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| 学習曲線(実践のべき乗則)× | 学習アナリティクス× | |
|---|---|---|
| 分野 | 教育アナリティクス | 教育アナリティクス |
| 系統≠ | Regression model | Process / pipeline |
| 提唱年≠ | 1936 | 2011 |
| 提唱者≠ | Theodore Wright | George Siemens & Phil Long |
| 種類≠ | Power-law regression model | data-driven educational process pipeline |
| 原典≠ | Wright, T. P. (1936). Factors affecting the cost of airplanes. Journal of the Aeronautical Sciences, 3(4), 122–128. DOI ↗ | Siemens, G., & Long, P. (2011). Penetrating the fog: Analytics in learning and education. EDUCAUSE Review, 46(5), 30–40. link ↗ |
| 別名 | Power Law of Practice, Experience Curve, Wright's Law, Öğrenme Eğrisi | Educational Data Mining, Academic Analytics, Learning Data Analytics, Öğrenme Analitiği |
| 関連 | 3 | 3 |
| 概要≠ | The learning curve models how performance improves predictably as cumulative experience accumulates. Formalized by Theodore Wright in 1936 using aircraft manufacturing data, it expresses the relationship between the number of practice trials (or production units) and the time or cost per unit as a power-law function. It is widely applied in educational psychology, industrial engineering, health professions training, and human factors research whenever repeated task execution is the mechanism of skill acquisition. | 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. |
| ScholarGateデータセット ↗ |
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