In conclusion, AI is best understood as an amplifier of pedagogy, rather than a replacement for teachers or human judgment, provided the same ethical safeguards apply.
Artificial intelligence is best understood as an amplifier of pedagogy, rather than a replacement for teachers or human judgment, and its benefits are conditional on AI literacy, transparent governance, and equitable access.
D. Bîrsan· Journal of Non-Formal and Di...· 0 citations
Artificial Intelligence (AI) has brought about significant changes in the educational landscape, driven primarily by the advancement of generative models and the increasing availability of tools capable of supporting teaching and learning processes. This study aimed to analyze the main possibilities and challenges associated with AI in pedagogical practice through a structured narrative literature review. Searches were conducted in the Web of Science Core Collection, Scopus, ERIC, SciELO, and Google Scholar, prioritizing publications from 2019 to 2026, while earlier foundational sources were retained when methodologically or conceptually relevant. The final interpretive corpus comprised 31 core sources, including peer-reviewed empirical studies, systematic and scoping reviews, meta-analyses, and institutional guidance. Evidence was synthesized into four themes: evolution and educational applications of AI, pedagogical potential, ethical and institutional challenges, and the changing role of teachers. The literature identifies opportunities for personalized learning, pedagogical planning, accessibility, formative assessment, and teaching-material development, but also recurring concerns involving information reliability, academic integrity, privacy, algorithmic bias, digital inequality, and teacher preparedness. Recent evidence indicates that positive outcomes are heterogeneous and depend on pedagogical scaffolding, human verification, institutional governance, and AI literacy. AI should therefore be understood as a supportive educational technology rather than a substitute for teacher mediation. Its integration requires critical, ethical, and pedagogically grounded use that preserves student autonomy, assessment validity, and educational equity.
A. F. da Silva, Rosimeire Rozendo, Cristiane Aparecida Simão Silverio· Brazilian Journal of Science· 0 citations
It is suggested that AI is not meant to replace the linguistic, pedagogical, and intellectual involvement of the human factor during the mediation action, and a 5-dimensional framework for the responsible use of AI in EMI is proposed.
Bushra Shaukat, Majid Khan, M. Habib et al.· Research Journal of Human an...· 0 citations
The review shows that AI offers substantial potential for personalised learning, scalable feedback, administrative automation and curriculum innovation, but that effective integration requires transparent governance, educator training, reliable evidence, accessibility and a commitment to ethical and human-centred use.
Pu Chen, Sherry Bawa, N. Islam et al.· Higher Education Studies· 1 citation
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.
Iman El-Nabawi Abdel Wahed Shaalan, Ayman Shaaban Khalifa Ahmad· Journal of Language Teaching...· 0 citations
The findings reveal that GenAI can effectively improve teaching efficacy, enable personalised learning experiences, and streamline assessment procedures, however, its implementation also draws attention to concerns regarding academic integrity, data privacy, algorithmic bias, and ethical governance.
Xi Bi· Exploring Science Academic C...· 0 citations
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