Towards feedback personalization in mobile assessment based on semantic web

Abstract

Feedback is a crucial component of the assessment process in mobile learning environments, simply because it can be used by the learner to bridge the gap in his/her knowledge or to have an idea about his/her performance. In this paper we propose a personalized mobile feedback module based on semantic web technologies, it is responsible to provide the learner with personalized mobile feedback related to mobile self assessment. Our module is a component of the framework PMAF (Personalized Mobile Assessment Framework) that aims to provide personalized mobile assessment resources. The use of semantic web technologies is explained with the feature of ensuring data interoperability and reuse of mobile feedback resources. In addition, an investigation for the enhancement of the defined feedback in IMS/QTI specification is presented. In our approach, a personalized mobile feedback module based on web services uses the learner's information stored in his/her e-portfolio to continuously suggest the most appropriate and personalized feedback in a particular field of knowledge to ensure the achievement of learning goals.