Performance Indicators for Online Geography in Secondary Education
| Authors |
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|---|---|
| Publication date | 2016 |
| Host editors |
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| Book title | BNAIC 2016 : Benelux Conference on Artificial Intelligence |
| Book subtitle | proceedings of the Twenty-Eight Benelux Conference on Artificial Intelligence : Amsterdam, November 10-11, 2016 |
| Series | BNAIC |
| Event | Annual Benelux Conference on Artificial Intelligence |
| Pages (from-to) | 206-207 |
| Publisher | Amsterdam: Vrije Universiteit, Department of Computer Sciences |
| Organisations |
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| Abstract | There is little consensus about what variables extracted from learner data are the most reliable indicators of learning performance. The aim of this study was to determine those indicators by taking a wide range of variables into consideration concerning overall learning activity and content processing. A Genetic Algorithm was used for the selection process and the variables were evaluated based on their predictive power. Variables extracted from exercise activities turned out to be the most informative. |
| Document type | Conference contribution |
| Language | English |
| Related publication | Performance indicators for online secondary education: a case study |
| Published at | http://bnaic2016.cs.vu.nl/index.php/proceedings |
| Downloads |
Performance Indicators for Online Geography in Secondary Education
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