Instructor guided personalization of learning path adopting SCORM

The growing interest in e-learning seems to be coming from several directions influencing traditional classroom to distant learning around the world. The advancements in web technologies motivated the personalized learning, pressurizing for a more personalized course for individuals. The driving components of a personalized course are the course structure and the learning content. This paper highlights the research carried out in designing a personalized course. Prior knowledge and learning styles are the two major parameters considered here for personalizing a course. Also the paper considers majorly on Sharable Content Object Reference Model (SCORM) conformance of the personalized courses, encouraging re-usability and interoperability of the courses across multiple learning systems. The main theme of the paper is to propose a system that guides an instructor to understand and provide personalized course path including learning content, activities etc. The proposed system reduces the time and burden of the instructor by considering the group of learners rather than individuals, achieved through clustering the groups based on their similar learning styles, which represents a traditional teaching model applied by the instructors.