THE ROLE OF BIG DATA IN PERSONALISED LEARNING ENVIRONMENTS: IMPLICATIONS FOR CURRICULUM DESIGN

Abstract

This research paper explores the transformative role of big data analytics in personalised learning environments and its profound implications for curriculum design. As educational institutions increasingly adopt data-driven approaches, understanding how to leverage vast amounts of learner data becomes crucial for developing effective, adaptive curricula. This paper examines the theoretical foundations of big data in education, analyses current applications in personalised learning systems, and discusses the implications for curriculum designers and educational practitioners. Through a comprehensive review of recent literature and case studies, this research identifies key challenges, opportunities, and best practices for integrating big data analytics into curriculum development processes. The findings suggest that big data, when properly implemented, can significantly enhance learning outcomes by enabling real-time adaptation, predictive analytics, and evidence-based curriculum refinement. However, successful implementation requires careful consideration of privacy concerns, data quality, pedagogical alignment, and institutional capacity. This paper contributes to the growing body of knowledge on educational technology by providing actionable insights for educators, curriculum designers, and policymakers seeking to harness big data for improved learning experiences.