Extracting structure of latent skills from examination results in programming education
| Project/Area Number |
25750095
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Educational technology
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| Research Institution | Kisarazu National College of Technology |
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Principal Investigator |
Oeda Shinichi 木更津工業高等専門学校, その他部局等, 准教授 (80390417)
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| Project Period (FY) |
2013-04-01 – 2016-03-31
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| Project Status |
Completed (Fiscal Year 2015)
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| Budget Amount *help |
¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2015: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2014: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2013: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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| Keywords | 非負値行列因子分解 / Educational Data Mining / プログラミング教育 / 教育データマイニング / EDM / NMF / BNF / 行列因子分解 / 時系列データ解析 / Knowledge Tracing / 隠れマルコフモデル / BMF |
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| Outline of Final Research Achievements |
Recently, ITS(Intelligent Tutoring Systems) has been widely used, these systems has allowed the collection of huge amounts of educational data, such as examination results or studying behavior of students. In this study, we extract latent skills to master programming technique from the point of view of EDM (Educational Data Mining).
Our studies applied NMF(non-negative matrix factorization) method to decompose the results of an examination into a Q-matrix and another matrix. The Q-matrix is the relationship between
items and skills. Our proposed method could extract and visualize latent skills of students.
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Report
(4 results)
Research Products
(15 results)
