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Generative AI and CEFR levels: Evaluating the accuracy of text generation with ChatGPT-4o through textual features
No full textSince its emergence, generative AI has significantly impacted various fields, including English language education. Numerous academic studies have investigated its capabilities in grammar correction, writing evaluation, and dynamics of user interaction. However, there have been insufficient investigations into whether texts generated by such AI align appropriately with CEFR proficiency levels. This study addresses this gap by exploring the applicability of generative AI to CEFR standards. Multiple texts were generated using ChatGPT-4o with specified CEFR levels and analyzed using a vocabulary level analyzer (CVLA) to evaluate text features. The findings revealed discrepancies between AI-generated texts and textbook standards, significant divergences between levels below B1 and above B2, and a noticeable topic bias. Although AI-generated texts seem to differ by level, they require careful evaluation before being applied to CEFR-based education
Exploring the role of Google Assistant in enhancing EFL learners' speaking skills: A systematic review
No full textThis study explores how Google Assistant can enhance the speaking skills of English as a foreign language (EFL) learners with an emphasis on involvement, pronunciation, accuracy and fluency. The study addresses the main question What is the approach by which Google Assistant helps EFL students become more proficient speakers? A total of 31 studies were selected and examined using a Systematic Literature Review (SLR) methodology. Criteria such as empirical study on the use of Google Assistant to enhance speaking skills were taken into consideration, and data were obtained from the Web of Science Core Collection. By employing a deductive content analysis, the studies were coded into groups about speaking practice, improving specific skills, and advantages and disadvantages. The main conclusions show that Google Assistant enhances learners' autonomy, offers instantaneous feedback, and minimizes speaking nervousness, which promotes improved fluency and pronunciation accuracy. However, there are limitations, such as trouble keeping up with complex conversations and challenges in comprehending non-native accents. According to the study's findings, Google Assistant significantly enhances the speaking skills of EFL students, although it works best when paired with conventional teaching techniques. These results highlight the potential for autonomous, accessible, and engaging learning experiences that AI-driven learning technologies may provide in language teaching
Exploring the dynamics of English language e-learning: A case study of motivations, beliefs, and strategies among advanced English as a foreign language university students
No full textIn a rapidly evolving e-learning landscape, where learner-centered pedagogy is increasingly embraced, understanding the factors influencing English language acquisition in digital environments is crucial. This mixed-methods study, primarily employing a qualitative approach, investigated the complex interplay of technological self-efficacy, intrinsic motivation, and e-learning strategy use among 31 advanced English language learners in Ben-Suef University. The findings revealed that while students’ internal factors like technological self-efficacy and motivation influenced their e-learning approach and engagement, they did not guarantee success and were, in fact, strongly determined by the learning context itself. The study further highlighted the importance of a well-designed e-learning environment, including structured learning objectives, frequent opportunities for interaction, and assessment approaches that support learning, as key factors for maximizing learners’ success. These findings emphasize the need for educators to move towards a more holistic approach that considers the complex interaction of learner attributes and the learning environment in the development of effective e-learning programs. Future research should explore these findings across a range of different types of learners and in different contexts to further develop our understanding of the most effective ways to support language learning in online environments
Mapping intercultural trajectories: Chinese secondary school learners’ standpoints on the cultivation of intercultural awareness in English education
No full textWith the intensification of globalisation and international exchange, intercultural communicative ability has become a focal point in English as a foreign language education in Chinese secondary schools. However, recent studies have indicated that the developmental construct of intercultural awareness is sometimes conflated with intercultural communicative competence. This leads to ambiguity in defining appropriate learning objectives. Using a sequential explanatory research design, this study surveyed 200 learners, followed by an interview with three learners. Questionnaire data were summarised using descriptive statistics, and thematic coding was used for analysing the interview transcripts. The results indicate that learners have positive attitudes towards cultural diversity (mean = 4.12) but fairly poor cultural knowledge (mean = 2.73) and low behavioural engagement (mean = 2.45). The thematic analysis highlights three barriers: a persistent grammar–translation orientation reinforced by exam pressure, fragmented “culture bites” offering little communicative value and showcase lessons disconnected from daily practice. The results highlight a disconnect between what the national curriculum aspires to achieve and what actually happens in classrooms. The material should include dialogue and recommendation-based materials and need to be supplemented with reflective journals and performance-based tasks to enable reflection and to promote aspects of authentic cultural interaction. Thus, it can enhance the development of intercultural awareness and provide some practical implications for promoting intercultural learning in Chinese secondary education
Minds vs machines: A comparative study of AI and teacher-generated summaries in ELT
