Prediction of UHV-STEM based educational framework for holistic and sustainable living using Educational Data Mining

Abstract

The rate of digital literacy and computational literacy has undoubtedly risen over the past few decades.  But "being literate" rather than "being educated" is still the goal. The focus of every government in the world is undoubtedly on STEM education, and students are also demonstrating positive attitude towards STEM learning. STEM education undoubtedly increases human skill. According to New Education Policies around the world, life skills were essential for the entire development of people.  Universal Human Values (UHV) education must now be incorporated into every educational discipline as a course, programme, and subject alongside students' STEM learning disciplines in order to forecast their learning ability or behavior. Undoubtedly, combining the study of science, technology, engineering, and math with UHV (UHV-STEM or UHVSTEM) can have a positive, long-lasting effect on society by removing stress from everyone's life as time goes on. Students with STEM education can behave more predictably by gathering UHV-based Self-Assessment Batteries and using tools and techniques of Educational Data Mining (EDM). This paper will focus on education impact, prediction of course, programme, subject, using k-means algorithm of EDM processes, tools, techniques and benefits of it in diverse classification and clustering of students’ performance prediction. The outcome has been taken as focusing on qualitative research with students, teachers through various logical research questions, and proposed UHV-STEM based Student performance assessment model. In this sequence, the fourth sustainable development goal of the United Nations can be satisfied by value-based education, or UHVSTEM education.