Learning data analytics through a Problem Based Learning course
Learning data analytics through a Problem Based Learning course
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通过基于问题的学习课程学习数据分析
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
Rosario Goméz
中科院分区：
文献类型：
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作者：
Miguel Núñez;Rosario Goméz
在工程中实现有意义的意义总是一个挑战。基于问题或项目的学习（PBL）是一种不同的方法，试图加强基于学生调查和创新解决方案的学习过程，以解决真实的问题。在目前的努力中，我们提出了一种新的方法来评估PBL应用于信息工程专业学生的分析课程的影响。我们描述的分析，设计，实现，评估和可视化的Web挖掘平台，以及图书馆分析系统。这些项目分别涉及网络分析和数据挖掘课程。前者为学生提供了一个机会，开发一个真实的项目，从数据采集，从网站，数据存储，分析和可视化。后一门课程提供了一个框架，用于学习和应用知识数据发现（KDD）方法在图书馆数据集上分析客户并了解业务动态。在这两门课程中，学生都面临着处理大量异构数据的问题。
Achieving significant meaningful in Engineering is always a challenge. Problem or Project Based Learning (PBL) is one of the different methodologies that tries to enhance a learning process based on student inquiries and innovative solutions to solve real problems. In the present effort, we present a new approach for assessing the impact of PBL applied to analytics courses for Information Engineering students. We describe the analysis, design, implementation, evaluation and visualization of a Web mining platform as well as of a Library Analysis System. These projects concern the Web Analytics and Data Mining courses, respectively. The former provides students the opportunity to develop a real project ranging from data acquisition, from a Web site, data storing, analytics and visualization. The latter course furnishes a framework to learn and to apply the Knowledge Data Discovery (KDD) methodology over a library dataset to profile customers and understand business dynamics. In both courses, students are confronted to handle big amounts of heterogeneous data.