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Artificial Intelligence Knowledge Development

This study examines the integration of artificial intelligence (AI) tools with Nation&rsquo;s Four Strands Framework in the design of pre-class learning modules for English as a Foreign Language (EFL) flipped classrooms. Focusing on conversational skills development&mdash;a domain requiring balanced attention to meaning-focused input/output, language-focused learning, and fluency&mdash;the research addresses a critical gap in material design for technology-mediated flipped instruction. Employing a qualitative case study methodology, semi-structured interviews and focus group discussions were conducted with six Indonesian EFL teachers at the tertiary level. Data analysis revealed a four-phase pedagogical model wherein AI tools were systematically deployed to: (1) scaffold meaning-focused input (e.g., AI-generated transcriptions, text adaptation), (2) reinforce language-focused learning (e.g., grammar/vocabulary feedback systems), (3) facilitate meaning-focused output (e.g., conversational AI prompts), and (4) enhance fluency development (e.g., adaptive speaking drills). Key challenges emerged regarding AI&rsquo;s limitations in contextual appropriateness, feedback reliability, and the risk of pedagogical fragmentation, necessitating teacher mediation to preserve theoretical fidelity. The study contributes to literature on flipped learning by demonstrating how AI can operationalize SLA principles while affirming educators&rsquo; central role in curricular decision-making. Practical implications for instructional design and teacher professional development are discussed, alongside recommendations for future research on AI&rsquo;s efficacy across diverse institutional contexts.

ltrq.2025.49.05.pdf

Original Research 

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A Four-Stranded Approach to AI-Assisted Pre-Class Learning Modules: EFL Teachers’ Practices in Designing Daily Conversation Content for Flipped Classrooms

Blended learning in maritime education, particularly in the Seafarer Upgrading Program, faces challenges in adapting effective teaching methods for Maritime English (ME) instruction. A promising approach, Blended Task-Based Language Teaching (B-TBLT), combines Task-Based Language Teaching (TBLT) with blended learning environments. However, limited studies have explored students' perspectives on its implementation. This study endeavours to investigate students&rsquo; perceptions of B-TBLT in ME teaching. Data were collected from twenty Deck Officer Class IV students who were enrolled in ME instruction with B-TBLT using a mixed-method approach. This was achieved through questionnaires and interviews. The results indicate that students perceive B-TBLT positively, particularly in improved language skills, satisfaction and engagement, task relevance to real-world applications, and the role of technology. Moreover, the students expressed favourable views on the blended learning format, as it helped them increase independence and collaboration. Despite these positives, challenges related to time management and learning balance were identified. These findings underscore the potential of B-TBLT in ME education and provide implications for improving blended learning strategies in specialized training programs, particularly in vocational contexts.

ltrq.2025.49.08.pdf

ltrq.2025.49.08.xml

Blended Task-Based Language Teaching in Maritime English: Voices of Indonesian Seafarer Upgrading Program Students