Design Adaptive Learning System Using Metacognitive Strategy Path for Learning in Classroom and Intelligent Tutoring Systems

Adaptive learning (AL) is a learning process focusing on students' personality through of recommendationbased learning and inquiry-based learning. This research intends to create a system capable of giving AL recommendation in the form of learning path (LP) in which LP will then be used as a recommendation for the teacher in constructing a learning process. In this research, LP was obtained through the identification of students' metacognitive with the use of Metacognitive Awareness Index (MAI) respectively. The system itself was developed using Naive Bayer Classifiers (NBC) and rule-based system to construct the LP. Accuracy of the machine learning for learner style module was of 97.25% and black box test indicated that the system was functionally acceptable. From these results, it can be concluded that the system was functionally acceptable and capable of representing an expert (seeing as it could produce an output that conformed to the expected condition). An expert in education had declared the LP was acceptable or in accordance to the design suggested by education experts. The developed adaptive learning path was proven to be better than the learning path in the preceding research.