Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Learning Analytics Method× | Учебная аналитика× | |
|---|---|---|
| Область≠ | Education | Образовательная аналитика |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления | 2011 | 2011 |
| Автор метода≠ | George Siemens, Ryan Baker, and the learning analytics research community | George Siemens & Phil Long |
| Тип≠ | Applied data-analytic methodology for educational data | data-driven educational process pipeline |
| Основополагающий источник≠ | Baker, R. S. J. d., & Inventado, P. S. (2014). Educational Data Mining and Learning Analytics. In J. A. Larusson & B. White (Eds.), Learning Analytics: From Research to Practice (pp. 61–75). Springer. DOI ↗ | Siemens, G., & Long, P. (2011). Penetrating the fog: Analytics in learning and education. EDUCAUSE Review, 46(5), 30–40. link ↗ |
| Другие названия | Learning Analytics Pipeline, Educational Learning Data Analytics, Analytics of Learner Trace Data, Learning Analytics Workflow | Educational Data Mining, Academic Analytics, Learning Data Analytics, Öğrenme Analitiği |
| Связанные≠ | 4 | 3 |
| Сводка≠ | Learning analytics is the measurement, collection, analysis, and reporting of data about learners and their contexts for the purposes of understanding and optimizing learning and the environments in which it occurs. Emerging as a distinct field around 2011, and consolidated through the work of George Siemens, Ryan Baker, and the Society for Learning Analytics Research, it is methodologically a pipeline: learner trace data are gathered from digital environments, integrated, modeled to detect patterns and predict outcomes, and then fed back to learners, instructors, and institutions to inform action. | Learning Analytics is the measurement, collection, analysis, and reporting of data about learners and their contexts, with the purpose of understanding and optimizing learning and the environments in which it occurs. Formally introduced by George Siemens and Phil Long in 2011, the approach draws on data generated in digital learning environments to provide educators, institutions, and learners with evidence-based feedback for improving educational outcomes. |
| ScholarGateНабор данных ↗ |
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