Usporedite metode

	Learning Analytics Method	Analitika učenja
Područje	Education	Analitika obrazovanja
Obitelj	Process / pipeline	Process / pipeline
Godina nastanka	2011	2011
Tvorac	George Siemens, Ryan Baker, and the learning analytics research community	George Siemens & Phil Long
Vrsta	Applied data-analytic methodology for educational data	data-driven educational process pipeline
Temeljni izvor	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.	Siemens, G., & Long, P. (2011). Penetrating the fog: Analytics in learning and education. EDUCAUSE Review, 46(5), 30–40.
Drugi nazivi	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
Srodne	4	3
Sažetak	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.