2016 Fiscal Year Final Research Report
Generating potential-response-tree for mathematics e-learning system using algorithm and expertise based on experience
| Project/Area Number |
15K12377
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Multi-year Fund |
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| Research Field |
Science education
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| Research Institution | Nagoya University |
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Principal Investigator |
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| Project Period (FY) |
2015-04-01 – 2017-03-31
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| Keywords | ｅラーニング / 教育工学 / 数学教育 |
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| Outline of Final Research Achievements |
It is important to develop a mechanism that can create potential response from students in order to flexibly respond to several kinds of answers from students and to give suitable feedbacks for them in online test of e-learning system that can evaluate mathematical expressions as answers. We developed a prototype of typical questions by utilizing mathematics e-learning system, STACK, and we found that it is the most efficient way to use the prototype of questions and modify them based on the expertise obtained from a lot of experience of education for most effective blending of algorithm and expertise based on experience.
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| Free Research Field |
教育工学
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