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Exam-based Education System

Song, Xuhang
http://rave.ohiolink.edu/etdc/view?acc_num=dayton1399044144

Abstract Details

2014, Master of Computer Science (M.C.S.), University of Dayton, Computer Science.
Big data is growing in importance in everyday life, yet traditional models of University education do not make good use of it. This thesis proposes a system that allows students to find courses based on similarity measures and take these courses in an exam-based environment. We describe a new mining method that can efficiently search, cluster and perform related functions in the system. The basic idea of this mining is to map courses in a university to buildings in a city. This means that finishing a degree or getting a skill is analogous to finding a path in the city. A number of approaches to build the city are presented. In the process of developing an algorithm, we use machine learning, artificial intelligence, and classic mining methods as core ideas.
Buckely James (Advisor)
Courte Dale (Committee Member)
Yao Zhongmei (Committee Member)
48 p.
Computer Science
Dataming; Genetic Agortihem; Eduction;

Recommended Citations

Citations

  • Song, X. (2014). Exam-based Education System [Master's thesis, University of Dayton]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1399044144

    APA Style (7th edition)

  • Song, Xuhang. Exam-based Education System. 2014. University of Dayton, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=dayton1399044144.

    MLA Style (8th edition)

  • Song, Xuhang. "Exam-based Education System." Master's thesis, University of Dayton, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1399044144

    Chicago Manual of Style (17th edition)

dayton1399044144
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This open access ETD is published by University of Dayton and OhioLINK.