Learner-generated contexts in the elementary EFL classroom: A GenAI-assisted framework

This paper investigated the difference in the opinions of lecturers and students on the use of generative AI (GenAI) systems in teaching and learning a foreign language. The study also sought to establish the perception and attitude of the foreign language students toward using GenAI in learning the foreign language. The current study employed a quantitative research approach to evaluate the current sample of lecturers and students’ attitudes toward the implementation of Generative AI (GenAI) systems in teaching and learning foreign languages. The sample involved 45 lecturers and 493 postgraduate students in foreign languages from Saudi Arabia. The survey questionnaire contained items based on the UTAUT model, which includes 15 items, of which four are based on performance expectancy, four on effort expectancy, three on social influence, and four on facilitating conditions. The survey took the form of Google Forms shared on social media and email. The data collected was analysed using descriptive statistics, and t-test results were obtained to see the overall influence of two sets of behavioural perceptions of the two groups. A comparative analysis of the attitudes reveals that lecturers had a positive optimism with relative efforts and facilitating conditions needed for the adoption and integration of GenAI in FL education (Mean = 4.29, SD = 0.79, Variance = 0.81, t = 2.45, p= 0.015). On the other hand, the students showed positive acceptance, usage and application of GenAI models in facilitating their academic engagements in FL education (mean = 7.58, sd = 0.42, variance = 0.18, t = 12.75 p = 0.001). It is thus concluded that while university lecturers are careful to fully accept and integrate GenAI models in FL teaching, their students overwhelmingly accept GenAI.

The exponential emergence of generative AI (GenAI) tools, such as ChatGPT, is reshaping language learning in higher education. However, little is known about the psychological and perceptual factors that sustain students’ long-term use of these technologies. This study develops and empirically tests an integrated framework combining Self-Determination Theory (SDT) and the Technology Acceptance Model (TAM) to explain continuance intention and actual usage of GenAI tools in English as a Foreign Language (EFL) learning. Using a descriptive cross-sectional survey design and non-probability convenience sampling, data were collected from 451 Malaysian university students (Generation Z). Partial Least Squares Structural Equation Modelling (PLS-SEM) and PLSpredict were used to examine direct and mediated effects of autonomy, competence, and relatedness on perceived usefulness and ease of use. The findings confirm that both motivational and technological constructs significantly influence continuance intention, which in turn predicts actual behaviour. By including actual usage, the study addresses the intention – action gap in EdTech research. Situated in a Southeast Asian context, the findings offer actionable insights for culturally responsive, learner-centred AI-enhanced EFL programs. This research is relevant to policymakers, instructional designers, and developers seeking to support the adoption of sustainable GenAI in language education.

This study aims to produce empirical insights into how students in Chinese higher vocational colleges view and use generative AI in EFL learning. This quantitative study uses the technology acceptance model (TAM) to analyze EFL learners' attitudes, intentions, and behaviors about utilizing generative AI in EFL learning with Structural Equation Modelling. 911 English as a foreign language(EFL) learners completed a questionnaire measuring personal innovativeness, perceived ease of use, perceived usefulness, attitude, behavioral intention, and actual use. Structural equation modeling investigations show that Perceived Ease of Use does not directly predict learners' attitudes but can impact them through the full mediator Perceived Usefulness. Positive attitudes towards generative AI and personal innovativeness are associated with increased behavioral intention. Behavior intention predicts the actual application of generative AI in English learning. This study demonstrates the effectiveness of generative AI as a language-learning tool for EFL learners, promoting personalized and sustainable learning.

Purpose Recent advances in generative AI (GenAI) are transforming multiple aspects of society, including education and foreign language learning. In the context of English as a Foreign Language (EFL), significant research has been conducted to investigate the applicability of GenAI as a learning aid and the potential negative impacts of these technologies. However, there are few formalised frameworks available to support the integration and development of AI literacy skills for EFL learners. Design/methodology/approach In this conceptual article, we demonstrate the way in which an existing framework, which is designed for integration of AI into educational assessment (the AI Assessment Scale), can be adapted to structure classroom activities, curricula and assessment in the context of EFL writing and translation. To achieve this, we contextualise the approach by firstly reviewing the extant literature on GenAI and EFL writing. Following this, we focus on Levels 2, 3 and 4 of the AI Assessment Scale (AIAS) and explore possible pedagogical adaptations to suit an EFL writing context. At the same time, we reflect on the possible advantages and limitations of this approach. Findings We argue that for pedagogy to succeed in a digital world, educators in the EFL field must not turn away from the affordances offered by AI technologies. At the same time, abundant caution is needed given the lack of empirical data on how these technologies may impact learning in the long term. To this end, we contend that a balanced approach, which clearly describes and communicates how AI may be used in learning activities, can be beneficial for both educators and learners in the EFL classroom. Practical classroom implications are included for writing and translation so teachers can apply the patterns immediately. Originality/value The adaptation of the AIAS from an assessment redesign tool to a framework for structuring EFL pedagogy is the core contribution and innovation in this article. The use of this framework has significant implications for classroom practice in the age of AI, as it enables a structured redesign of existing pedagogical activities in light of new technologies.

