Background: India’s rich educational heritage dates to ancient times, with popular institutions like Nalanda, Takshashila, and Banarasi-Kasi flourishing as early as the 6th century BC, which offered diverse courses spanning medicine, mathematics, astronomy, and more. Invasions by the Mughals and British during the 12th to 18th centuries disrupted India’s traditional education systems. Post-independence, India faced the challenge of transitioning from ancient to modern education. Remarkably, the country managed to preserve its popular traditional education through a strategic change management approach by the educational institutions. The Government of India has introduced in the National Education Policy 2020 (NEP 2020) in July 2020, to bring transformational reforms in school and higher education systems. In this manuscript, we have summarized the salient features of the NEP 2020 and the preparedness steps to its effective implementation in Indian educational institutions. Method: We have utilised standard databases like PubMed, Science Direct, or Google Scholar, and/or public domains and the NEP 2020 document for this literature survey. Value addition: NEP 2020 aims to ensure access, equity, quality, affordability, and accountability with more flexible curricular structure, and holistic approaches. Despite the COVID-19 pandemic’s impact, dynamic planning, and collaboration among public and private institutions, and industries supported the effective implementation of NEP 2020. Notably, the change management approach, which has been a constant throughout India’s educational journey, played a pivotal role in keeping pace with technological advancements and fostering growth in the higher education system in India.
Students from different cultures possess varying levels of skills in learning, remembering, and understanding concepts. Some terms and their explanations may seem easy for one group of students but difficult for another. Therefore, delivering educational content that aligns with student’s learning capabilities is a challenging task based on cultural orientations. This study addresses the learning challenges by developing a Thesaurus Glossary E-learning (TGE) framework method. This study introduces the TGE method which is a multi-language tool with visual associations that adapts to students’ capabilities. It also examines cultural differences and native languages, particularly aiding Arab Native to visualize appropriate terms (thesaurus) and their explanations (glossary) based on students’ learning capabilities. TGE learns from students’ term selection behavior and displays terms at a simple or advanced level that matches their learning ability. Additionally, TGE demonstrated its effectiveness as an e-learning tool, accessible to all students anytime and anywhere. The study analyzed 314 records related to student performance, out of which 114 students were surveyed to evaluate the effectiveness of the TGE method. This work presents TGE as a novel e-learning tool designed to enhance conceptual thinking within the context of modern educational practices during the digital transformation. TGE is based on artificial intelligence algorithms and associative rules that simulate the human brain, establishing logical connections between related key terms and sketching associations among diverse facets of a situation. An experiment was conducted at a private university in the Sultanate of Oman to assess the effectiveness of the proposed TGE tool. TGE was integrated with selected subjects in information systems and used by the students as a resource for e-learning methods and materials. The results show that 85% of students who used TGE improved their performance by 19%. We believe this work could establish a new smart e-learning teaching method and attract modern and digital universities to enhance student learning outcomes linked with conceptual thinking.
The presence of a crisis has consistently been an inherent aspect of the Supply Chain, mostly as a result of the substantial number of stakeholders involved and the intricate dynamics of their relationships. The objective of this study is to assess the potential of Big Data as a tool for planning risk management in Supply Chain crises. Specifically, it focuses on using computational analysis and modeling to quantitatively analyze financial risks. The “Web of Science—Elsevier” database was employed to fulfill the aims of this work by identifying relevant papers for the investigation. The data were inputted into VOS viewer, a software application used to construct and visualize bibliometric networks for subsequent research. Data processing indicates a significant rise in the quantity of publications and citations related to the topic over the past five years. Moreover, the study encompasses a wide variety of crisis types, with the COVID-19 pandemic being the most significant. Nevertheless, the cooperation among institutions is evidently limited. This has limited the theoretical progress of the field and may have contributed to the ambiguity in understanding the research issue.
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