Variable- and Person-centred meta-re-analyses of university students' learning strategies from a cross-cultural perspective

Alex Shum*, Luke K. Fryer, Jan D. Vermunt, Clara Ajisuksmo, Francisco Cano, Vincent Donche, Dennis C.S. Law, J. Reinaldo Martínez-Fernández, Peter Van Petegem, Ji Yu

*Autor corresponent d’aquest treball

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Resum

Studies on learning strategies across cultures in higher education inform the internationalisation of teaching and learning. Previous comparisons relied on geographical generalisations (e.g., “Asian”, “Western”, “Latin-American”) or only variable-centred methods, which can overgeneralise the contexts they represent. Eight learning strategy datasets (ILS; Inventory of Learning patterns of Students) from seven countries (n = 4883) were obtained and (re-)analysed using variable-centred and person-centred (Latent Profile Analysis; LPA) methods. Employing Hofstede’s individualism-collectivism and power distance indices as predictors, lower individualism and higher power distance scores corresponded to students’ overall combined reporting of meaning-directed, reproduction-directed and application-directed learning strategies. Furthermore, sample LPAs found that less individualistic contexts presented profiles with similar shape (i.e., profiles differed by similar amounts across most learning strategies). More individualistic contexts presented profiles with different shapes (i.e., different profiles preferred different strategies). Multiple “Western” contexts presented profiles that describe the “Asian” and “Latin-American” learner stereotypes. These results question the existence of such stereotypes and point to the usefulness of cultural indicators for making cross-cultural learning strategy comparisons. Theoretical and practical implications are discussed.
Idioma originalEnglish
Nombre de pàgines24
RevistaHigher Education
DOIs
Estat de la publicacióPublicada - 21 de juny 2023

Keywords

  • Cross-cultural Analysis
  • International
  • Learning Patterns
  • Learning strategies
  • Person-centred Analysis

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