Multimedia based student-teacher smart interaction framework using multi-agents in eLearning

• Published in: Multimedia tools and applications Vol. 77; no. 4; pp. 5003 - 5026
• Main Authors: Iqbal, Muhammad Munwar, Saleem, Yasir, Naseer, Kashif, Kim, Mucheol
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.02.2018; Springer Nature B.V
• Subjects: Animation; Computer Communication Networks; Computer Science; Data management; Data mining; Data Structures and Information Theory; Distance learning; Learning curves; Machine learning; Multimedia; Multimedia Information Systems; On-line systems; Online instruction; Special Purpose and Application-Based Systems; Students; Teachers; Unstructured data; Virtual environments; Multimedia data; Text mining; eLearning; Multimedia application; Machine learning
• ISSN: 1380-7501; 1573-7721
• DOI: 10.1007/s11042-017-4615-z

Multimedia content comprises the graphics, audio & video clips, animation and text to present learning materials in a style, which improves learner expectation in eLearning paradigm. Electronic learning gained the popularity due to its immense coverage of students and subjects all over the world. The aim of this study is enhancements using agent-based framework through multimedia data in eLearning paradigm. Analysis of multimedia contents and eLearning data are helpful for the course designers, teachers, and administrators of eLearning environments to hunt for undetected patterns and underlying data in learning processes. This research improves the learning curves for the students. It also needs to improve the overall processes in eLearning paradigm. Information and Communication Technologies supported education, and virtual classrooms environments are mandatory. In eLearning data is evolving day by day that includes the semi-structured data, unstructured data, and structured data which is also collectively marked as multimedia big data. Multimedia data has the potential to mining for the analytics and learning. The learning outcomes for the students are very important to find the facts that what impacts the input data on the student. There are 1108 students posted questions in online Learning Management System (LMS) and instructors reply these queries. Sensor data is also gathered by the mobile GPS to find the student location. The system has analyzed the relevance of the replied answers. The student satisfaction is achieved by providing the multimedia-based student-teacher interaction. This can lead to synchronous communication and multimedia content conversation in eLearning paradigm. Machine learning techniques are applied to that data to discover the patterns and behavioral trends. It can also be used in the eLearning environments for the teacher to assist and enhance the pedagogical skills and for student’s learning curve enhancements.