A Context-Aware Framework to Provide Personalized Mobile Assessment

In mobile learning environment, context-aware systems refer to applications that employs contextual information to provide appropriate services to the leaners or other applications to perform a specific task. An important challenge in such applications is context modeling, using ontologies to model context information and to reason about context at a semantic level has attracted a lot of interest in the research community. Semantic Web technologies have been applied in recent years with different purposes in education. But, their applications for generating useful personalized mobile assessment resources have not been researched enough so far.In this paper, we introduce a context-aware approach that makes use of Semantic Web technologies to support personalized assessment in mobile environments. We propose a Service-based framework for bringing assessment techniques to mobile environment. We provide a formal description for our mobile assessment framework and detail the functionalities of its various layers. We have carried out also an experiment with computer science university students to evaluate our mobile assessment framework

An associative neural network with emphasis on parallelism and modularity

Ph.D.James O. Hamble

A Context-aware Approach for Personalized Mobile Self-Assessment

Abstract: With the increasing development of mobile technologies, the learning environment is currently undergoing a major shift. Access to contextual information in a mobile learning environment aims to meet the needs of learning and assessment personalization according to various learners' profiles and a range of learning contexts. Semantic Web technologies have been applied in recent years with different purposes in education. But, their applications for generating useful personalized mobile assessment resources have not been researched enough so far. In this paper, an approach making use of semantic Web technologies to support personalized self-assessment in mobile environments is described. Assessment techniques are formalized with First Order Logic rules which allow to personalize assessment activities. We also propose an algorithm for semantic assessment resources retrieval. Finally, a Mobile Semantic Web Assessment Personalization system is presented. The qualitative and quantitative evaluation of the proposed system is also provided

A Context-aware Approach for Personalized Mobile Self-Assessment

With the increasing development of mobile technologies, the learning environment is currently undergoing a major shift. Access to contextual information in a mobile learning environment aims to meet the needs of learning and assessment personalization according to various learners' profiles and a range of learning contexts. Semantic Web technologies have been applied in recent years with different purposes in education. But, their applications for generating useful personalized mobile assessment resources have not been researched enough so far. In this paper, an approach making use of semantic Web technologies to support personalized self-assessment in mobile environments is described. Assessment techniques are formalized with First Order Logic rules which allow to personalize assessment activities. We also propose an algorithm for semantic assessment resources retrieval. Finally, a Mobile Semantic Web Assessment Personalization system is presented. The qualitative and quantitative evaluation of the proposed system is also provided

An Assessment Framework for eLearning in the Semantic Web

In this paper we present a flexible assessment framework for eLearning based on semantic web technologies. The assessment techniques are formalized as reasoning rules. These rules are able to reason over resources annotated with semantic web metadata formats and according to the standards LOM and IMS QTI. The framework is tested using TRIPLE, a rule-based language for the semantic web

Towards a Service Based Architecture for Assessment

In this paper we propose the outline of a service based architecture for bringing assessment techniques to open e-learning environments. We first describe a use case scenario for a generic assessment framework offering personalized assessment generation and then present its basic architecture as part of the Personal Reader Framework. The generic assessment framework enables the search for the appropriate assessment resources after checking the learner’s last saved performances and specific needs (e.g. language preferences, device requirements). In our assessment framework personalization functionalities are available as web services. The communication between these services is based on the Semanti

Suitability of UML4ODP for an Engineering Specification of a Distributed Environment for Teaching Embedded Systems

In this paper, we will contribute to an engineering specification of a distributed environment that will help to generate remote Lab work supports for teaching embedded systems. Our main objective is to show the appropriateness of adopting the ODPRM (Open Distributed Processing - Reference Model) model proposed by the ISO (International Organization for Standardization) to express the specification of our environment from an engineering point of view. By choosing the UML4ODP language that comprises all the ODP-RM concepts to express the specification of such point of view we will try to specify our environment as a distributed system composed of a set of objects and that support the necessary mechanisms and functions for their distributed interactions. Software architecture styles, such as SOA, MVC and N-tier, are considered in our engineering specification, since they are closely related to the distribution strategy. Keywords-- ODP-RM, UML4ODP, Distributed Environment, Remote lab work, Online laboratory

Short and Open Answer Question Assessment System based on Concept Maps

International audienceComputer Assisted Assessment of Short and open answers has established a great deal of work during the last years due to the need of evaluating the deep understanding of the lessons’ concepts by learners that, conferring to most teachers, cannot be done by simple MCQ testing. In this paper we have reviewed the techniques underpinned this system, the description of currently available systems for marking short and open text answer and finally proposed a system that would evaluate answers using Natural Language Processing and lastly compared the results obtain by human expert graders and proposed system. We have also compared the results of proposed system with some existing systems