A Comprehensive Review on Generative AI for Education

Abstract

Artificial Intelligence (AI) has immense potential for personalized learning experiences, content generation, and vivid educational support. This paper delves into generative AI (GAI) and its potential applications within GAI, specifically mentioning generative adversarial networks (GANs). The article delves into the transformative impact of GAI in education, underscoring its expertise in creating diverse instructional materials, from texts and images to videos. Adaptive learning, one of the chief abilities of GAI, has been highlighted, emphasizing its capability to select content customized to individual student profiles, learning habits, and preferences. The paper further explores the fusion of GAI with innovative education systems, highlighting how these models can mimic conversational interfaces, promoting an engaging, customized learning journey. The exploration doesn’t stop at the benefits; it delves into challenges like ensuring data privacy, mitigating biases, and ensuring accountability in AI-driven educational systems. The conclusion contemplates the potential limitations and assurances of embedding GAI within educational setups. An appeal has been made for more profound research and enhancement of AI’s educational function. The intersection of pedagogical insights and effective human-AI collaboration is pivotal in this journey. This paper serves as a compass, guiding educators, researchers, and policymakers toward harnessing GAI’s potential to sculpt enriched, immersive educational landscapes.

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