Teacher-driven: web-based learning system

This paper reports a web-based platform-independent adaptive learning system dedicated to both students and teachers. For a student who uses the system, the content in the system is individually tailored toward his or her knowledge, which makes learning more personal, adaptive towards individual needs, and specialized. For a teacher, the system provides generic rule-based library to supervise students' learning. These rules enable teachers to choose different assessment, assignment, and learning strategies to be enforced automatically on students according to the teacher's selections and the student's performance. We believe that our system is an original and important contribution to supervised learning using web-based technologies, and future students will benefit from this new system.