Learning data analytics through a Problem Based Learning course

Miguel Núñez-del-Prado, Rosario Goméz
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引用次数: 10

Abstract

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.
通过基于问题的学习课程学习数据分析
在工程领域取得重大成就始终是一个挑战。基于问题或项目的学习(PBL)是一种不同的方法,试图加强基于学生的询问和创新的解决方案来解决实际问题的学习过程。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分析课程的影响。本文描述了一个Web挖掘平台的分析、设计、实现、评估和可视化,以及一个图书馆分析系统。这些项目分别涉及网络分析和数据挖掘课程。前者为学生提供了开发一个真实项目的机会,包括数据采集、网站、数据存储、分析和可视化。后一门课程提供了一个框架来学习和应用知识数据发现(KDD)方法,通过图书馆数据集来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。
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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