Artificial intelligence in higher education

Integrating Adaptive Artificial Intelligence in Secondary Education

This paper examines the role of artificial intelligence (AI) platforms in secondary education, as well addressing the limitations of a one-size-fits-all method of instruction. Post-pandemic, learning gaps continue to grow and classrooms and growing more diverse in addressing academic needs of students. Therefore, it is becoming more important to note students’ individual needs for learning. Drawing on recent research, this paper argues that AI systems improve academics by offering individualized instruction, real-time feedback, and self-paced learning methods while enabling teachers to monitor progress with real-time data. This paper further explores how this technology can reduce teacher workload, allowing them to devote more time to support students. Although there are still concerns about relying too heavily on technology, the increasing number in screen time, and cost of implementing this technology, current evidence suggests that adaptive AI is most effective when used to help rather than replace teachers. This paper concludes that AI should be viewed as a long-term investment in education that supports learning outcomes and reduces teacher burnout.  

AI FLUENCY FOR FUTURE HIGHER EDUCATION

Artificial intelligence (AI), digital technology, and agentic automation are transforming business, employment, and higher education. Based on Abdul Latif Abdul Rahman's IC-BESTS 2026 material and supported by recent Scopus-indexed literature, this conceptual article examines how higher education should prepare Generation Z for an AI-intensive labor market. The study uses a qualitative conceptual review by synthesizing presentation themes on Southeast Asian AI adoption, agentic AI, skill transformation, operational risks, and higher education strategy with academic studies on AI in education, AI literacy, ethics, assessment, and digital pedagogy. The findings indicate that higher education institutions must shift from producing graduates for routine clerical work to developing AI-fluent orchestrators who can prompt, critique, integrate, govern, and ethically collaborate with AI systems. The article proposes a four-pillar strategic blueprint: democratizing AI fluency across all faculties, redesigning learning workflows, elevating digital governance and ethics, and reforming traditional academic assessment. The implication is that universities must move beyond tool adoption toward curriculum-wide transformation aligned with industry, government, and social needs.

Research Trends of Artificial Intelligence in Learning for Elementary Education

A temporal shift toward generative AI and contextual inquiry as the most recent research concerns is confirmed, and the complete absence of publications from Africa, Latin America, and South Asia signals a critical equity gap in the global research agenda.

Artificial Intelligence in Higher Education: A Scoping Review of Applications, Challenges, and Policy Directions

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.

Artificial Intelligence and the Changing Aims of Higher Education

Utilization of Artificial Intelligence to Support the Learning Process in Higher Education

The development of artificial intelligence (AI) has significantly impacted the learning process in higher education. This study aims to analyze the use of artificial intelligence to support the learning process in higher education, including the forms of use, benefits, and challenges it poses. The study used a qualitative descriptive approach with a literature review method. Data were obtained from various scientific journal articles, books, research reports, and institutional documents relevant to the use of AI in higher education. Data analysis was conducted using content analysis by identifying, classifying, comparing, and synthesizing various previous research findings. The results show that AI can be utilized as a learning assistant, a supporter of personalized learning, a developer of teaching materials, a provider of feedback, an assessment supporter, and a tool to enhance student self-directed learning and creativity. The use of AI can also help lecturers increase efficiency in planning and implementing learning. However, the use of AI presents challenges such as information inaccuracy, technology dependency, violations of academic integrity, data privacy, bias, and the potential for a decline in students' critical thinking skills. Therefore, the use of AI in higher education must be carried out ethically, critically, responsibly, and human-centeredly through strengthening AI literacy, improving lecturer competency, institutional policies, and adjusting assessment systems. AI should be positioned as a tool to enhance the learning process, not as a substitute for lecturers or students' thinking processes.