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

机译:DBLearn:适用于实际数据库课程的自适应电子学习—一种集成架构方法

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摘要

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.
机译:本文提出了一种设计和开发基于Web的DBLearn应用程序的集成体系结构方法。 DBLearn系统是一种个性化的自适应电子学习系统,专门为数据库课程中的学习实践而设计。这种方法侧重于对新学习者而言重要但困难的主题,例如数据库设计和结构化查询语言(SQL)命令查询。该系统采用了自适应电子学习和自主代理的概念,以消除有效的电子学习的传统限制,例如学习感官和知识水平不同的问题。使用了四种方法来解决此问题。首先,使用学习风格理论对每个学生的学习方式进行分类。其次,将学生活动(历史数据)保存在系统中,以分析学生应学习或复习的下一个知识。接下来,使用SQL查询自动评分器来判断学生查询的正确性。该分级机支持DML和DDL中的所有必需命令。最后,介绍了可以自动生成SQL查询问题的SQL查询问题生成器模块。这将减少教师提出足够问题的工作量,并允许学生按照自己的步调练习。通过使用这四种技术,学生将获得更好的学习体验,并在学习成果方面变得更加成功。

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