Salīdzināt metodes

	Classroom Observation Protocol	Vispārības teorija (G-teorija)
Nozare	Education	Psihometrija
Saime	Process / pipeline	Latent structure
Izcelsmes gads	2009	1963–1972
Autors	Teaching-measurement tradition (Pianta & Hamre CLASS; Danielson Framework; MET project)	Lee J. Cronbach, Goldine Gleser, Harinder Nanda, Nageswari Rajaratnam
Tips	Structured, standardized measurement of classroom teaching via trained observers	Variance-components reliability model
Pirmavots	Pianta, R. C., & Hamre, B. K. (2009). Conceptualization, measurement, and improvement of classroom processes: Standardized observation can leverage capacity. Educational Researcher, 38(2), 109–119.	Cronbach, L. J., Gleser, G. C., Nanda, H. & Rajaratnam, N. (1972). The Dependability of Behavioral Measurements: Theory of Generalizability for Scores and Profiles. Wiley.
Citi nosaukumi	Standardized Classroom Observation, Observation Instruments for Teaching, Classroom Observation System, Structured Teaching Observation	G-theory, G-study / D-study framework, variance components reliability
Saistītās	4	4
Kopsavilkums	A classroom observation protocol is a standardized instrument for measuring teaching by having trained observers rate lessons against defined dimensions of practice. Unlike informal walkthroughs, validated protocols such as the Classroom Assessment Scoring System (CLASS) and the Danielson Framework specify what to look for, how to score it, and how to train and calibrate raters. As Pianta and Hamre argued, standardized observation turns teaching into something that can be measured systematically, studied for sources of error, validated against student learning, and used to improve instruction.	Generalizability Theory is a psychometric framework that decomposes observed score variance into multiple sources — persons, items, raters, occasions, and their interactions — using analysis of variance. It replaces the single reliability coefficient of classical test theory with a family of coefficients that tell researchers how well scores generalize across different measurement conditions.