By: Bhavna Sharma
Assistant Professor, Department of Computer,LajPat Rai College,(L.R) Sahibabad, Ghaziabad, Uttar Pradesh, India.
A revolutionary factor that evolves how learning is experienced and how educational systems function is the incorporation of artificial intelligence (AI) and machine learning (ML) in the classroom. Data- driven decision-making, administrative work automated processes, real-time feedback, and education personalization are all made possible by AI and ML technologies, which are no longer just found in research and industry. This study addresses the various ways that AI and ML can be used in education, emphasizing how they can be used to develop more customized, easily accessible, and effective learning environments. With the help of AI-powered tools such as predictive analytics, adaptive learning systems, and intelligent tutoring platforms, education is becoming more individualized for each student’s needs, encouraging a deeper engagement with a subject matter and enhancing learning results. Additionally, by automating processes like scheduling, grading, and resource management, AI and ML are improving administrative efficiency and freeing up instructors and administrators at schools to concentrate more on mentoring and instruction. But there are certain difficulties in integrating these technologies. To guarantee that the advantages of AI and ML in teaching are shared equitably, ethical issues, such as algorithmic bias, data privacy, and equitable access to technology must be considered. The study also highlights how crucial it is to strike the right equilibrium between the indispensable human components of education and the application of AI, stressing that technology should be used to supplement teachers rather than replace them. In the end, education could undergo a transformation thanks to the transformative potential of AI and ML, which could make it more inclusive, efficient, and personalized. But only if AI and ML are applied carefully, morally, and with an emphasis on the needs of all students regardless of their backgrounds, equal skill levels can this promise be fulfilled.
Keywords: Artificial intelligence, machine learning, education, personalized learning, intelligent tutoring systems, data-driven insights, ethical considerations
Citation:
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