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منحنی یادگیری (قانون توان تمرین)×ردیابی دانش×
حوزهتحلیل‌گری آموزشیتحلیل‌گری آموزشی
خانوادهRegression modelMachine learning
سال پیدایش19361994
پدیدآورTheodore WrightAlbert Corbett & John Anderson
نوعPower-law regression modelProbabilistic student modeling
منبع بنیادینWright, T. P. (1936). Factors affecting the cost of airplanes. Journal of the Aeronautical Sciences, 3(4), 122–128. DOI ↗Corbett, A. T., & Anderson, J. R. (1994). Knowledge tracing: Modeling the acquisition of procedural knowledge. User Modeling and User-Adapted Interaction, 4(4), 253–278. DOI ↗
نام‌های دیگرPower Law of Practice, Experience Curve, Wright's Law, Öğrenme EğrisiBKT, Bayesian Knowledge Tracing, Deep Knowledge Tracing, Bilgi İzleme
مرتبط33
خلاصهThe 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.Knowledge Tracing (KT) is a student-modeling technique that estimates, at each moment in time, the probability that a learner has mastered a target knowledge component. Introduced by Corbett and Anderson in 1994, the classical Bayesian Knowledge Tracing (BKT) model treats skill acquisition as a two-state Hidden Markov Model driven by four interpretable parameters: prior knowledge, learning rate, slip, and guess. Deep variants (DKT, DKVMN, AKT) later replaced HMMs with recurrent and transformer architectures.
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ScholarGateمقایسهٔ روش‌ها: Learning Curve · Knowledge Tracing. بازیابی‌شده در 2026-06-15 از https://scholargate.app/fa/compare