DBLearn: Adaptive e-learning for practical database course — An integrated architecture approach

Abstract

In this paper, an integrated architecture approach in designing and developing a DBLearn web-based application is presented. The DBLearn system is a personalized and adaptive e-learning system designed especially for learning practices in database courses. This approach focused on topics that are important but difficult for new learners, such as database design and structured query language (SQL) command query. The concept of adaptive e-learning and autonomous agents were applied in this system to eliminate the traditional constraints of effective e-learning, such as the problem of different learning sensory and knowledge levels. Four approaches were used to solve this problem. First, learning style theory was used to classify the way of learning for each student. Second, the student activity (historical data) is kept in the system to analyze the next knowledge the student should learn or review. Next, the SQL query automated grader was used to judge the correctness of the student's query. This grader supports all the necessary commands in both DML and DDL. Finally, the SQL query question generator module that can generate SQL query questions automatically is presented. This will reduce the instructor's work load in creating enough questions and allow the students to practice at their own pace as much as they want. By using these four techniques, the students will have a better learning experience and becoming more successful in learning outcomes.