Assessment of artificial intelligence-based digital learning systems in higher education amid the pandemic using analytic hierarchy

Vikrant Vikram Singh (), Nishant Kumar (), Shailender Singh (), Meenakshi Kaul (), Aditya Kumar Gupta () and P. K. Kapur ()
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Vikrant Vikram Singh: Symbiosis International (Deemed University)
Nishant Kumar: CHRIST (Deemed to be University)
Shailender Singh: Symbiosis International (Deemed University)
Meenakshi Kaul: Symbiosis International (Deemed University)
Aditya Kumar Gupta: Amity University
P. K. Kapur: Amity University

International Journal of System Assurance Engineering and Management, 2024, vol. 15, issue 8, No 36, 4069-4084

Abstract: Abstract 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 study’s outcome revealed which AI systems are effectively used in developing digital learning systems by various higher education institutions.

Keywords: Digital literacy; Pythagorean fuzzy; Artificial intelligence; Higher education; Digital learning platform; Evaluation methodologies; Data science (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s13198-024-02411-x

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