Premium
Latent class analysis of non‐formal learners’ self‐directed learning patterns in open educational resource repositories
Author(s) -
Kim Dongho,
Lee InHeok,
Park JooHo
Publication year - 2019
Publication title -
british journal of educational technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.79
H-Index - 95
eISSN - 1467-8535
pISSN - 0007-1013
DOI - 10.1111/bjet.12746
Subject(s) - formal learning , open educational resources , class (philosophy) , autodidacticism , formal education , educational technology , computer science , mathematics education , open learning , psychology , cooperative learning , pedagogy , teaching method , world wide web , artificial intelligence
Open educational resources (OERs) are increasingly adopted in non‐formal education contexts. However, little research has been conducted to investigate the self‐directed learning patterns of non‐formal learners using OERs. A lack of knowledge about non‐formal learners precludes discussions on how to support their self‐regulated learning in open learning environments. We explored the self‐directed learning patterns of 1892 non‐formal online learners who were using OER repositories. In addition, we examined whether differences existed in future intentions to use OERs between learners with different learning patterns. Four latent classes were identified, and learners’ age was found to affect class membership. We also found that non‐formal learners’ use of self‐directed learning strategies predicted their future intentions to use OERs. This study advanced our understanding of the subpopulations of non‐formal learners using OERs. Future research will benefit from the findings related to designing OER environments that can accommodate diverse self‐directed learners.