MATCHA: Journal of Modern Approaches to Communication, Humanities, and Academia

Voices in Transition: EFL Learners’ Interaction with AI Tools to Improve Speaking

2025-10-10T21:15:31+07:00

This study explores how English as a Foreign Language (EFL) learners experience and make sense of their interactions with Artificial Intelligence (AI) tools to develop speaking proficiency. Using a narrative inquiry approach, in-depth interviews and reflective journals were collected from 12 learners who regularly used ChatGPT, ELSA Speak, Duolingo, and MySpeaker Rhetorich. Grounded in Sociocultural Theory and Swain’s Output Hypothesis, the analysis examined how AI mediated learners’ cognitive and affective engagement within their Zones of Proximal Development. Findings revealed that AI tools created psychologically safe spaces, reduced speaking anxiety, and provided immediate, precise feedback, fostering greater fluency, accuracy, and learner autonomy. Learners valued AI’s personalization and accessibility but also noted limitations in cultural nuance, humor, and emotional depth, positioning AI as a supplement rather than a substitute for human interaction. This study offers qualitative insights into the affective and social dimensions of AI-mediated speaking practice, highlighting strategies for integrating AI into EFL pedagogy to support both linguistic development and emotional readiness for communication.

Examining English Teachers’ Lesson Plans: A Content Analysis of Higher-Order Thinking Skill Integration

2025-08-06T09:56:39+07:00

This study investigates the extent and nature of higher-order thinking skill (HOTS) integration in English teachers’ lesson plans within English as a Foreign Language (EFL) context. Using Bloom’s Revised Taxonomy as the analytical framework, the research employed a qualitative content analysis of 12 lesson plans drawn from secondary and tertiary English teachers in Indonesia. The analysis focused on identifying the presence and types of cognitive processes embedded in learning objectives, instructional activities, and assessments. The findings reveal a predominant emphasis on lower-order thinking skills (LOTS), particularly understanding and applying, while HOTS—such as analyzing, evaluating, and creating—were included less frequently and often lacked alignment across instructional components. Among the HOTS categories, analyzing appeared most commonly, whereas evaluating and creating were significantly underrepresented. This suggests a limited instructional emphasis on critical and creative thinking development in EFL lesson planning. The study concludes that while teachers may recognize the importance of fostering HOTS, structural, curricular, and pedagogical constraints often hinder their consistent implementation. Limitations of the study include the small sample size and exclusive reliance on document analysis. Future research should incorporate classroom observations and teacher interviews to gain a more holistic understanding of how HOTS are operationalized in practice.

Teachers’ Experiences Using ChatGPT for Lesson Planning in EFL Classrooms

2025-10-20T14:28:31+07:00

This qualitative study explores EFL teachers’ experiences using ChatGPT for lesson planning, focusing on both practical interactions and reflective perceptions. Through semi-structured interviews with eight teachers, the research investigates how ChatGPT influences lesson design, professional identity, and pedagogical thinking. Findings reveal that ChatGPT enhances efficiency by providing immediate access to diverse resources and stimulates creativity by suggesting novel teaching ideas. However, teachers also face challenges related to the contextual relevance and accuracy of AI-generated content, requiring critical evaluation and adaptation to align with local curricula and student needs. Additionally, teachers experience a shift in professional identity, viewing themselves as collaborators with AI rather than sole content creators. This shift fosters deeper pedagogical reflection and more flexible lesson design practices. At the same time, concerns about over-dependence on AI and the potential loss of authenticity highlight important ethical and professional considerations. The study emphasizes the need for balanced and critical engagement with AI tools in EFL teaching, advocating for teacher training programs that address both technical and ethical dimensions. The findings contribute to understanding the complex role of AI in language education and suggest directions for future research on AI-supported teaching practices.

Digital Literacy Among EFL Teachers: Navigating Technological Demands in 21st-Century Classrooms

2025-10-26T09:17:46+07:00

This study investigates the digital literacy of English as a Foreign Language (EFL) teachers and the challenges and support systems they encounter in integrating technology into 21st-century classrooms. Drawing on qualitative data from semi-structured interviews and classroom observations with seven EFL teachers, the research explores the multidimensional nature of teachers' digital literacy, the systemic and emotional obstacles they face, and the informal strategies they adopt to cope. The findings reveal that digital literacy among EFL teachers extends beyond technical skill to include pedagogical adaptability and critical awareness. However, limitations such as infrastructural instability, lack of institutional guidance, and emotional resistance often hinder full digital engagement. Despite these challenges, teachers demonstrate agency by forming peer support networks, engaging in self-directed learning, and drawing encouragement from student feedback. These informal mechanisms, while valuable, highlight the absence of coordinated institutional support. The study concludes that sustainable digital integration in EFL contexts requires a holistic approach that combines technological access, emotional support, and professional learning communities. By reframing digital literacy as a dynamic and context-sensitive practice, the study contributes to ongoing dialogues around teacher agency, equity, and innovation in language education.

AI Writing Assistants in English Language Learning: Evaluating Feedback Quality and Learner Autonomy

2025-10-21T15:32:35+07:00

As artificial intelligence (AI) writing assistants become increasingly integrated into English language learning (ELL), their influence on feedback quality and learner autonomy warrants critical evaluation. This mixed-methods study investigates how AI-generated feedback compares to teacher feedback in terms of accuracy, clarity, usefulness, and its impact on learner autonomy. Forty university-level ELLs completed writing tasks using either AI tools or instructor input. Results showed that while AI feedback was effective for correcting surface-level errors, it lacked the pedagogical depth necessary to foster meaningful learning. Teacher feedback, by contrast, encouraged reflective revision, metacognitive engagement, and greater writing independence. Despite AI tools’ convenience and immediacy, learners often accepted suggestions passively, which hindered the development of critical evaluation skills and self-regulated learning. The study concludes that AI writing assistants can serve as useful supplements in writing instruction but should not replace human feedback. Instead, a hybrid model that combines technological efficiency with pedagogical insight may offer the most effective support for developing autonomous, reflective writers.