A practical use of learning system using user preference in ubiquitous computing environment

Abstract

U-learning, or ubiquitous learning, has become the state-of-the-art educational trend in information technology. In ubiquitous learning environment, students now have the ability to learn anytime and anywhere. In many computer-assisted learning systems (such as e-learning, m-learning and u-learning), students must follow the lesson plans and learning environments established by the teacher. To overcome this limitation and increase effective learning, new techniques that reflect alternative learning styles, such as self-directed learning, adaptive learning and personalized learning, have been developed. These techniques have been researched extensively, but they still do not consistently reflect the specific needs of all students. In this article, a u-learning system is proposed that considers the learning level and preferences of each learner. The system provides information about the student's preferred learning section and difficulty level of learning contents and indicates the areas that may require additional study (based on the educational history of the student), thus allowing students to set up an optimized learning environment. A topic preference vector was applied to calculate the student's preferences, and the learning section and the difficulty level were used as each vector value in the system. To verify the effectiveness of the proposed system, an English-learning system was implemented using content from the reading comprehension section of the Test of English for International Communication (TOEIC). An experiment was conducted using a control group and a test group. The results demonstrated that the system proposed in this paper is useful for improving learning efficiency.