generative ai

AI Harnessing in Language Learning: A Systematic Review of Opportunities for Innovation and Pedagogical Transformation

This research presents a systematic review of the use of artificial intelligence (AI) in language education, synthesising evidence on tools used for teaching and learning. The review encompassed empirical, conceptual and review studies identified from key education and language databases and is focused on AI use by language learners and teachers in both formal and non-formal contexts. The review is organised under five main dimensions: (1) stakeholder perceptions and readiness; (2) AI applications and associated technologies; (3) AI tools’ impact on language skills and affective factors; (4) pedagogical integration and instructors’ professional development; and (5) overall affordances/challenges and the future implications. The findings reveal that generative AI and conversational agents are increasingly becoming integral components in language education, utilised by educators to offer personalised feedback, adaptive practice, and student engagement and motivation. Evidence also indicates positive impacts regarding writing quality, oral performance, vocabulary, and academic motivation. However, the integration of AI is not universally beneficial: its value is heavily contingent upon learner proficiency, task design and teacher mediation, coupled with risks of learners’ over-reliance, diminished metalinguistic awareness, anxiety or threats to academic integrity. AI literacy, infrastructural and policy constraints, data privacy and bias, and geographic and linguistic inequities in evidence-based research are the most highlighted challenges necessitating system-wide planning of AI harnessing in education.

Dialogic encounters in the third space: Generative AI, hybridity, and English language teaching for adults from migrant and refugee backgrounds

This article examines the use of generative artificial intelligence (AI) in English language teaching for adults from migrant and refugee backgrounds through the theoretical lenses of Bakhtin’s dialogism and Bhabha’s notion of third space and hybridity. As generative AI platforms become increasingly embedded in educational contexts, there is an urgent need to move beyond instrumental conceptions of AI as a neutral tool and to interrogate the cultural, linguistic and ideological dimensions of human–AI interaction in language learning. Drawing on Bakhtin’s understanding of language as inherently dialogic and socially situated, and Bhabha’s theorisation of hybrid cultural spaces where new meanings are negotiated, this article argues that generative AI can function as a dialogic interlocutor within a productive third space, but only when deployed with critical pedagogical intent. The article reviews existing literature on AI in adult English language education, including recent empirical research on educator, learner, and leader attitudes toward generative AI in this sector, and establishes a theoretical framework grounded in dialogism and hybridity. It analyses the affordances, limitations, and dangers of generative AI in this context, with particular attention to diminished criticality, the erasure of embodied learning and creativity, and cultural homogenisation. The article concludes by proposing pedagogical approaches that foster critical AI literacy and preserve the multiplicity of human–AI collaborative possibilities.

Peer Review Report For: AI Tools and Grammatical Performance in Arabic: A Student Perspective [version 1; peer review: 3 approved]

Background This study investigates the impact of the latest AI-based technology, particularly; Generative AI (GAI), on the development of grammatical abilities among Arabic-speaking University graduates. Conducted at Al Ain University in the UAE, the study analyzes the different applications of Artificial Intelligence, including SIRI, Telegram, ALEXA, and ChatGPT, along with the LENGO application. Methods It employs several correlational methods such as correlation and multiple regressions, using SPSS, to analyze the results. Results Preliminary findings indicate a strong positive correlation between the use of GAI and the development of student’s grammatical abilities. The findings also demonstrate that the use of ChatGPT and Telegram applications, among other GAI tools, has statistically, significant, beneficial effects on the development of student’s grammatical skills. Recommendations The study recommends that future GAI tools be developed and tailored to include other less popular forms of the Arabic language, as well as to include more variety of structural complexities of the language. Finally, the Arabic language proficiency of students, and their career prospects, will be significantly improved by the complete integration of GAI tools into the educational curriculum.

The golden thread of AI subalternity: epistemic activism

There is a rising tide of initiatives countering predominant AI practices and narratives. The social and environmental consequences of AI-dedicated data centres; the death, injury and human displacement involving AI-enabled lethal autonomous weapons; and the corrosion of educational institutions via the adoption of generative AI tools are just a few targets of diverse initiatives taking a stance against AI. However, these initiatives are generally siloed; they do not constitute a single movement but a fragmented patchwork. In this paper, I draw on Gramsci’s Prison Notebooks to make the case for unity among those running such initiatives, whom I call “AI subalterns.” Drawing on literature on epistemic injustice, I confront the AI subaltern with “ruling AI authorities”; those from the ruling classes with the ability to speak about AI with authority and thus perpetrate epistemic injustice. I argue that epistemic activism constitutes a key weapon in the AI subaltern’s arsenal, and that recognising how it is wielded by peers may help develop a sense of political consciousness. I show how the resulting unity among AI subalterns meets the criteria Gramsci sets out when describing how subalterns have historically coordinated successful political uprisings.

