Context-aware mobile learning on the semantic web / by Xiaoyun Zhang.

Progress made in Semantic Web technologies and Ubiquitous Computing has lead to the development of mobile learning services that can adapt to the learner's background, learner's needs, and surrounding environment. In particular, the emerging techniques from these two technologies have the potential to revolutionize the way mobile learning services available on the web are discovered, adapted, and delivered according to context. Context acquisition and management, conceptual knowledge modeling and reasoning, and adaptive services discovery are the main ingredients for designing such context-aware mobile learning systems. However, a number of challenges are still facing the research community in this field. These can be summarized in the following: (i) current mobile learning services act as passive components rather than active components that can be embedded with context awareness mechanisms, (ii) existing approaches for service composition neglect contextual information on surrounding environment, and (iii) lack of context modeling and reasoning techniques for integrating the various contextual features for better personalization. In this thesis an attempt is made to solve the above-mentioned problems. These challenges are addressed by proposing a personalized mobile learning system based on a global ontology space to aggregate and manage context information related to the learner, the used device, the surrounding environment, and the task at hand. The system adopts a unified reasoning mechanism, around the global ontology space, in order to adapt the learning sequence and the learning content based on the learner profile and the perceived contextual information. The adopted approach for ontology reasoning aims at achieving two types of adaptations--system-centric adaptation and--learner-centric adaptation. These are implemented on a Run-Time Environment that identifies new contextual changes and translates them into new adaptation constraints. We developed and tested our system on a number of subject-domain ontologies using various learning scenarios, and the obtained experimental results are very promising

Validation of Metacognitive Awareness Inventory in Academic Stage of Undergraduate Medical Education

Medical students are expected to improve critical thinking, clinical reasoning and problem solving skills. These cognitive attributes need to be supported with metacognitive skills. Students with better metacognitive ability will be able to synergize their learning with self-reflection strategies to achieve learning target. One of the tools to assess students’ metacognitive skills is Metacognition Awareness Inventory (MAI). This study is aimed to validate Indonesian MAI in the academic stage of undergraduate medical education and was done on May-June 2014 at faculty of medicine Universitas Malahayati Bandar Lampung. This study used cross-sectional design consisted of 3 stages: language adaptation, pilot study and validation study. Validation study involved 1200 medical students. Factor analysis was conducted to identify factors of MAI. Language adaptation and pilot study produced Indonesian MAI which contains the same number of items. There were 757 MAI questionnaires eligible for analysis. Extraction of the 51-item MAI using principal component analysis (PCA) produced 5 factors which were cognitive preparation, supervision, management, strategy and evaluation. The Cronbach alpha value for the whole Indonesian MAI was 0.904. Indonesian MAI complies to construct validity criteria, specifically content validity and internal consistency. MAI is useful as an instrument to assess metacognitive ability in the academic stage of undergraduate medical education

Sensory semantic user interfaces (SenSUI)

Rapid evolution of the World Wide Web with its underlying sources of data, knowledge, services and applications continually attempts to support a variety of users, with different backgrounds, requirements and capabilities. In such an environment, it is highly unlikely that a single user interface will prevail and be able to fulfill the requirements of each user adequately. Adaptive user interfaces are able to adapt information and application functionalities to the user context. In contrast, pervasive computing and sensor networks open new opportunities for context aware platforms, one that is able to improve user interface adaptation reacting to environmental and user sensors. Semantic web technologies and ontologies are able to capture sensor data and provide contextual information about the user, their actions, required applications and environment. This paper investigates the viability of an approach where semantic web technologies are used to maximize the efficacy of interface adaptation through the use of available ontology

Context-awareness for mobile sensing: a survey and future directions

The evolution of smartphones together with increasing computational power have empowered developers to create innovative context-aware applications for recognizing user related social and cognitive activities in any situation and at any location. The existence and awareness of the context provides the capability of being conscious of physical environments or situations around mobile device users. This allows network services to respond proactively and intelligently based on such awareness. The key idea behind context-aware applications is to encourage users to collect, analyze and share local sensory knowledge in the purpose for a large scale community use by creating a smart network. The desired network is capable of making autonomous logical decisions to actuate environmental objects, and also assist individuals. However, many open challenges remain, which are mostly arisen due to the middleware services provided in mobile devices have limited resources in terms of power, memory and bandwidth. Thus, it becomes critically important to study how the drawbacks can be elaborated and resolved, and at the same time better understand the opportunities for the research community to contribute to the context-awareness. To this end, this paper surveys the literature over the period of 1991-2014 from the emerging concepts to applications of context-awareness in mobile platforms by providing up-to-date research and future research directions. Moreover, it points out the challenges faced in this regard and enlighten them by proposing possible solutions

Agents for educational games and simulations

This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications