Marian Hickendorff|Peter Adriaan Edelsbrunner|Jake McMullen|Michael Schneider|Kelly Trezise
Informative tools for characterizing individual differences in learning: Latent class, latent profile, and latent transition analysis
Leiden University|ETH Zurich|University of Turku|Universität Trier|University of Melbourne
article gives introduction latent class latent profile latent transition models researchers interested investigating individual differences learning development models allow analyzing observed heterogeneity group eg individual differences conceptual knowledge traced back underlying homogeneous subgroups eg learners differing systematically developmental phases estimated parameters include characteristic response pattern subgroup case longitudinal data probabilities transitioning one subgroup another time article describes steps involved using models gives practical examples discusses limitations extensions overall models help characterize heterogeneous learner populations multidimensional learning outcomes nonlinear learning pathways changing relations learning processes application models therefore make substantial contribution understanding learning individual differences