Emotional Reliance on Artificial Intelligence: A Scoping Review of AI Companionship and Mental Health Implications

Background: Artificial intelligence (AI)-driven conversational systems are increasingly capable of simulating empathy, adapting to individual users, and fostering emotional bonds that blur the boundary between tool and companion. This scoping review maps the extent and nature of published evidence regarding psychological mechanisms underlying emotional reliance on AI chatbots and associated mental health implications. Methods: Conducted in accordance with PRISMA-ScR guidelines, we systematically searched PubMed/MEDLINE, PsycINFO, Web of Science, Scopus, and IEEE Xplore from database inception to March 2026. Two independent reviewers screened records and extracted data using the PCC (Population, Concept, Context) framework. Thematic synthesis was performed to map evidence across psychological, clinical, and developmental domains. Results: Of 1847 records identified, 46 studies met inclusion criteria. Key themes included: (1) the ELIZA effect as a foundational mechanism of human–AI attachment, with documented cases of severe dependency including fatal outcomes; (2) anthropomorphization and artificial intimacy fostered by adaptive, personalized AI design; (3) proposal of Generative AI Dependency (GAID) as a conceptual framework mapping onto behavioral addiction components, pending empirical validation; (4) particular vulnerability of adolescents and lonely individuals to exclusive affective bonds with AI; and (5) potential erosion of human relational capacities, empathy development, and tolerance for interpersonal complexity. Significant gaps were identified in longitudinal research, validated screening tools, and intervention protocols. Conclusions: Emotional reliance on AI represents an emerging clinical phenomenon with addiction-like features requiring specific diagnostic frameworks, evidence-based interventions, and ethical design guidelines. Future research should prioritize longitudinal studies examining developmental impacts and neurobiological investigations of AI-mediated reinforcement mechanisms.

THE IMPACT OF ARTIFICIAL INTELLIGENCE ON MARKETING STRATEGIES OF TRANSNATIONAL COMPANIES IN INTERNATIONAL BUSINESS

The article examines the impact of artificial intelligence technologies on the transformation of marketing strategies of transnational companies in international business. The relevance of the study stems from the rapid expansion of the global artificial intelligence market and the fact that marketing and sales have consistently remained among the business functions with the highest intensity of AI adoption worldwide. For transnational companies, which coordinate marketing activities across dozens of national markets with different languages, consumer cultures and regulatory regimes, artificial intelligence directly affects the classical dilemma of international marketing between standardisation and adaptation: the technology promises to deliver globally consistent brand communication that is simultaneously tailored to local audiences at a scale and speed unattainable for traditional marketing organisations. The article discusses the main directions in which artificial intelligence penetrates the international marketing activity of transnational companies, including hyper-personalisation of customer experience based on machine learning, generative production of advertising and communication content, restructuring of organisational models of marketing departments, and localisation of global campaigns for national markets. Particular attention is paid to the experience of leading transnational corporations in the consumer goods, digital services and e-commerce sectors, as well as to the organisational conditions under which investments in artificial intelligence translate into measurable economic outcomes. The study also addresses the risks accompanying the diffusion of the technology, including changes in consumer attitudes towards AI-generated advertising, reputational threats, and the new regulatory environment created by the European Union Artificial Intelligence Act for companies operating in the European market. The consequences of the uneven global distribution of AI infrastructure, investment and competencies for the competitive positions of companies from developed and developing economies in international markets are considered as a separate dimension of the problem within the field of international economic relations.

