The landscape of education is undergoing a profound and unprecedented transformation, fueled by the rapid evolution of educational technology and artificial intelligence (AI). No longer peripheral, these innovations have become central to how learning is designed, delivered, and evaluated across diverse educational contexts. AI-powered tools and digital platforms offer a range of opportunities from enhancing instructional quality and administrative efficiency to enabling more flexible, inclusive, and personalized learning experiences that respond to the varied needs of 21st-century learners.Yet, alongside these advancements emerge pressing questions that demand critical attention. The increasing reliance on algorithm-driven systems and digital infrastructures challenges traditional pedagogical models, often reducing opportunities for meaningful human interaction and raising ethical concerns regarding surveillance, data privacy, algorithmic bias, and equitable access. As the educational sphere becomes increasingly datafied and automated, there is a growing need to ensure that technological integration is guided by human-centered values, pedagogical soundness, and a long-term vision of sustainability.This study seeks to explore how educational technology, and AI can be thoughtfully and effectively employed to enrich the learning process while addressing the multifaceted challenges that accompany their implementation. Through a critical and evidence-based analysis, the research aims to illuminate practical strategies that support a balanced integration amplifying the benefits of innovation while mitigating its potential risks. In doing so, the study aspires to contribute to the development of inclusive, resilient, and forward-thinking educational policies that not only keep pace with technological change but also uphold the foundational goals of education: equity, empowerment, and lifelong learning.
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Samir F. Matar (Thu,) studied this question.
www.synapsesocial.com/papers/68c199ee9b7b07f3a061bc64 — DOI: https://doi.org/10.63332/joph.v4i2.2915
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