Abstract: Augmented Human Intelligence (AHI) represents a paradigm shift in human-AI collaboration, leveraging Generative AI, Quantum Computing, and Extended Reality (XR) to enhance cognitive capabilities, decision-making, and immersive interactions. Generative AI enables real-time knowledge augmentation, automated creativity, and adaptive learning, while Quantum Computing accelerates AI optimization, pattern recognition, and complex problem-solving. XR technologies provide intuitive, immersive environments for AI-driven collaboration, bridging the gap between digital and physical experiences. The convergence of these technologies fosters hybrid intelligence, where AI amplifies human potential rather than replacing it. This research explores AI-augmented cognition, quantum-enhanced simulations, and AI-driven spatial computing, addressing ethical, security, and societal implications of human-machine synergy. By integrating decentralized AI governance, privacy-preserving AI techniques, and brain-computer interfaces, this study outlines a scalable framework for next-generation augmented intelligence applications in healthcare, enterprise intelligence, scientific discovery, and immersive learning. The future of AHI lies in hybrid intelligence systems that co-evolve with human cognition, ensuring responsible and transparent AI augmentation to unlock new frontiers in human potential. Keywords: Augmented Human Intelligence, Generative AI, Quantum Computing, Extended Reality, XR, AI-driven Cognition, Hybrid Intelligence, Brain-Computer Interfaces, AI Ethics, AI-enhanced Learning, Spatial Computing, Quantum AI, Immersive AI, Human-AI Collaboration, Ethical AI Frameworks.

This qualitative study explores the potential of Generative AI (GenAI) in developing culturally responsive English as a Foreign Language (EFL) curricula for pre-teens (ages 9–12) in the MENA region, including Iran, Iraq, Kuwait, and Egypt, with a focus on cultural sensitivity. Through a semester-long intervention, 57 EFL teachers observed 5637 learners engaging with AI-generated materials. Data from online focus-group interviews identified three core outcomes: first, GenAI facilitated the creation of culturally nuanced resources, including bilingual storybooks, bicultural calendars, and intercultural communication handbooks; second, learners showed marked improvements in language proficiency, cultural awareness, critical thinking, intercultural communication, and academic engagement; third, challenges emerged, such as cultural oversimplification, algorithmic bias, and overreliance on AI-generated content. The study advances ethnolinguistic research by proposing frameworks for culture-language integration and hybrid curriculum design, emphasising GenAI's capacity to enhance inclusive pedagogy while underscoring the necessity for content validation and contextual adaptation in diverse educational settings.

AI-powered EFL pedagogy: Integrating generative AI into university teaching preparation through UTAUT and activity theory

The use of information and communication technology greatly improved foreign languages teaching and learning. Learning management systems, such as Moodle, used to create and deliver courses, facilitate e-learning in different types of educational institutions. Blended learning as a combination of face-to face and e-learning is conducive to deep learning. We designed a new course “Teaching English as a foreign language to learners with special educational needs” to provide students enrolled in a master’s programme – pre-service English teachers, with an opportunity to enhance their language and professional skills as well as to develop their learner autonomy through meaningful learning experiences blending learning can supplement. We considered micro, meso and macro levels of the course implementation and functioning. In this paper we describe the context in which the course is introduced by providing information about the setting, the curriculum, the need for including this course in the master’s programme at the faculty of foreign languages. We also outline the way the course is designed, including its structure, particular tasks and assessment procedures and present students’ feedback about the impact of the course on their foreign language skills and learner autonomy. The results indicate that blended learning is an effective tool for development of pre-service teachers’ English language skills and learner autonomy. The findings of the study can be applied by faculty and administrators involved in the design of courses at tertiary level.

The past decade has witnessed a plethora of research to study the relationship between reading strategies and reading comprehension, but few studies have examined the brain functionality; more specifically the relationship between hemispheric dominance and reading strategies. Therefore, this study aimed to investigate whether there would be any relationship among elementary English as a Foreign Language (EFL) learners’ hemispheric dominance (Left, Right and Whole-brained dominance), their reading strategies, and reading comprehension. To this end, 67 elementary EFL students were selected based on convenience sampling. After determining the participants’ brain dominance, they completed a survey of reading strategies (RS) in order to identify their general preferences of reading strategies. Then a Reading Comprehension Test (RC) was administered to examine the students’ reading comprehension proficiency. The results demonstrated that most of the students were left-brain who generally preferred to employ problem-solving strategies (PROB). Furthermore, no significant relationship was found between hemispheric dominance, reading strategies, and reading comprehension of Iranian elementary EFL students. The results had also some implications for teachers stating that they should consider their students’ individual differences in terms of hemisphericity and adopt or balance their teaching techniques based on the students’ brain dominance types (learning styles and strategies) or at least to be sensitive to that.