No full textThis study investigates the differences between human-generated and AI-generated summaries in a remote English as a Foreign Language (EFL) lesson setting, addressing the research problem of how each approach captures and interprets lesson content. Utilizing Zoom-AI as the AI summarization tool, the study compares its output with summaries created by ten human educators. Each participant summarized the same lesson, providing a basis for direct comparison. The methodology involved qualitative analysis, focusing on aspects such as content comprehensiveness, pedagogical judgment, contextual understanding, and the recognition of classroom dynamics. The key findings have revealed that while the AI-generated summary is significantly more efficient in capturing the content, it lacks depth in educational insights and contextual nuances. Conversely, human-generated summaries appear to have provided richer educational judgments and a better understanding of classroom interactions but sometimes deviated from the core content, decreasing their educational value. The study suggests a complementary approach, integrating AI’s efficiency with human expertise through a human-in-the loop system to enhance the overall quality and utility of educational summaries. These results have important implications for integrating of AI in educational settings, highlighting the potential for AI to assist educators and the irreplaceable need for the nuanced understanding and contextual interpretation that human educators provide
Investigating a case study of self-instructed language learning with ChatGPT
No full textBased on the concept of “learner agency”, this single case study examines the self-instructed language learning process of a language learner with ChatGPT since May 2024. To serve the purpose of the study, qualitative data were collected through a semi-structured interview, the participant’s chat logs with the bot, and his learning diary. The analysis of collected data revealed (1) factors that led to the learner’s informed decision to incorporate ChatGPT as a primary learning tool into his self-practice for an international standardized English test, (2) how the tool was utilized to serve different learning purposes, and (3) the main challenges the learner encountered during that process. The findings provide implications for language learning approaches with transformative artificial intelligence (AI) technologies while emphasizing the importance of open discourse on AI’s integration into education and of training on self-study skills for learners
Integrating affective knowledge into TPACK: A new visual representation
No full textThis invited review critically examines the Technological Pedagogical Content Knowledge (TPACK) framework and argues for the integration of Affective Knowledge (AK) as a foundational component in technologically mediated pedagogy. Drawing on recent scholarship in emotional and teacher education, the article identifies a persistent gap in how TPACK conceptualizes the affective experiences of educators, particularly in the context of emerging technologies and digital learning. Building on McLay and Reyes Jr.’s (2024) TAPACK model, we propose a new visual representation that retains Contextual Knowledge while embedding Affective Knowledge across all TPACK domains. This reimagined model acknowledges that emotions, values, and moods are not peripheral but central to how teachers engage with technology, make pedagogical decisions, and navigate professional identity. We conclude with implications for teacher education, calling for emotionally informed professional development and a shift toward more humanizing approaches to technology integration
Utilizing an AI-CEFR checker: What is the efficacy for utilizing CEFR results for first year university students?
No full textWe investigated a text analyzer tool that provided Common European Framework of Reference for Languages (CEFR) level results for supporting language activities in two communication classes. In one class, students self-evaluated their language in formative assessment (FA) tasks and in the end, completed a survey of their experiences, which we evaluated. Students demonstrated insights into the thought process behind their written language and their motivation to evaluate their written English. They did this with the aim of improving their own language use and developing their language to achieve CEFR-J (Japanese version) based objectives. In class two, we applied the analyzer to video presentation transcripts for determining summative assessment (SA). Findings showed future potential for using this tool for grading and designing resources for CEFR-J activities and level-specificity. We concluded that Artificial Intelligence (AI)-linked CEFR-J based activities and task-based learning showed potential for further AI-language research
Generating discussion: Using ChatGPT to foster critical thinking skills
No full textCultivating critical thinking (CT) skills has become standard practice in education in Japan at the behest of many institutes and Japan's Ministry of education, culture, sports, science, and technology (MEXT, 2023). However, recent developments in generative artificial intelligence (AI) have left many educators to freshly consider how to encourage creativity and critical thinking in a world with such powerful and readily available AI like ChatGPT. However, by exposing students to the realities of ChatGPT and educating them on how it can be used, AI can be a tool to foster CT skills (Chang et al., 2021). This article outlines the procedure, impressions, and considerations of a classroom practice in which English-language students analyzed discussion questions created by ChatGPT. Students were required to use higher-order thinking skills by considering the significance, role, and qualities of thought-provoking discussion questions and evaluating generated questions against these criteria. Beyond encouraging CT, the activity highlighted its necessity when adopting new, exciting technology
The successful use of AI for English teachers’ professional development
No full textTeachers are required to develop their professional capabilities. However, in practice, many problems affect teachers’ professional development (TPD), such as overflowing administrative tasks, the lack of competence to integrate technology, and the lack of time allocated for continued professional development. Nowadays, the use of artificial intelligence (AI) is considered a way to solve these problems. This research aimed to investigate how AI is used in TPD. This qualitative case study design involved six in-service teachers who have joined the teachers’ professional education program in the Indonesian context. The findings indicate that AI provides an inclusive basis for transforming TPD for several reasons. For example, AI supports teachers’ personality competence (commonly known as professional conduct) by helping lighten their administrative workload. AI assists teachers’ pedagogical competence by offering easy integration of technology. AI upgrades teachers’ professional competence by providing unlimited resources, especially related to online professional development courses. Lastly, AI intensifies teachers’ social competence by providing opportunities to connect with each other. This study implies that AI is important to use in today’s TPD due to its adaptability, compatibility, and flexibility. While this study references specific AI tools used in TPD practices like ChatGPT, Perplexity, and Google Sites, it did not conduct an in-depth analysis of any single AI system. It is recommended that further studies focus on a particular AI tool to better understand its impact on TPD