Aug 2026· Revista de Estudos Interdisciplinares· Vol 25, pp. e3812· 0 citations
TL;DR
Analyzing the main pedagogical transformations associated with Generative AI, Learning Analytics, and learning personalization in higher education concluded that integrating these technologies has transformative potential when guided by ethical principles, qualified pedagogical mediation, and consistent institutional policies.
Abstract
The incorporation of Generative Artificial Intelligence (AI) into higher education has transformed pedagogical practices, particularly through the development of personalized strategies, educational data analysis, and the reorganization of teaching and learning processes. This study aimed to analyze the main pedagogical transformations associated with Generative AI, Learning Analytics, and learning personalization in higher education, highlighting their potential, challenges, and contemporary implications. An integrative literature review was conducted using the ERIC, Latindex, SpringerLink, and Miguilim databases, considering publications from 2021 to 2026 in Portuguese and English. Studies addressing generative technologies, adaptive learning, educational data analysis, and personalized learning pathways were analyzed. The findings indicated potential to expand learning individualization, support content production, facilitate feedback, improve assessment processes, and inform pedagogical decision-making. However, challenges related to academic integrity, privacy, information reliability, equity, AI literacy, and teacher training were also identified. It is concluded that integrating these technologies has transformative potential when guided by ethical principles, qualified pedagogical mediation, and consistent institutional policies.
Generative Artificial Intelligence (GenAI) has rapidly transformed higher education practices, creating new opportunities for pedagogical innovation while introducing complex challenges related to assessment validity, academic integrity, and institutional governance. However, existing studies remain fragmented across technological adoption, learning processes, assessment practices, and ethical considerations, limiting a comprehensive understanding of how GenAI can be integrated responsibly into higher education ecosystems. This systematic literature review aims to synthesize current evidence on the educational implications of GenAI by examining its influence on teaching transformation, student learning, assessment redesign, and academic integrity governance. Following the PRISMA framework, relevant studies were systematically identified, screened, and analyzed to reveal emerging patterns, challenges, and future research directions in GenAI adoption within higher education. The synthesis revealed four interconnected themes: (1) transformation of teaching practices through AI-supported instructional design and efficiency improvement, (2) enhancement of student learning through personalization and self-regulated learning support, (3) evolution of assessment toward authentic and competency-oriented approaches, and (4) development of institutional governance frameworks addressing ethical, privacy, transparency, and integrity concerns. The findings indicate that successful GenAI integration requires a balanced approach combining technological capability, pedagogical redesign, and responsible governance. This review contributes to Artificial Intelligence in Education (AIED) research by proposing an integrated perspective for sustainable GenAI adoption and identifying priorities for future empirical investigations.
Syusinka Rahmatika, Martanto, Ryan Hamonangan· Immortalis Journal of Interd...· 0 citations
The findings suggest that the pedagogical transformation enabled by artificial intelligence depends less on the sophistication of the technologies themselves and more on the institutional capacity to establish curricular guidelines, implement ethical policies, and foster critical digital competencies among both teachers and students.
Félix Antonio Díaz, Juan Carlos Toribio Fernández, J. Martínez-Alonzo et al.· MENTOR revista de investigac...· 0 citations
AI has considerable potential to complement conventional pedagogical practices and contribute to more adaptive and student-centered higher education, provided that its implementation is guided by sound pedagogical principles and responsible governance frameworks.
Sugandha Sahay, Gouranga Patra· International Journal for Sc...· 0 citations
This document outlines the conceptual, theoretical, and methodological underpinning of the AI-Augmented Pedagogy Integration Model (AAPIM), which has now been further supported by a growing evidence base of 2025–2026 meta-analyses and systematic reviews.
Ahnaf Afsin, Rumaysha Tahan Towaa, Kasif Suhail Ayate et al.· Frontiers in Computer Scienc...· 0 citations
This paper examines the existing research on generative artificial intelligence (GenAI) in language education and highlights its potential to reshape teaching practices, learner engagement, and pedagogical design. By leveraging co-word analysis and BERTopic modeling on 908 publications from 2023 to the end of 2025, the article traces thematic patterns and conceptual developments in the GenAI field. The co-word analysis identifies key clusters at the intersection of GenAI and English language instruction, including its use in academic writing, translation, assessment, and learner-centered pedagogy. These themes demonstrate the critical role of GenAI in enabling personalized feedback, adaptive learning environments, and enhanced teacher–student interaction. The application of BERTopic modeling adds a semantic layer to this analysis and reveals diverse topics such as AI-assisted writing, teacher engagement with AI tools, emotional and motivational dynamics, and technology acceptance among learners. Results also indicate a progression from broad pedagogical experimentation toward more focused inquiries into learner psychology, ethical use, and professional development. This trend reflects the maturation of GenAI applications in both formal and informal educational contexts. The findings offer implications for language educators, curriculum designers, and policymakers by highlighting the need to integrate GenAI through pedagogically grounded, ethically responsible, and learner-centered approaches. They also suggest that future language education practices should combine AI literacy, transparent assessment policies, and teacher professional development to support effective and equitable GenAI adoption. Ultimately, the article positions GenAI as a transformative force in language education that offers technological innovation and new frameworks for inclusive, responsive, and emotionally attuned instruction.
Abderahman Rejeb, K. Rejeb, Heba F. Zaher et al.· Quality & Quantity· 0 citations
Across the reviewed studies, generative AI was found to enhance language learning through personalized feedback, increased learner autonomy, and greater learning engagement, but concerns regarding academic integrity, AI literacy, ethical issues, and institutional readiness remain significant challenges to its sustainable implementation.
N. H. Hong Nhung· International journal of soc...· 0 citations