The Project-Based Learning Study of Insurance Information Courses to Simulate the Application of Online Analytical Processing

IF 3.8 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Yung-Cheng Liao, Mei-Su Chen
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引用次数: 2

Abstract

The use of data warehouses combined with online analytical processing (OLAP) platforms has become popular in Taiwan’s insurance market. However, most schools do not have an insurance data warehouse and OLAP platform for student learning in Taiwan. The researched courses are insurance information system courses for two university classes. Based on the teacher’s experience and innovativeness, those courses are integrated using the guided project-based learning approach. Students need to build a customer micro-database, analyze customer figures through pivot analysis charts, and plan marketing campaigns. The study finds a project-based learning approach is helpful to enhance students’ OLAP analysis abilities. Secondly, the research finds that the flexibility for students to choose the topic of their project is one of the key success factors. Thirdly, the evaluation share of the student’s learning scores is important for the completion of the project. Fourthly, the courses are accompanied with satisfaction questionnaires to monitor the learning results and analyze the learning satisfaction for students among course A, course B, and the college average. Those students in the two classes both have higher satisfaction scores than the college average, but there are still differences between the classes after the t-test.
基于项目的保险信息课程学习研究——模拟在线分析处理的应用
结合联机分析处理(OLAP)平台的数据仓库的使用,在台湾的保险市场已经很流行。然而,大多数学校没有保险数据仓库和OLAP平台供学生在台湾学习。所研究的课程是两所大学的保险信息系统课程。根据教师的经验和创新,将这些课程整合在一起,采用引导式的项目式学习方法。学生需要建立一个客户微数据库,通过枢轴分析图表分析客户数据,并计划营销活动。本研究发现,以专案为基础的学习方式有助于提高学生的OLAP分析能力。其次,研究发现学生选择项目主题的灵活性是成功的关键因素之一。第三,学生学习成绩的评价份额对项目的完成很重要。第四,对课程进行满意度问卷调查,监测学生的学习效果,分析学生对课程A、课程B和学院平均水平的学习满意度。两班学生的满意度均高于大学平均水平,但经t检验,两班学生的满意度仍存在差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Applied System Innovation
Applied System Innovation Mathematics-Applied Mathematics
CiteScore
7.90
自引率
5.30%
发文量
102
审稿时长
11 weeks
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