AI Chatbots to develop communicative competence in english

The impact of ChatGPT on students’ academic writing skills: A scoping review

ChatGPT Integration in EFL Advanced Grammar Instruction: A Pedagogical Framework

This study addresses the growing integration of artificial intelligence in English as a Foreign Language (EFL) education, particularly in advanced grammar instruction where learners often face difficulties in mastering complex structures. It aims to examine how ChatGPT can support grammar learning based on established second language acquisition (SLA) theories and learners’ perceptions. The study employs a qualitative descriptive design supported by a small-scale survey involving undergraduate students. Data were collected through questionnaires and a systematic literature review and analyzed thematically. The findings reveal that ChatGPT provides significant pedagogical affordances, including immediate corrective feedback, promotion of learner autonomy, and contextualized language use. Students also reported positive perceptions regarding its usefulness and ease of use. These findings align with key frameworks such as the Interaction Hypothesis, Sociocultural Theory, and Focus on Form. The study concludes that ChatGPT can effectively enhance grammar instruction when integrated within a structured pedagogical framework. This research contributes to the development of AI-assisted language learning models and offers practical implications for EFL practitioners and curriculum designers. Keywords: ChatGPT; EFL Instruction; Grammar Learning; Language Pedagogy; Second Language Acquisition

The Effectiveness of AI Chatbots in Developing Conversational Fluency in Arabic as a Second Language

The rapid advancement of artificial intelligence (AI) has transformed language education by providing learners with innovative tools for language practice and interaction. Among these tools, AI chatbots have emerged as effective platforms for enhancing second-language learning through personalized and interactive communication. This study investigates the effectiveness of AI chatbots in developing conversational fluency in Arabic as a Second Language (ASL). A quasi-experimental pre-test–post-test control group design is proposed to compare the conversational performance of learners using AI chatbots with those receiving traditional instruction. The study examines improvements in fluency, accuracy, vocabulary use, pronunciation, and communication confidence. Findings are expected to demonstrate that AI chatbots significantly enhance learners’ conversational fluency by providing continuous opportunities for meaningful interaction, immediate feedback, and reduced communication anxiety. The study contributes to the growing body of research on artificial intelligence in language education and offers practical implications for Arabic language teaching in digital learning environments.

Development of SobatAI: A Companion Chatbot for English Language Learning Based on Users’ Passion and Profession

The rapid integration of artificial intelligence (AI) into educational practices has enabled the development of adaptive learning tools that provide personalized language-learning experiences. This study aims to develop SobatAI, an English learning companion chatbot that adapts to users’ passions and professional backgrounds. Employing the Design and Development Research (DDR) method, this study consists of three phases: analysis of user needs, system design and development, and usability testing. A total of 75 university students and early-career professionals participated in prototype testing. Findings show that SobatAI successfully provides personalized vocabulary, situational dialogues, and micro-learning content tailored to users’ specific fields, such as technology, health, tourism, and creative industries. Usability scores indicate that the system achieves high acceptance, with an average SUS score of 83.2. The study concludes that integrating personal interests and professional context significantly enhances engagement and relevance in English language learning. Recommendations for further improvement include incorporating multimodal responses and adaptive proficiency-level tracking.

Improving the Methodology for Developing Linguistic and Communicative Competence of Future English Language Teachers through the CLIL Approach

The present study investigates the effectiveness of the Content and Language Integrated Learning (CLIL) approach in improving the methodology for developing linguistic and communicative competence among future English language teachers. Responding to the growing demand for language educators who possess not only advanced linguistic proficiency but also the ability to communicate effectively across academic and professional contexts, the study explores the pedagogical potential of CLIL in teacher education. A mixed-methods quasi-experimental research design was employed involving 72 undergraduate students enrolled in English language teacher education programmes. Quantitative data were collected through pre- and post-tests and structured questionnaires, while qualitative evidence was obtained from classroom observations, semistructured interviews, and students’ reflective journals. The findings revealed that CLIL-based instruction produced statistically significant improvements in linguistic accuracy, vocabulary development, communicative fluency, interactional confidence, critical thinking, and interdisciplinary communication skills compared with conventional language instruction. The analysis further identified collaborative learning, authentic communicative tasks, reflective practice, project-based activities, and the integration of digital educational technologies as the principal factors facilitating competence development. The study argues that CLIL promotes meaningful language use by integrating subject content with language learning, thereby enhancing both academic achievement and professional readiness. It concludes that the CLIL approach represents an effective pedagogical framework for modern English language teacher education and offers valuable implications for curriculum design, teacher training, and educational innovation in multilingual learning environments.

Chatbot-Supported Implementation on Pre-Service English Language Teachers' Academic Speaking Skills

Artificial intelligence (AI) chatbots, particularly with the advancements in generative artificial intelligence (GAI), have gained prominence in language education. In this context, the main purpose of this study, designed with a mixed-methods experimental design, is to examine the effect of the Call Annie chatbot application on the academic speaking skills of pre-service English language teachers, considering the structural limitations of the EFL context. Furthermore, it aims to examine in depth how this effect occurs through qualitative data. The study's data were collected through speaking achievement tests, response papers, and semi-structured interviews, and the validity and reliability of the research were increased by triangulating the data sources. The quantitative findings of the research revealed a statistically significant difference in the midterm and final grades of the experimental group compared to the control group after a 10-week application. The qualitative findings show that pre-service teachers experienced a learning environment free from stress and anxiety, with personalised instant feedback provided by the chatbot implementation. It was concluded that Call Annie had a positive effect on oral communication skills, and pre-service teachers indicated that they would continue to utilize this tool in future speaking activities.