Tipo: artículo

Metodología: estudio empírico

Temas: enseñanza/aprendizaje de lenguas

Resumen:

Effective academic communication in multilingual higher education requires pragmatic competence, yet this dimension of language ability is often overlooked in instruction and insufficiently supported through feedback or authentic practice. Grounded in instructed pragmatics and technology-mediated learning frameworks, this study reports on the design, implementation, and empirical evaluation of an artificial intelligence (AI)-mediated multimodal platform developed to scaffold pragmatic competence in Indonesian within digital academic contexts. The platform integrates five interdependent features: automated text analysis to identify speech acts, politeness strategies, and violations of conversational principles; video analysis with multilingual transcription and theory-based annotation; conversation simulations providing context-...

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Tipo: artículo

Metodología: estudio empírico

Temas: comprensión oral

Resumen:

Listening instruction in language education often remains product-oriented, focusing on comprehension accuracy rather than awareness of cognitive processes and learner self-regulation. Grounded in metacognitive and self-regulated learning frameworks, this study examined the effectiveness of an artificial intelligence (AI)-mediated metacognitive listening textbook designed to promote metacognitive awareness and learner autonomy through guided reflection and adaptive feedback. The textbook implemented a four-phase metacognitive cycle (planning, monitoring, evaluating, reflecting) supported by AI feedback that helped learners diagnose comprehension challenges, plan strategies, and monitor progress. A 12-week quasi-experimental mixed-methods design was conducted with 500 upper-secondary learners divided into experimental (n = 250) and...

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Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

This study investigates the impact of an artificial intelligence (AI) assistant on reader response theory in novel analysis using a mixed-methods approach. It examines how AI-generated real-time feedback, powered by advanced machine learning and natural language processing, enhances interpretive possibilities beyond conventional methods, aligning with reader response theory’s emphasis on reader-text interaction. The AI assistant, designed with Real-Time Theme Identification, Character Relationship Mapping, Symbolism Detection, and Interactive Literary Simulation, supports nuanced interpretations, uncovers underlying patterns, and fosters deeper engagement with literary texts. Participants (n = 100), aged 15–18 years, were divided into an experimental group (n = 50), which used the AI assistant for novel analysis, and...

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