ADAPTIC LEARNING AND LEARNING ANALYSIS

Abstract

Adaptive learning, also known as adaptive teaching, is an educational method which uses computer algorithms as well as artificial intelligence to orchestrate the interaction with the learner and deliver customized resources and learning activities to address the unique needs of each learner. The goal of utilizing Adaptive Learning was to increase student retention levels, and increase efficiency for both students and teachers. Learning analysis on the other hand, was found to be aimed at addressing “how to learn.” According to the activity theory, learning can be divided into three levels hierarchy: activities, actions, and operations. The learning activity can be seen as a sequence of learning behaviors. Due to the differences in individual characteristics such as the learner’s learning style and knowledge level, the learning activities are also different. Exploring the learner’s potential learning patterns with techniques such as educational data mining and machine learning is the key to achieving the recommendations of a personal learning path. This paper thus discussed the core concepts of adaptive learning and learning analysis.