A Collaborative Project: Development of An Undergraduate Data Mining Course

合作项目：本科数据挖掘课程的开发

• 批准号: 0231448
• 负责人: Huan Liu
• 金额: $ 5.27万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-01-01 至 2004-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0231448&HistoricalAwards=false
• 关键词: Collaborative; Project; Development; Undergraduate; Data

Data mining is an emerging field. The knowledge of data mining has been in demand in the IT industry and in new areas like bioinformatics, information assurance, and homeland security where data are massive. Traditionally, data mining courses are offered at the graduate level; now, this type of course is needed at the undergraduate level to increase interest in this area and address labor market demands. This collaborative project between Arizona and Wright State Universities develops an undergraduate data mining course for junior and seniors. The objectives are: develop a course that can be taught either by semester ASU or quarter WSU term, establish vehicles and approaches to increase student retention in the course, and promote data mining skills essential to problem solving. The objectives are accomplished in several ways: designing a pre-assessment instrument measuring student knowledge of data mining, and on-line tutorials; develop course materials that will enhance problem solving skills through reflection, critique, exercises, discerning theory from practice; and using a continuous evaluation process that addresses not only student achievement but also enrollment retention. Input from leading IT industry is used to incorporate immediate practical needs. The results of the project including evaluation are published via various means. Notes, supporting materials, projects, and exams are made available on the course web site.

数据挖掘是一个新兴领域。 IT 行业以及生物信息学、信息保障和国土安全等数据量巨大的新领域一直需要数据挖掘知识。传统上，数据挖掘课程是在研究生级别提供的；现在，本科生需要开设此类课程，以增加对此领域的兴趣并满足劳动力市场的需求。亚利桑那州和莱特州立大学之间的这个合作项目为大三和大四学生开发了本科数据挖掘课程。目标是：开发一门可以按亚利桑那州立大学学期或华盛顿州立大学季度授课的课程，建立提高学生在课程中的保留率的工具和方法，并提高解决问题所必需的数据挖掘技能。这些目标通过多种方式实现：设计一个预评估工具来衡量学生的数据挖掘知识和在线教程；开发课程材料，通过反思、批评、练习、从实践中辨别理论来提高解决问题的能力；并使用持续的评估流程，不仅考虑学生的成绩，还考虑入学保留率。来自领先 IT 行业的意见被用来满足当前的实际需求。项目评估结果通过多种方式公布。课程网站上提供了笔记、支持材料、项目和考试。