Higher education through AI: a vision for student-centred learning

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The future of higher education is set for a groundbreaking transformation through the integration of artificial intelligence, where traditional textbooks, scheduled exams and rigid classroom structures will be replaced with AI-powered learning models. These models will provide a personalised, interactive and adaptive educational experience, ensuring students receive knowledge in a way that best suits their individual learning styles. This shift will redefine the roles of AI, students and teachers, creating an education system that is more efficient, inclusive and student-centred.

A fundamental aspect of this transformation is the introduction of AI Subject Models, which will store and provide academically verified subject content. These AI-driven models will ensure that all information presented is comprehensive, accurate and aligned with the desired academic standards. Their development will require collaboration between AI specialists and subject matter experts. In the natural sciences, experts will validate these models to ensure scientific accuracy. In the social sciences, where cultural, ethical and religious sensitivities play a role, regulatory bodies and socio-religious experts will ensure alignment with societal values. In the humanities, experts in literature, history and philosophy will guide content curation to foster critical thinking and preserve ethical dimensions.

AI Subject Models will also revolutionise student assessments. These models will generate customised student assessments by creating unseen questions of varying difficulty levels - easy, moderate and challenging. This process will be rigorously tested before deployment, ensuring fairness and accuracy. Once certified, AI Subject Models will autonomously generate unbiased, academically sound questions tailored to each student's progress.

To complement, an accompanying AI Learning Management System (AI-LMS) will act as an intelligent tutor, extending or replacing traditional classroom structures. Unlike conventional generative AI systems that passively respond to student queries, AI-LMS will proactively guide students through the curriculum at their own pace. It will dynamically present concepts using varied explanations and examples, adapting to each student's learning needs. If a student struggles, AI-LMS will break down topics into smaller parts and revisit prerequisite knowledge. Conversely, if a student grasps concepts quickly, AI-LMS will introduce advanced topics for further intellectual growth.

The AI-LMS will be configured by universities, allowing institutions to design and structure academic programs. Institutions will set curricula for individual courses and degree programmes using AI Subject Models. Educators can define the sequence of concepts, set learning outcomes and ensure students meet academic standards. The system will also provide tools to configure student evaluations. Universities can set grading schemes, determine question difficulty distribution and adjust evaluation frequency - whether after each concept, chapter or subject unit - ensuring flexible assessment methods.

This system will continuously track student progress, by presenting examination-style questions when students feel ready. By analysing learning speed and comprehension, the system will assess proficiency in real time, making evaluations more reflective of actual understanding rather than rote memorisation.

In addition to serving as a tutor, AI-LMS will also feature an intelligent intervention mechanism. If a student consistently struggles with a particular concept, the system will alert teachers to intervene. This will be particularly useful for working with students with diverse background, as is the case in universities such as UMT and GCU Lahore. It will identify students with learning disabilities or other unique challenges requiring personalised attention.

AI-LMS will not replace teachers but enhance their ability to support students who need additional guidance. While AI takes on the role of delivering instruction, generating assignments and evaluating student performance, teachers will shift their focus to mentorship and personal development. Their role will evolve from information providers to facilitators of critical thinking, problem-solving, creativity and ethical reasoning. They will facilitate students develop emotional intelligence, social skills and teamwork through group discussions, collaborative projects, one-on-one mentorship and extracurricular activities. This will ensure that education remains deeply human, with teachers focused on fostering a sense of belonging and emotional well-being among students.

Teachers will remain vital in guiding students' career paths, bridging classroom knowledge with real-world application. They will facilitate internships, projects and field experiences to boost employability. As AI becomes central to education, teachers will also mentor students on responsible AI use, digital citizenship and ethical decision-making.

Building such an AI-powered education ecosystem will require significant investment and collaboration across multiple sectors. The development of AI Subject Models and AI-LMS will necessitate the creation of a new industry segment, bringing together academia, AI specialists, publishers, universities and governments. Once AI Subject Models and AI-LMS platforms are developed, they will also require advancements to ensure that the AI-driven education system remains current, relevant and continuously improving.

Given the scale of investment required, leadership in this field is likely to emerge from two primary sources. Educational publishers may transition from producing textbooks to developing AI-powered subject models, assembling interdisciplinary teams to drive this transformation. Alternatively, AI technology companies may take the lead, integrating subject matter experts into their teams to ensure academic rigour while developing sophisticated quality assurance frameworks. Other stakeholders - such as private research institutions, well-funded universities and government agencies - may also contribute to the development of this initiative.

The education landscape is on the brink of a revolutionary transformation, driven by AI Subject Models and AI Learning Management Systems. The vision presented above eliminates traditional textbooks, classrooms and scheduled exams, replacing them with an AI-powered, student-centric learning experience. AI will provide precisely validated knowledge, adaptive assessments and continuous personalised learning, while teachers will take on the crucial role of mentors, nurturing students' problem-solving abilities, creativity, emotional intelligence and ethical reasoning.

This shift requires a cross-disciplinary effort between AI specialists, educators, regulatory bodies and policymakers. By embracing this AI-driven education model, we can create a future where learning is accessible, adaptive and deeply human - empowering students to not just acquire knowledge but develop the skills and values needed to become lifelong learners.