Family factors significantly influence the development of critical thinking (CT) dispositions. Yet, the dynamics of this influence among foreign language (FL) learners remain underexplored, with potential moderating factors still unclear. Building on social capital theory, social support theory, and ecological systems theory, this study explored this relationship among FL learners and further investigated whether teacher support moderates this connection. A total of 16,006 secondary students from China participated in the study, spanning grades 7 through 12 (M age = 14.842 years, SD = 1.416). Data were collected using student-reported CT disposition scale, FL teacher support scale, and SES questionnaire. Multiple regression analysis revealed a positive relationship between SES and CT dispositions of FL learners. Furthermore, moderation analysis showed that teacher support positively moderated this relationship. That is, higher levels of teacher support enhanced the positive effect of SES on CT dispositions among FL learners. This research has both theoretical and practical implications for the development of CT dispositions among FL learners.

This paper examines how teachers’ ability to create collaborative and inclusive classroom environments can enhance learners’ autonomy and motivation in English as a Foreign Language (EFL) and English for Specific Purposes (ESP) contexts. It explores pedagogical strategies that empower learners by supporting their autonomy, engagement, and motivation. It also emphasizes the importance of teaching practices that are responsive to culture and considers how students’ cultural backgrounds influence their learning and motivation. Adopting a mixed-methods approach, this study combines a meta-synthesis of existing research to provide an overview of key theoretical frameworks in learner motivation and autonomy, alongside classroom observations drawn from the author’s teaching experience. The paper also presents strategies for balancing teacher support with learner autonomy. Finally, it offers practical recommendations for EFL/ESP teachers who wish to create motivating learning environments for their students.

The fast and increasingly natural adoption of handheld devices such as smartphones and tablets into everyday life is a rapidly growing social phenomenon which is also believed to have vast potential for foreign language learning. The small-scale study presented in this article contributes to the discussion of whether handheld devices should be further integrated into or eliminated from the classroom by presenting part of the results of a small-scale study conducted in a German secondary English as a foreign language classroom. The study examined the impact of a mobile vocabulary learning app on secondary school students’ vocabulary performance, also giving some indications about the students’ development of foreign language learner autonomy. Although the results of the study showed an unexpectedly limited use of the app, they allow assumptions to be made about the reasons which prevented students from using the app more frequently which can influence future researchers’ and practitioners’ app choices. The first section of this article briefly outlines the theoretical framework of the study, particularly focussing on the potential of computer-assisted and mobile-assisted language learning for enhancing students’ foreign language skills and learner autonomy. The ensuing section then provides some background on investigating students’ foreign language vocabulary learning. This is followed by a presentation of the research design, including the main features of the app (Socrative) used in this study. The next section then critically discusses some of the major research results. The contribution concludes by summarising some of the outcomes of the study and outlining some gaps for further research.

This research investigated the effects of generative AI on affective factors (motivation, interest, and confidence) of English as a foreign language (EFL) learners enrolled in Korean university-level general English courses. During the Spring 2024 semester, this study involved 89 participants exposed to a generative AI-based instruction model. Compared to traditional methodologies, these results highlight the potential effectiveness of generative AI-based English instruction for writing and speaking in supporting linguistic proficiency and positive affective attitudes toward language learning among EFL learners.

Anecdotal evidence suggests that the use of GenAI has both advantages and disadvantages in students’ learning and assessment processes. However, despite the increasing volume, few studies have been conducted to explore English as a Foreign Language (EFL) students’ perceptions towards language learning and assessments pre and in GenAI era. Therefore, employing a qualitative research approach, mainly through interviews and thematic analysis, the study aims to discover in-depth information about features and patterns of tertiary EFL students’ perceptions and perception changes, regarding the impact of GenAI on language learning and the fairness of assessments in China. Findings of the study reveal that students do not embrace the idea of banning the use of GenAI in their learning and assessment, while they believe this could lead to not only advantages but also negative outcomes. Their perception towards assessment has shifted after the emergence of GenAI, compared with pre-GenAI era. To mitigate the negative consequences of GenAI in learning and assessment, participants presented some key suggestions. Tertiary education policy makers could draw on the findings of the study to create well-informed guidelines and strategies to effectively and ethically implement the use of GenAI tools, ultimately improving the teaching and learning experiences in Chinese and worldwide tertiary education sectors.

We present a collaborative learning environment called iCycle (Intelligent Computer-supported hybrid Collaborative Learning Environment) along with enabling Artificial Intelligence (AI) applications. The research is derived from a collaboration of four universities offering six cyber-learning courses in Computational Data-enabled Science and Engineering (CDSE) emphasising collaborative Project-Based Learning (PBL) and data-driven learning assessment to promote deep-learning. Relevant data sets for evidence-based learning assessment and iterative course improvement may grow in size to terabytes of information in the near future. We developed AI applications for collecting teamwork data, automating data analysis, and for formative learning assessment.