Paper Title
BRIDGING THE GAP IN MULTIDISCIPLINARY USING DATA SCIENCE TO IMPROVE EDUCATION ASSESSMENT IN THE FIELD OF SCIENCE AND TECHNOLOGY

Abstract
This paper explores how data science multidisciplinary fields are transforming various discipline and creating new opportunities for scientific and technological advancement. Bridging the gap between these fields requires fostering collaboration, applying data driven methodologies and creating shared platforms.Key applications used to demonstrate the power of data driven solutions in student performance analysis and multidisciplinary research include Learning Management System(LMS) Analytics, Educational Data Mining(EDM), Student Information system(SIS), Academic Analytics Performance(AAP)and Predictive Analytics for Student Success(PASS). The paper proposes an Integrated Research Framework(IRF) that combines qualitative and quantitative methods to bridge the gap between disciplines. The multidisciplinary approach engages stakeholders in research design and implementation, enhancing the overall benefits of collaboration and knowledge sharing. Ultimately, this framework broadens the scope and impact of research, balancing depth with a comprehensive range inquiry. The paper will highlight how advanced data science techniques can accelerate progress in both theoretical research and practical application, addressing global challenges in science and innovation. Keywords - System Dynamic modelling, Collaborative problem Solving, Concept mapping Stakeholder Analysis.