<p class="Abstract"><span>A directed graph represents an accurate picture of course descriptions for online courses through computer-based implementation of various educational systems. E-learning and m-learning systems are modeled as a weighted, directed graph where each node represents a course unit. The Learning Path Graph (LPG) represents and describes the structure of domain knowledge, including the learning goals, and all other available learning paths. In this paper, we propose a system prototype that implements a propose adaptive learning path algorithms that uses the student’s information from their profile and their learning style in order to improve the students’ learning performances through an m-learning system that provides a suitable course content sequence in a personalized manner.</span></p>
<span>Sign languages are the most basic and natural form of languages which were used even before the evolution of spoken languages. These sign languages were developed using various sign "gestures" that are made using hand palm. Such gestures are called "hand gestures". Hand gestures are being widely used as an international assistive communication method for deaf people and many life aspects such as sports, traffic control and religious acts. However, the meanings of hand gestures vary among different civilization cultures. Therefore, because of the importance of understanding the meanings of hand gestures, this study presents a procedure whichcan translate such gestures into an annotated explanation. The proposed system implements image and video processing which are recently conceived as one of the most important technologies. The system initially, analyzes a classroom video as an input, and then extracts the vocabulary of twenty gestures. Various methods have been applied sequentially, namely: motion detection, RGB to HSV conversion, and noise removing using labeling algorithms. The extraction of hand parameters is determined by a K-NN algorithm to eventually determine the hand gesture and, hence showing their meanings. To estimate the performance of the proposed method, an experiment using a hand gesture database is performed. The results showed that the suggested method has an average recognition rate of 97%. </span>
Abstract-In this paper, we present a conceptual framework for using the Semantic Web to get student data from other educational institutions, enabling the educational institutions to communicate and exchange student data. Educational institutions could then use this information to adjust the students' profiles and modify their learning paths. Semantic Web will create a more personalized dynamic course for each student, according to his/her ability, educational level, and experience.Keywords-Adaptive Learning; dotNetRDF; Graphs; mLearning; Ontology; RDF; Semantic Web; Shortest Path; Turtle; User Profile. IntroductionThroughout the most recent decades, numerous research studies have examined the possibilities of changing the educational instruction model from the customary onesize-fits-all model to a more adaptive and customized learning model. Most of the techniques calculate the optimal learning path, based on the characteristics in the 16 http://www.i-jim.orgPaper-Updating Student Profiles in Adaptive Mobile Learning using ASP.net MVC, dotNetRDF,… student's profile to make the course more personalized. However, we have not seen any technique that updates profiles dynamically using the Semantic Web to exchange information between educational institutions. The student profile contains information about the student (such as first name, last name, address, course units that have been completed, and grades of those course units). "eLearning is learning utilizing electronic technologies to access educational curriculum outside of a traditional classroom. In most cases, it refers to a course, program, or degree delivered completely online." [1]. This current model can be applied to mobile learning and eLearning in community colleges, as well as, in a typical graduate or undergraduate program at the university level for any course. Students could benefit from and personalize their college experience and graduate earlier by completing their requirements. However, this model does not apply to K-12 students, because they are outside the scope of our research. Adaptive learning is an educational method that aids students in the learning process according to their needs. In addition, adaptive learning assists instructors in conveying course content to their students in a personalized manner based on the students' ability and background. Furthermore, from a developer's point of view, adaptive learning is a technique using computers and other resources to assist in producing a better learning experience. One of the most challenging tasks for adaptive mobile learning is to create an adaptive course. Several researchers have used different techniques in order to make the course adaptive in terms of the course content and units. To the best of our knowledge, there has been no research that attempts to make the course adaptive in terms of previously completed materials by the students at another educational institution by using the Semantic Web to communicate directly with various educational institutions' systems to acquire the ...
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