Linking emotional intelligence and AI-enhanced learning to goal-setting behavior: A cognitive load theory framework

Reflecting previous studies on technology-mediated language learning, the present research focused on the interrelatedness of artificial intelligence (AI) use, cognitive load, emotion regulation, goalsetting behaviour and satisfaction in English as a Foreign Language (EFL) situations. A total of 549 EFL learners in higher education voluntarily participated in the research by responding to validated questionnaires on the use of AI tools, perceived cognitive load, emotion regulation strategies, goalsetting behaviour and overall satisfaction. The data were analysed through SPSS (version 27) for descriptive and correlational statistics and AMOS (version 24) for structural equation modelling. The results indicated that AI use positively impacted on goalsetting behaviour and satisfaction of learners with cognitive load and emotion regulation functioning as both mediators and moderators of this effect. More specifically, those learners who managed cognitive load effectively and used adaptive emotion regulation strategies indicated greater clarity in their goals, greater commitment to learning and greater satisfaction with the learning process. The findings contribute to Social-Cognitive Theory and Cognitive Load Theory by focusing on the interplay of technology, cognition and emotion in language learning and provide valuable perspectives on how AI-enhanced EFL learning environments may be designed and implemented.