Context Aware Mobile Learning Model Dadang Syarif SS
Context Aware Mobile Learning Model Dadang Syarif SS Lukito Edi Nugroho Ridi Ferdiana Paulus Insap Santosa Department of Electrical Engineering and Information Technology Faculty of Engineering, Universitas Gadjah Mada, Indonesia BACKGROUND AND OBJECTIVE • Enhancing and delivering learning paradigm has been shifted from traditional all-size type of learner to adaptive and personalized learning. • The emerging of ubiquitous computing has provided a significant opportunity for using a mobile technology as a learning medium. • There are limited researchers present a model of adaptive mobile learning for learners who are always traveling due to some context issues. The model proposed suitable knowledge for building a context-aware mobile learning. The model deals with some issues in term of mobile contexts, such as user contexts, physical and environments contexts. RELATED WORKS AND Proposed Methods Proposed Approach Related Works Zervas. , et. al, 2014 F. Ako-nai. , et. al, 2012 Wang and Wu, 2011 Presenting a context-aware mobile learning to transform the educational resources that can be personalized into a mobile player platform. Propose the 5 -R framework for mobile learning adaptation. The 5 -R deals and focuses on the 5 -Rights: location, device, time, learner, and contents. Applying context-aware technology and recommendation algorithm to personalize learning resources and materials using RFID Theoretical Background Mobile learning is a cutting-edge kind of learning process, utilizing mobile devices, reaching various digital educational resources and services, whenever, wherever. Mobile learning picks up and conducts a learning environment that can be assisted by the wireless technologies. The mobile learning purposed to occupy learners in learning process stimulated by individual situation and condition. Compared with the traditional learning methods, mobile learning has following features: mobility, real-time, interactive, virtualization, digitization, and personalization. Different with online learning, the mobile learning usually uses wireless communication technology, easy to move, easy to carry. However, it is influenced by the level of noise, quality of network and level of illumination. The process of adaptive and personalized context-aware mobile learning is a mechanism and steps to convey learner contextual information and kind of recommendations that can be produced accordingly. The previous concept, related works, tools and design model for context-aware adaptive and personalized mobile learning has been given suitable and proper foundation to be implemented in context-aware mobile learning for traveling learner. The concept of mobile learning gives basic knowledge and characteristics of mobile learning. Related works in mobile learning application show the state of the art about researchers in adaptive and personalized contextaware mobile learning, whereas recommender mobile applications in tourism gives inspirations, how the context-aware mobile learning implemented for travelers especially how to deal with the constraints of traveling situation contexts such as limited connectivity, noise, and illumination level. Design adaptation of context-aware mobile learning gives guidance and become tools to develop the proposed model. Information of Learner Context Adaptation Process (Adaptation Engine) Personalization of Mobile Learning Proposed Approach In the learner contextual information, the proposed model using learning styles, learning preferences, and time preference as learning context that is input by the learner. Location with GPS technology sensor is used as mobile context to detect nearest library and classmates location. As well as the Wi-Fi, noise and illumination sensor will be used by the system to select appropriate learning materials. In adaptation engine phase, adaptation rules such as condition structure rule based are implemented as the approach. In this phase, also are provided with library database, learner profiles, map services, GPS services and resources database. In the adaptation phase, some adaptation types are conducted. Selection adaptation type is used for presenting learning material recommendations based on learning style and learning preferences by dealing with the connectivity level (poor, good, strength), noise level, and illumination level. On the other hand, navigation to location, communication and interaction adaptation types are used for presenting library and nearest classmates’ location. Results The Proposed Model Simple Wireframe Design FUTURE WORK • In the future works, the model can be implemented and be tested in a real situation. • Various contexts, adaptation engine and personalization, included the user contexts can be considered in order fit with the learner condition.
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