A Concept for an Intelligent Tutoring System to, Support Individual Learning Paths in Software Development Courses

Abstract

Freshmen students of computer science usually are a highly heterogeneous set, especially regarding their initial programming skills, which range from none to professional. As well, students are unequally equipped with essential base competencies, and differ in their respective pace of learning and the amount of practice they need to get new skills under their belt. As a consequence, every student requires an individual learning path to meet his or her specific needs. To ensure an efficient learning progress, it is crucial to select additional exercises for the students’ self-study phases appropriately, so that they really meet the individual student’s current need. Therefore, we developed a concept and implemented a prototype for a tutoring system that supports individual learning paths by providing each student with exercises that specifically address his or her specific needs and take existing skills and competencies into account.