirm learning issues that have implications for how the alliance partners manage their cooperative learning activities in the alliance system. Many of these implications are grounded in the assumption that partners in the alliances have routines for transferring knowledge, learning, gaining management efficiencies. Thus organisations can support ...
متن کاملA context-sensitive dynamic role-based access control model for pervasive computing environments
Resources and services are accessible in pervasive computing environments from anywhere and at any time. Also, due to ever-changing nature of such environments, the identity of users is unknown. However, users must be able to access the required resources based on their contexts. These and other similar complexities necessitate dynamic and context-aware access control models for such environmen...
متن کاملAdaptive Dynamic Data Placement Algorithm for Hadoop in Heterogeneous Environments
Hadoop MapReduce framework is an important distributed processing model for large-scale data intensive applications. The current Hadoop and the existing Hadoop distributed file system’s rack-aware data placement strategy in MapReduce in the homogeneous Hadoop cluster assume that each node in a cluster has the same computing capacity and a same workload is assigned to each node. Default Hadoop d...
متن کاملThe Collaborative Learning in the e-Learning Environments
Introduction: The collaborative learning and interactive electronic-learning (e- learning) is one of the key factors in education system success. This study examined the collaborative e-learning in the framework of constructivism theory. Methods: This is a review article. The databases such as Scientific Information Databases, Magiran, Science Direct, and Google Scholar were reviewed. Also,...
متن کاملHierarchical Functional Concepts for Knowledge Transfer among Reinforcement Learning Agents
This article introduces the notions of functional space and concept as a way of knowledge representation and abstraction for Reinforcement Learning agents. These definitions are used as a tool of knowledge transfer among agents. The agents are assumed to be heterogeneous; they have different state spaces but share a same dynamic, reward and action space. In other words, the agents are assumed t...
متن کامل