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.
Abstract
This article presents a scoping review of the emerging transformative role of Artificial Intelligence (AI) in higher education. Using a Population-Concept-Context (PCC) review design, we focus on the implications of AI for three major stakeholder groups: students, educators and institutions. Based on academic studies and grey literature from 2010 onwards, the review covers AI technologies, including machine learning, natural language processing, intelligent tutoring systems, learning analytics, chatbots and generative AI, and examines their pedagogical, administrative and ethical impacts. We analyse stakeholder demand, teaching and learning innovations, AI literacy education, institutional implementation barriers, data privacy, algorithmic bias, academic integrity and policy governance. 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. The article concludes with best-practice and policy recommendations for responsible AI implementation and adoption in higher education.
It is concluded that AI should complement educators rather than replace them and that responsible implementation supported by institutional policies, faculty development, and ethical guidelines is essential for sustainable educational transformation.
Jestin James M· International Journal of Tec...· 0 citations
The rapid expansion of higher education enrolment has created unprecedented challenges in managing large classrooms, prompting institutions to explore artificial intelligence (AI) as a transformative solution. This systematic review, conducted in accordance with PRISMA guidelines, synthesises current research on AI applications in large-class management within higher education settings. A comprehensive search of academic databases yielded 47 studies that met the inclusion criteria, published between 2018 and 2024. Thematic analysis revealed five key domains: automated assessment and feedback systems, intelligent tutoring and personalised learning, student engagement monitoring, administrative task automation, and predictive analytics for student success. Findings indicate that AI technologies significantly enhance instructor efficiency, improve student engagement, and enable personalised learning at scale. However, implementation challenges, including technological infrastructure, faculty training needs, ethical considerations, and concerns about data privacy, emerged as critical barriers. The review identifies a notable gap between AI's theoretical potential and practical implementation in resource-constrained institutions. This study contributes to understanding how AI can address scalability challenges in higher education while highlighting the need for evidence-based implementation frameworks, ethical guidelines, and inclusive design principles. Recommendations for practitioners, policymakers, and researchers are provided to guide the responsible integration of AI in large classroom contexts.
Zaffar Ahmad Nadaf, S. Jamal· Journal of Education Method...· 0 citations
Artificial Intelligence (AI) is reshaping higher education through adaptive learning, intelligent tutoring, generative tools, learning analytics, research assistance and administrative automation. This structured narrative review synthesizes recent academic and institutional literature on the influence of AI on teaching, learning, research and university management. The evidence indicates meaningful potential for personalization, timely feedback, accessibility and operational efficiency, but also identifies risks involving inaccurate output, academic integrity, algorithmic bias, data privacy, unequal access and insufficient faculty preparedness. The review argues that AI should augment rather than replace educational judgment. Sustainable adoption requires clear governance, transparent assessment rules, faculty and student AI literacy, data protection, human oversight and regular evaluation of accuracy and equity. The paper also identifies the need for longitudinal research on learning outcomes and discipline-specific implementation.
Husna Sultana, Irfan Ahmed, Jeevan G· International journal of res...· 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
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
The study identifies a persistent fragmentation in existing research and proposes the Integrated Challenge Model for AI Curriculum Development (ICM-AI-CD), which conceptualizes AI integration as a dynamic socio-technical system comprising interdependent ethical-policy, pedagogical-design, and technical-institutional domains.
Abdul Malik· Applied Business: Issues &am...· 0 citations
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