Framework for Context-Aware Mobile Learning

情境感知移动学习是下一代智能电子学习系统的重要要求。然而，现实世界应用中的上下文管理是一项复杂的信息处理任务。在本研究计划中，情景反映了在整个企业生态系统中培养普及性学习的及时性和移动性。其目的是在学习者主导的背景下，在学习者的时间表上，随时随地动态地提供有用的学习资源。为了使组织能够将学习转变为战略杠杆，这对企业学习提供商尤其重要。随着学习材料的扩展和更长的教学时间变得普遍，知识的获取变得依赖于时间，并且由于当今知识经济要求的巨大变化，知识的获得越来越多地在动态中获得。然而，向移动学习者推断、交流和呈现情景感知学习资源的过程给研究界带来了新的挑战。这主要是由于移动技术的局限性(即无线网络上的有限带宽和移动设备上的有限资源)，以及缺乏认知移动学习模型(即与领域知识表示和上下文信息检索、时间限制的教学和人机交互有关的问题)。本研究计划利用语义网理论、电子学习标准化和移动计算的进展，为解决认知移动学习中的一些具有挑战性的问题做出贡献。该方法是开发一个基于本体论公式的以知识为中心的框架，将知识组织成有意义的内容，并创建一个环境，在该环境中，在对等学习对象库中漫游的软件代理可以容易地执行复杂的学习服务发现和组合。本体的使用旨在提供定制的学习模式，这些模式根据学习者的需求和可用的学习时间，按需交付给学习者和/或与其他模式组合，形成一条自我调整的学习路径。

Context-aware mobile learning is an important requirement for next generation intelligent e-learning systems. However, context-management in real world applications is a complex information processing task. In this research program, context reflects timeliness and mobility to nurture pervasive learning throughout an enterprise ecosystem. The aim is to dynamically provide useful learning resources on demand, anywhere, in a learner-driven context and on a learner's schedule. This is particularly important for corporate learning providers in order to make it possible for organizations to transform learning into a strategic lever. As learning material scale up and longer instruction times become common, knowledge acquisition become time-dependent and is increasingly acquired on the fly due to considerable changes in today's know-how economy requirements. However, the process of inferring, communicating, and presenting context-aware learning resources to mobile learners poses new challenges to the research community. This is mainly due to the limitations of mobile technology (i.e. limited bandwidth on wireless networks, and limited resources on mobile devices), and to the lack of cognitive mobile-learning models (i.e. problems related to domain-knowledge representation and contextual information retrieval, time constrained instruction, and human-computer interaction). This research program contributes towards solving some of the challenging problems in cognitive mobile-learning by making use of the progress in Semantic Web theory, e-learning standardization, and mobile computing. The approach is to develop a knowledge-centered framework based on ontological formulation that structures knowledge into meaningful content and creates an environment where software agents roaming around peer-to-peer learning object repositories can readily carry out sophisticated learning services discovery and compositions. The use of ontology aims at providing customized learning patterns which are delivered on-demand to the learner and/or combined with other patterns to form a self-adjusted learning route according to the learner's needs and available learning time.