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Exploring Challenges in Online Higher Education for AI Integration Using MICMAC Analysis
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Author(s): Ramji Nagariya (Christ University, India), Priyanshu Sharma (Birla Institute of Technology, Mesra, India), Abhineet Saxena (Amity University, Jaipur, India), Priti Saxena (S.P. Mandali's Prin. L.N. Welingkar Institute of Management, Development, and Research, India)and Garima Pancholi (Amity University, Jaipur, India)
Copyright: 2024
Pages: 16
Source title:
Integrating Generative AI in Education to Achieve Sustainable Development Goals
Source Author(s)/Editor(s): Ruchi Doshi (Universidad Azteca, Mexico), Manish Dadhich (Sir Padampat Singhania University, India), Sandeep Poddar (Lincoln University College, Malaysia)and Kamal Kant Hiran (Sir Padampat Singhania University, India & Lincoln University College, Malaysia)
DOI: 10.4018/979-8-3693-2440-0.ch021
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Abstract
The consequence of Covid-19 has affected the traditional higher education system. Acknowledging the significant role of online education in national development for accessibility and quality education, countries around the world have understood its importance in current digital era. Indian policymakers have been giving due importance to enhancing the education quality, however the progress made by the country in higher education is not adequate. Amidst all the inadequacies of traditional education system, artificial intelligence (AI) technologies are bringing new ray of hope to democratize education system. This chapter is subjected to identify the challenges in online education and suggest specific ways to address each of them. The challenges are categorized into internal and external challenges/barriers. These challenges have been modeled with the expertise of educationalist's opinions and interpretive structural modeling to create a hierarchy of the barriers using MICMAC analysis and categorize these barriers into four clusters.
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