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.
Assessment has always been a very important step in the learning process. The use of mobile devices for assessment makes possible the creation of new types of assessment activities. MobiSWAP (Mobile Semantic Web Assessment Personalization) system provides mobile self-assessment resources considering contextual information. Mobile self-assessment offers ubiquitous access to testing material anytime and anyplace. It has the potential to complement and to enhance other assessment delivery modes (i.e. paper-and-pencil based assessment and computer-based assessment). However, the effective development of a mobile self-assessment depends essentially on students’ acceptance. The research purpose aims to build a model that demonstrates the factors that affect university students’ intention to use a mobile self-assessment. An experiment study was conducted with 40 university students enrolled in an Object Oriented Programing course. Experiment’s results help to derive the factors that influence the use of self-assessment in mobile environment. The proposed model, Mobile Self-Assessment Acceptance Model (MSAAM) combines two theoretical frameworks: Technology Acceptance Model (TAM) and Self-Determination Theory of Motivation (SDT). Partial Least Squares (PLS) was used to test the measurement and the structural model. Results indicate that Perceived Ease of Use and Attitudes Towards Use have a direct effect on mobile self-assessment Intention to Use. Perceived Usefulness, Competency, Autonomy and Relatedness have only indirect effects. The study confirms Technology Acceptance Model and showed that Self Determination Theory can be useful in predicting students’ acceptance in the context of mobile self-assessment.
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