Creative agency on generative AI music platforms: Reframing artistic identity and the creative subject

Generative AI music platforms promise to facilitate creative production without advanced technical skills. This study analyzed an approximately 22,000-word corpus of interface texts, terms of use, marketing materials, and blog posts from Suno, Udio, AIVA, and Soundraw using Fairclough’s Critical Discourse Analysis and Lakoff and Johnson’s conceptual metaphor theory. It examined how platform texts construct power relations and attribute agency. Three tendencies emerged. The agency game denotes the tension between the creative agency attributed to users in interface discourse and the contractual limits imposed through licensing and ownership clauses. The illusion of transparency denotes the backgrounding of algorithmic operation behind metaphors of magic, tool, and partnership. The rhetoric of democratization reflects the ideological function of the “anyone can be a musician” framing, which may bear on how professional expertise is valued. Disclosure of training material was assessed at three levels of specificity. Three analytical units on two platforms described in general terms where training material was obtained, one under litigation and two as a commercial guarantee; none identified specific works or datasets, and none disclosed any consent, attribution, or compensation mechanism for the relevant rights holders. The findings indicate that these platforms do not eliminate creative agency but render it discursively ambiguous by offering users a symbolic creative subject position while obscuring the distributed agency underlying production.

A human knowledge–driven generative AI design approach for architecture and structure integration

Fostering SCALE habits of mind through AI-empowered arts-based pedagogy

Abstract The SCALE taxonomy offers a future-oriented framework of educational objectives for the age of artificial intelligence (AI). This conceptual paper asks how these objectives can be enacted through a pedagogy that remains embodied, creative, and connected to human life. We thus integrate SCALE with Arts-Based Pedagogy (ABP), drawing on embodied cognition to conceptualize ABP as a life-connected learning ecology organized through four interrelated dimensions: perception, representation, creative iteration, and resonance. Rather than fixed stages, these dimensions describe how artistic experience enables learners to notice lived phenomena, give ideas perceptible form, revise meaning through making, and reconnect creation with personal social life. Building on this conceptual integration, we propose the AI-empowered ABP for K-12 education and beyond. The pedagogy moves from sensorial perception and artistic representation to feedback and self-reflection, creative making and AI-empowered iteration, and sharing for resonance. We argue that AI may generate text, images, music alternatives, or feedback, but learners retain primary responsibility for intention, interpretation, judgment, and transformation. AI-empowered ABP therefore positions AI as a generative collaborator and facilitator within a human-led, life-connected process of meaning-making, through which SCALE habits of mind can be mobilized within shared inquiry.

From Social Media to Generative AI: The Layering of Digital Mediation in Algerian Consumers’ Food Choices and Shopping Experiences

This study investigates the role of artificial intelligence (AI) in consumers’ food-related decision-making and its relationship with established social-media-mediated practices in e-commerce. A cross-sectional survey was conducted in Algeria in 2025 and generated 223 valid responses. 39.5% of respondents reported using AI, with ChatGPT making up 87.5% of applications reported by AI users. AI users experienced greater satisfaction with AI-related food experiences than non-users (Mann–Whitney U = 7,840.00, p < .001). However, AI use was not significantly associated with food purchasing after social-media exposure (p = .987). Social-media-mediated food discovery and purchasing practices remained prevalent, with no evidence of displacement by AI in the present sample. The findings conceptualize AI-assisted food choice as an additional layer of digital mediation in an established multi-source consumption environment and contribute evidence on AI-augmented consumer behavior to the under-researched Algerian context.

How Generative AI Influences Learning Outcomes in Programming Education: A Three-level Bayesian Meta-analysis

Peer Review Report For: AI Tools and Grammatical Performance in Arabic: A Student Perspective [version 1; peer review: 3 approved]

Background This study investigates the impact of the latest AI-based technology, particularly; Generative AI (GAI), on the development of grammatical abilities among Arabic-speaking University graduates. Conducted at Al Ain University in the UAE, the study analyzes the different applications of Artificial Intelligence, including SIRI, Telegram, ALEXA, and ChatGPT, along with the LENGO application. Methods It employs several correlational methods such as correlation and multiple regressions, using SPSS, to analyze the results. Results Preliminary findings indicate a strong positive correlation between the use of GAI and the development of student’s grammatical abilities. The findings also demonstrate that the use of ChatGPT and Telegram applications, among other GAI tools, has statistically, significant, beneficial effects on the development of student’s grammatical skills. Recommendations The study recommends that future GAI tools be developed and tailored to include other less popular forms of the Arabic language, as well as to include more variety of structural complexities of the language. Finally, the Arabic language proficiency of students, and their career prospects, will be significantly improved by the complete integration of GAI tools into the educational curriculum.