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A STUDY ON THE MULTIDISCIPLINARY TEACHING ASPECT OF THE NEP 2020

Authors: Dr. Sanchita Datta;

A STUDY ON THE MULTIDISCIPLINARY TEACHING ASPECT OF THE NEP 2020

Abstract

The world is undergoing rapid changes in the knowledge landscape. With various dramatic scientific and technological advances, the rise of big data, machine learning, and artificial intelligence , many unskilled jobs worldwide taken over by machines, while for a skilled workforce, particularly involving mathematics, computers , and data science, in conjunction with multidisciplinary abilities across the sciences, social sciences, and humanities, increasingly in greater demand. With , increasing pollution, and depleting natural resources, be a sizeable shift in how we meet the world’s energy, water, food, and sanitation needs, again resulting in the need skilled labour, particularly in biology, chemistry, physics, agriculture, climate science, and . The gap between state of learning outcomes and what is required must be bridged through undertaking major reforms that bring the highest quality, equity, and integrity into the system. The aim must be for India to have an education system by 2040 second to none, with equitable access to the highest-quality education for all learners social or economic background. (NEP:2020).Present higher education system in India faces many lacunas of fragmented, compartmentalised learning with rigid curriculum structure emphasis on skill development. Teaching-learning and research are integral higher education, but compared developing countries research in Indian higher education shows a dismal picture. The Study captures research aspects of practical issues in the achieved functioning of HEI and suggestions HEI to ensure full access, equity, and inclusion.

Keywords

Higher Education Policy 2020, Research Programmes in India, Ph.D in India

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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