Affective Repertoires and Motivation in L2 and L3 Learning: An AI ‐Augmented Mixed Methods Study

Abstract 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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Publication Details

Journal
TESOL Quarterly
Published
2026-08-24
DOI
https://doi.org/10.1002/tesq.70213
Primary Topic
EFL/ESL Teaching and Learning
Type
article
Field-Weighted Citation Impact
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article

Affective Repertoires and Motivation in L2 and L3 Learning: An AI ‐Augmented Mixed Methods Study

Derin Atay, Ertürk Erdağı, Esra Meşe, Özge KURU
TESOL Quarterly
EFL/ESL Teaching and Learning
article

Affective Repertoires and Motivation in L2 and L3 Learning: An AI ‐Augmented Mixed Methods Study

Derin Atay, Ertürk Erdağı, Esra Meşe, Özge KURU
article en

Abstract

Abstract 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.

TESOL Quarterly
Bahçeşehir University (TR), Mi̇lli̇ Eği̇ti̇m Bakanliği (TR), Istanbul Technical University (TR), Istanbul Medeniyet University (TR)
Quality Education
Openalex Percentile: Top 2%
EFL/ESL Teaching and Learning
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Affective Repertoires and Motivation in L2 and L3 Learning: An AI ‐Augmented Mixed Methods Study — Derin Atay, Ertürk Erdağı, et al. · TESOL Quarterly (2026) | TGRS Research Map | TGRS