ISSN: 0976-4860
Soya Mathew*
The exponential growth of data has transformed information into a vital asset, driving innovation and strategic decision-making. This paper explores the profound impact of data analytics on education, emphasizing its role in enhancing teaching, learning and institutional operations. By leveraging predictive modelling, educational institutions can make informed decisions, improve performance and optimize processes. The shift from print to digital literacy is crucial, necessitating the creation, maintenance and secure management of extensive digital databases. While data analytics presents challenges such as data digitization and long-term investment, its benefits in decision-making, efficiency and cost-effectiveness are undeniable. The integration of data analytics in Electronic Theses and Dissertations (ETDs) has revolutionized data management, enabled, automated, accurate analysis and fostered a collaborative research environment. This paper examines the life cycle of analytics, highlighting its stages from data preparation to AI-driven predictions. The application of analytics in ETDs allows for efficient data processing, retrojection studies and algorithmic historiography, leading to insightful, transparent and unbiased research outcomes. However, the adoption of analytics requires careful consideration of consistency, technical challenges and ethical standards. Despite these hurdles, the potential of analytics to transform educational research and institutional strategies is immense. As we transition into the fourth industrial revolution, characterized by AI and big data, the strategic use of analytics in ETDs is paramount for future readiness and innovation.
This paper underscores the necessity for educational institutions to embrace data analytics, outlining the benefits, challenges and strategic importance of this transformative tool in navigating contemporary educational and research landscapes.
Published Date: 2025-04-16; Received Date: 2024-06-25