Salīdzināt metodes

	Mācīšanās līkne (prakses pakāpes likums)	Apguvuma analītika
Nozare	Izglītības analītika	Izglītības analītika
Saime	Regression model	Process / pipeline
Izcelsmes gads	1936	2011
Autors	Theodore Wright	George Siemens & Phil Long
Tips	Power-law regression model	data-driven educational process pipeline
Pirmavots	Wright, T. P. (1936). Factors affecting the cost of airplanes. Journal of the Aeronautical Sciences, 3(4), 122–128.	Siemens, G., & Long, P. (2011). Penetrating the fog: Analytics in learning and education. EDUCAUSE Review, 46(5), 30–40.
Citi nosaukumi	Power Law of Practice, Experience Curve, Wright's Law, Öğrenme Eğrisi	Educational Data Mining, Academic Analytics, Learning Data Analytics, Öğrenme Analitiği
Saistītās	3	3
Kopsavilkums	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.