Forest HyperSoft Sets for Quality Measurement of Preschool Education in the New Era Utilizing MCDM Approach and Data Analytics

Abstract

The assessment of preschool education quality has evolved in the new era, necessitating 
a comprehensive evaluation framework that encompasses pedagogical approaches, teacher 
effectiveness, learning environments, and institutional policies. This study explores the critical 
factors influencing preschool education quality, emphasizing the importance of holistic child 
development, parental engagement, and technology integration. By employing multi-criteria 
decision-making (MCDM) methodologies, we propose a MCDM methodology with the Entropy 
method to compute the criteria weights and the TOPSIS method to rank the alternatives. We use 
the Forest HyperSoft set to divide each criterion as a TreeSoft set. In each TreeSoft set we compute 
the criteria weights and rank the alternatives. This study uses four criteria and five alternatives. 
So, we have four TreeSoft sets. 

DOI: 10.5281/zenodo.15052202