Jul 2026· MENTOR revista de investigación educativa y deportiva· 0 citations· 22 references
TL;DR
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.
Abstract
The aim of this study was to analyze the opportunities, risks, and pedagogical transformations associated with the use of artificial intelligence in higher education learning processes. A theoretical review based on documentary analysis was conducted through the critical examination and comparative synthesis of scientific literature published between 2021 and 2026 in databases such as Scopus, Web of Science, and ERIC. The analysis explored the main dimensions through which artificial intelligence is reshaping university teaching and learning, including personalized learning systems, generative AI tools, algorithmic assessment, and emerging ethical and epistemological challenges. The reviewed literature revealed that artificial intelligence offers significant benefits depending on institutional contexts and the pedagogical approaches guiding its implementation, while also posing risks related to academic dependency, superficial learning, and assessment bias. The opportunities and risks identified represent an interdependent tension that influences the effective integration of artificial intelligence into higher education. 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.
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.
Rosiane Almeida Minet Marsaioli, Tiago Mendonça Scavone, Francisco Pujol et al.· Revista de Estudos Interdisc...· 0 citations
The paper analyzes key directions of AI integration into educational practice, including adaptive learning systems, intelligent tutoring, automated assessment, and personalized learning pathways, and contributes to the development of a structured approach to integrating artificial intelligence into higher education.
Нурлан Серикович Мукатаев –, Zh.Zh, T. K. Bagisov⃰ et al.· Bulletin of Shakarim Univers...· 0 citations
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
Abstract
Objective: This systematic review examines the impact of Artificial Intelligence (AI) on commerce education in higher education by synthesizing existing empirical evidence on its opportunities, challenges, and future implications for teaching and learning.
Design: A systematic literature review design was adopted following the PRISMA 2020 guidelines. Relevant peer-reviewed studies published between 2020 and 2026 were identified from major academic databases, including Scopus, Web of Science, Google Scholar, ERIC, and IEEE Xplore.
Methods: Studies were selected based on predefined inclusion and exclusion criteria focusing on AI applications in commerce and business education. Data were extracted and analyzed using a thematic synthesis approach to identify major patterns related to AI adoption, educational benefits, implementation challenges, ethical concerns, and future research directions.
Results: The review indicates that AI technologies, including generative AI tools, intelligent tutoring systems, and adaptive learning platforms, have significantly enhanced personalized learning, student engagement, research productivity, and digital competency among commerce students. However, challenges such as academic integrity, algorithmic bias, data privacy, faculty preparedness, and overdependence on AI-generated content remain significant barriers to effective implementation. Ethical governance and institutional readiness emerged as critical factors influencing the successful integration of AI in commerce education.
Conclusion: Artificial Intelligence has the potential to transform commerce education by improving learning outcomes and fostering innovation in teaching and assessment. Nevertheless, its successful adoption requires comprehensive institutional policies, faculty training, ethical guidelines, and responsible AI governance to ensure sustainable and effective implementation in higher education.
R. S, N. B., Sowmya K et al.· International Journal For Mu...· 0 citations
Background: The rapid advancement of Artificial Intelligence (AI) has significantly transformed higher education by influencing teaching practices, learning processes, research activities, assessment systems, and institutional management. Although AI provides substantial opportunities for improving educational quality and efficiency, its implementation also introduces complex challenges related to academic integrity, ethical governance, data privacy, algorithmic bias, and institutional readiness.
Aims: This study aims to critically examine the role of AI in higher education by analysing its contribution to pedagogical innovation, identifying ethical and institutional challenges, and exploring future governance strategies for responsible AI adoption within university contexts.
Method: This study employed a critical literature review approach by analysing relevant scientific publications on AI applications in higher education. The literature was identified from academic databases and examined using qualitative thematic analysis to synthesize major patterns related to AI benefits, risks, and future implementation directions.
Results: The findings reveal that AI supports higher education through personalized learning, intelligent tutoring systems, automated assessment, learning analytics, academic support services, and improved institutional decision-making. However, effective AI integration requires addressing concerns regarding academic misconduct, privacy protection, unequal technological access, algorithmic fairness, and the preparedness of educators and institutions. The review further highlights that responsible AI implementation depends on ethical policies, AI literacy development, teacher professional development, and human-centered governance frameworks.
Conclusion: AI should be positioned as a complementary educational resource rather than a replacement for human expertise. Sustainable AI adoption in higher education requires a balanced approach that integrates technological innovation, ethical responsibility, institutional governance, and continuous adaptation to ensure inclusive and meaningful educational transformation
Therese Kabala - Mwagalwa· Journal of Literacy Educatio...· 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