[Paper Review] Generative AI in Modern Education Society

Sanjay Chakraborty|arXiv (Cornell University)|Dec 10, 2024

Artificial Intelligence in EducationComputer Science7 citations

TL;DR

A literature review outlining how Generative AI (GenAI) fits Education 5.0, its potential, adoption challenges, and future research directions across teaching, learning, and research.

ABSTRACT

Transitioning from Education 1.0 to Education 5.0, the integration of generative artificial intelligence (GenAI) revolutionizes the learning environment by fostering enhanced human-machine collaboration, enabling personalized, adaptive and experiential learning, and preparing students with the skills and adaptability needed for the future workforce. Our understanding of academic integrity and the scholarship of teaching, learning, and research has been revolutionised by GenAI. Schools and universities around the world are experimenting and exploring the integration of GenAI in their education systems (like, curriculum design, teaching process and assessments, administrative tasks, results generation and so on). The findings of the literature study demonstrate how well GenAI has been incorporated into the global educational system. This study explains the roles of GenAI in the schooling and university education systems with respect to the different stakeholders (students, teachers, researchers etc,). It highlights the current challenges of integrating Generative AI into the education system and outlines future directions for leveraging GenAI to enhance educational practices.

Motivation & Objective

• Explain the evolution from Education 1.0 to Education 5.0 and the role of GenAI in this transition.
• Summarize how GenAI supports personalized, adaptive, and experiential learning in schools and higher education.
• Identify challenges and gaps in integrating GenAI into education and research ecosystems.
• Outline future directions and research opportunities for leveraging GenAI in Education 5.0 frameworks.

Proposed method

• Conduct a literature-based analysis of GenAI tools, models, and applications in Education 5.0.
• Synthesize case studies and theoretical perspectives on AI-driven teaching, learning, and assessment.
• Present a conceptual framework and future directions for GenAI integration in education systems.

Figure 1: Evolution of Education 1.0 to Education 5.0 in the context of AI

Experimental results

Research questions

• RQ1 How does the academic ecosystem integrate GenAI into teaching and learning?
• RQ2 How can stakeholder goals be achieved and adoption of GenAI in higher education be measured and communicated?
• RQ3 What are the main challenges of GenAI in the modern education system?
• RQ4 What future directions can enhance the impact of GenAI in education?

Key findings

• GenAI is seen as enabling collaboration between AI and humans, moving beyond simple automation.
• There are significant challenges related to privacy, integrity, bias, and social interaction that must be addressed.
• GenAI offers possibilities for personalized learning, rapid feedback, and data-driven instructional design, but requires careful integration and ethical considerations.
• Education 5.0 emphasizes lifelong learning, value-based education, and human-AI collaboration, supported by tools like LLMs, VR/AR, and adaptive platforms.
• Prompt engineering and memory/evaluation enhancements are important for effective GenAI deployment in education.

Figure 2: Transition in Learning Methodologies over the Past Years