AI-driven: An Exploration of the Pathways to Reshape the Ecosystem of Quality Education
DOI:
https://doi.org/10.63313/ESW.2011Keywords:
Artificial Intelligence, Education, Personalized Learning, Ethics, Digital Divide, Teacher TrainingAbstract
This study investigates the transformative potential of Artificial Intelligence (AI) in reshaping the quality education ecosystem, focusing on key pathways and associated challenges. It addresses the current limitations in personalization, accessibility, and scalability within traditional educational methods, arguing that AI offers innovative solutions through personalized learning experiences, intelligent tutoring systems, and automated administrative tasks. The research explores the ethical considerations, data privacy concerns, and the digital divide that must be addressed for equitable and responsible AI implementation. The study employs a comprehensive analysis of existing literature and theoretical frameworks to identify specific pathways for AI to enhance education quality. It examines the benefits and challenges of integrating AI into various educational facets, proposes strategies for mitigating biases in AI algorithms, and develops a framework for responsible AI implementation, emphasizing data privacy and equity. The expected outcomes include a detailed analysis of AI's impact on teacher roles, pedagogical practices, and student learning outcomes. Furthermore, it offers recommendations for teacher training and strategies for bridging the digital divide. This research contributes to the understanding of how AI can revolutionize education while ensuring fairness, inclusivity, and ethical considerations are prioritized.
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