方法对比

	Latent Transition Analysis in Education	Learning Progressions Analysis
领域	Education	Education
方法族	Latent structure	Process / pipeline
起源年份	2010	2009
提出者	Latent variable methodology (Collins & Wugalter; Collins & Lanza)	Science and mathematics education research (Corcoran, Mosher, Rogat; Wilson; Clements & Sarama)
类型	Longitudinal latent class model for movement between qualitative learner states	Empirically grounded ordered description of how understanding develops over time
开创性文献	Collins, L. M., & Lanza, S. T. (2010). Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences. Wiley. ISBN: 9780470228395	Corcoran, T., Mosher, F. A., & Rogat, A. (2009). Learning Progressions in Science: An Evidence-Based Approach to Reform (CPRE Research Report RR-63). Consortium for Policy Research in Education.
别名	Educational LTA, Latent Markov Modeling of Learning, Stage-Sequential Latent Class Modeling, Latent Transition Modeling	Learning Trajectories, Progress Variables, Learning Progression Validation, Construct Maps
相关	4	4
摘要	Latent transition analysis (LTA) is a longitudinal extension of latent class analysis that models how individuals move between qualitatively distinct, unobserved categories over time. In education it represents students as belonging to learner profiles or developmental stages — for example, types of motivation, reading-strategy profiles, or mastery stages — and estimates the probabilities of transitioning from one profile to another between time points. It answers not only how many kinds of learners there are, but how learners change type as instruction and development unfold.	Learning progressions analysis is a methodology for describing and validating the typical paths by which students' understanding of a core concept grows more sophisticated over time. A learning progression hypothesizes an ordered sequence of increasingly advanced ways of thinking — from naive ideas to expert understanding — and then tests that ordering against evidence of how students actually reason. Prominent in science and mathematics education, it links a theory of the domain, the design of assessment tasks, and a measurement model into a coherent description of conceptual development.