A1 Refereed original research article in a scientific journal

Informative tools for characterizing individual differences in learning: Latent class, latent profile, and latent transition analysis




AuthorsMarian Hickendorff, Peter A. Edelsbrunner, Jake McMullen, Michael Schneider, Kelly Trezise

PublisherElsevier

Publication year2018

JournalLearning and Individual Differences

Volume66

First page 4

Last page15

Number of pages12

ISSN1041-6080

eISSN1873-3425

DOIhttps://doi.org/10.1016/j.lindif.2017.11.001

Web address http://www.sciencedirect.com/science/article/pii/S1041608017301863

Self-archived copy’s web addresshttps://research.utu.fi/converis/portal/detail/Publication/27049564


Abstract

This article gives an introduction to latent class, latent profile, and latent transition models for researchers interested in investigating individual differences in learning and development. The models allow analyzing how the observed heterogeneity in a group (e.g., individual differences in conceptual knowledge) can be traced back to underlying homogeneous subgroups (e.g., learners differing systematically in their developmental phases). The estimated parameters include a characteristic response pattern for each subgroup, and, in the case of longitudinal data, the probabilities of transitioning from one subgroup to another over time. This article describes the steps involved in using the models, gives practical examples, and discusses limitations and extensions. Overall, the models help to characterize heterogeneous learner populations, multidimensional learning outcomes, non-linear learning pathways, and changing relations between learning processes. The application of these models can therefore make a substantial contribution to our understanding of learning and individual differences.


Downloadable publication

This is an electronic reprint of the original article.
This reprint may differ from the original in pagination and typographic detail. Please cite the original version.





Last updated on 2024-26-11 at 12:50