While cluster analysis is becoming a popular method of identifying groups of learners that share similar characteristics, learners are typically grouped based on a small set of closely-related ID variables. To better understand L2 learning, we need to take a more integrative approach to profiling learners, considering abilities and attributes from different domains. In this study, we took an integrative, person-centered approach to identify language learner profiles among 544 learners of L2 Dutch in the Netherlands. We conducted a cluster analysis to identify similar groups of learners, considering cognitive abilities, pro-social behaviors, motivation, self-beliefs, level of multilingualism, and prior Dutch experience. Five distinct learner profiles emerged: (1) higher cognitive abilities – lower self-belief , (2) social learners – higher self-belief , (3) lower cognitive abilities – highly motivated , (4) highly multilingual – less social , and (5) lower motivation . While two profiles stood out for having particularly strong or weak attributes, other profiles were more mixed. In contrast to studies profiling learners of English in foreign language contexts, we did not find linear associations between prior Dutch experience and socio-affective constructs, highlighting the need for more research on learner profiles in LOTE settings. We also examined the relationship between different profiles and L2 learning gains over time, but found only small differences in L2 learning gains between profiles.
Freeborn et al. (Wed,) studied this question.