Smart Assistive Technologies (SAT) can be a powerful tool in supporting education environments and inclusion for learners with visual/hearing impairments. For example, while captions in videos are a necessity for deaf users, audio reading is inevitable for blind ones. Including such technologies into a smart e-learning environment provide huge opportunities to customize the content presentation to needs and ability of learners. Despite the number of models being introduced during the last decade, acceptance model and behavioral model are, yet, exhibiting design drawbacks for learners with visual and hearing impairments. Meanwhile, the e-learning initiatives in the universities have paid great efforts in order to optimize usability of conventional e-learning systems. However, optimizing assistive e-learning systems is not covered in the recent research. Central to e-learning optimization is the learners’ realization problem; in terms of the size of gap between learners’ expectations and real interaction measures. This paper presents a study of measure the usability of assistive e-learning systems and modeling better interaction based on adjusted Fitt’s Law to consider time of movement for assistive technologies embedded in e-learning systems. The proposed usability evaluation considers the hardness of mental operations during e-learning various activities.
In e-Iearning environments, collect data on users from their activities traces is crucial. It permits to improve the adaptation process and the development of pedagogical tools.Modeling users in e-Iearning environment is largely looked in research. Nevertheless, sharing and reusing user data jointly in different environments is yet overlooked. In this context, the question that arises is: How to update systematically different environments after activities performed by a user in a given environment?In this paper, we address this question and we propose a solution which updates systematically diverse models of different environments based on the activities performed by a user in a given environment.
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