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Mixed-methods study reveals distinct emotional profiles and an affect-motivation mismatch across languages in multilingual high school students, highlighting language-specific emotional dynamics.
This study investigates the enjoyment, anxiety, and motivation of Turkish high school learners in L2 English and L3 Spanish foreign language classes using an explanatory sequential mixed methods design. Quantitative data were collected from 115 students using the Foreign Language Enjoyment (FLE), Foreign Language Classroom Anxiety (FLCA), and Attitude/Motivation Test Battery (AMTB) scales. Findings showed significantly higher enjoyment and anxiety in Spanish, while English elicited greater motivation. To explore the deeper underlying causes, focus group interviews were analyzed through AI‐assisted Sentiment Analysis (SA), followed by thematic analysis. SA enabled efficient pre‐clustering of learner statements by emotional polarity and supported integration through merging. Qualitative findings revealed an affect‐motivation mismatch: Spanish was more enjoyable due to creative pedagogy but triggered anxiety linked to low proficiency; English was less engaging but perceived as essential for future goals. Methodologically, the study illustrates the value of combining traditional and AI‐assisted tools in ELT research. Drawing on Pavlenko's sociocognitive view of emotion, the study emphasizes that each language has its own affective repertoires and reveals the language‐specific dynamics of multilingual learners' emotional investment in additional foreign languages. The findings demonstrate the central role of affect in foreign language learning processes and show that each language can create distinct emotional profiles in multilingual contexts.
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KURU et al. (2026) studied this question.
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