UTILIZATION OF WEIGHTED AGGREGATED SUM PRODUCT ASSESSMENT FOR TEACHER CANDIDATE SELECTION
Abstract
A fair, objective, and measurable teacher selection process is a real challenge facing many educational institutions. In today's digital age, the need for a systematic and accountable decision-making system is crucial, especially in selecting qualified educators.
This book presents an innovative approach to teacher selection through the application of the Weighted Aggregated Sum Product Assessment (WASPAS) method, a multi-criteria decision-making technique that combines the advantages of the Weighted Sum Model (WSM) and Weighted Product Model (WPM). Through theoretical explanations, case studies, and calculation simulations, readers are invited to understand how WASPAS works in practice in determining the best teacher candidates based on various criteria such as education, experience, microteaching, and interviews.
With easy-to-understand language and supported by applicable data, this book serves not only as an academic reference but also as a practical guide for schools, foundations, and education practitioners who want to build data- and technology-based selection systems.
This is essential reading for those seeking to combine data science, objective decision-making, and a passion for quality education.
