Embracing the data-driven paradigm: a comprehensive framework for effective teaching and learning in higher education

Abstract

The present study investigated the pragmatic implementation and efficacy of data-driven instructional approaches. The complete framework is underpinned by stated objectives, a robust data infrastructure, adaptive practises, and ongoing collaboration. The present study adopted a mixed-methods research design, incorporating qualitative interviews with both academics and students, alongside quantitative evaluations of outcomes from Learning Management Systems (LMS). The objective of this study was to examine the complex correlation between instructional practises and data analytics. This study provided evidence of the potential of data-driven methodologies to significantly enhance customised learning and inform timely pedagogical decisions. Nevertheless, the efficacy of these interventions is contingent upon comprehensive training, endorsement from relevant parties, and ongoing enhancement. This study contributes to the current scholarly discourse on the correlation between data analytics and teaching. The argument posits the importance of a strategic integration that considers both technological and human-centric considerations.