Injecting intelligence into learning management systems: The case of adaptive grain-size instruction

Abstract

Learning management systems have been widely used for managing the learning material and providing assessments to students. However, so far, they fail to offer intelligence and adaptivity in their diagnostic and reasoning mechanisms. In view of the above, this paper presents a novel and smart Learning Management System for tutoring the programming language Java. Our system performs diagnosis of students’ misconceptions based on their syntax and logical programming mistakes. It also takes as input their learning style which is based on the VARK model (Visual-Auditory-Read/Write-Kinesthetic Learner) in order to provide adaptive grain-size instruction to them. “Grain-size” instruction refers to the level of detail of the domain knowledge that a tutoring system provides to students. As such, the adaptive grain-size domain knowledge delivery corresponds to the knowledge levels and needs of the students. The evaluation was conducted using an established framework and student’s t-test and the results of the system show a high level of acceptance of the presented model.