Language learning motivation and attitudes among immigrant background studentsa mixed method approach comparing three secondary school contexts

Resumen

For over half a century, second language acquisition research has sought to identify individual factors that explain language learners' different degrees and rates of acquisition. Studies have shown that motivation is one of the factors most relevant to whether or not an individual will learn a language (Dörnyei, 2001; Gardner, 1985; 2010; Skehan, 1989). While L2 motivation studies are decidedly abundant, few combine qualitative and quantitative methods as does this study, and rarely have motivation and attitudes between languages of study been compared with immigrant background students¿ attitudes toward their home language. This study utilizes the Socio-educational (SE) Model (Gardner, 1985, 2010) and an adaptation of the mini-AMTB (Bernaus & Gardner, 2008) to identify possible factors affecting plurilingual or potentially plurilingual students¿ attitudes and motivation toward the languages they study and/or speak. It compares and contrasts these factors in three different study contexts, along with self-ratings of language ability, in order to identify significant language-based, socio-demographic, and contextual differences. Two secondary school contexts in Catalonia, one of the EU territories with the highest rate of recent immigration, are compared with a central Californian context in the United States. Data were collected from a total of 233 students. t-Tests comparing student short-term residents with their longer resident and native peers confirmed that significant differences existed in response patterns between these two groups for certain measures. Significant differences were shown not only when comparing Catalan contexts as a whole to the California context, but also when comparing two separate Catalan contexts. Univariate repeated measures analysis of variance showed significant differences between languages studied, demonstrating variation for most measures when languages were compared. The use of open-ended survey questions resulted in 947 Units of Analysis that were categorized according to similarities. The Units of Analysis, analyzed qualitatively, are considered to both complement and enhance quantitative data.