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              <text>Assessment of artificial intelligence-based digital learning systems in higher education amid the pandemic using analytic hierarchy</text>
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              <text>Artificial intelligence; Data science; Digital learning platform; Digital literacy; Evaluation methodologies; Higher education; Pythagorean fuzzy</text>
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              <text>The devastating effects of the 2020 worldwide COVID-19 virus epidemic prompted widespread lockdowns and restrictions, which will continue to be felt for decades. The repercussions of the pandemic have been most noticeable among educators and their students, which boosts the effectiveness of various AI-based learning systems in the education system. This study examines the AI-based digital learning platforms in higher education institutions based on various characteristics and uses of these systems. Several significant aspects of AI-based digital learning systems were obtained from the available literature, and significant articles were selected to properly examine various characteristics and functions of AI-based digital learning platforms used by multiple higher education institutions. The analytical hierarchy process (AHP) is employed to rank multiple AI-based learning systems based on key factors and their sub-factors. The studys outcome revealed which AI systems are effectively used in developing digital learning systems by various higher education institutions.  The Author(s) under exclusive licence to The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2024.</text>
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              <text>Singh V.V.; Kumar N.; Singh S.; Kaul M.; Gupta A.K.; Kapur P.K.</text>
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              <text>International Journal of System Assurance Engineering and Management, Vol-15, No. 8, pp. 4069-4084.</text>
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              <text>Springer</text>
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              <text>2024-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1007/s13198-024-02411-x" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/s13198-024-02411-x&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197219873&amp;amp;doi=10.1007%2Fs13198-024-02411-x&amp;amp;partnerID=40&amp;amp;md5=8097d64eb5d82b646f0907db597bd930" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197219873&amp;amp;doi=10.1007%2fs13198-024-02411-x&amp;amp;partnerID=40&amp;amp;md5=8097d64eb5d82b646f0907db597bd930&lt;/a&gt;</text>
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              <text>Restricted Access</text>
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              <text>ISSN: 9756809</text>
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              <text>Singh V.V., Symbiosis Centre for Management Studies, Noida, Symbiosis International (Deemed University), Pune, India; Kumar N., School of Business and Management, CHRIST (Deemed to be University), Bangalore, India; Singh S., Symbiosis Law School, Noida, Symbiosis International (Deemed University), Pune, India; Kaul M., Symbiosis Law School, Noida, Symbiosis International (Deemed University), Pune, India; Gupta A.K., Amity International Business School, Amity University, U.P, Noida, India; Kapur P.K., Amity Centre for Interdisciplinary Research, Amity University, U.P, Noida, 201313, India</text>
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