Analyzing MAUT, ELECTRE, and SMART Methods in Determining the Best Physics Learning Media Aid - Andre Farhan Saputra; Fransiskus Pito Tenawahang; Mulia Yuga Utama; Perani Rosyani; Suryaningrat; Yono Cahyono (International Journal of Integrative Sciences, 2023)
This study, titled " Analyzing MAUT, ELECTRE, and SMART Methods in Determining the Best Physics Learning Media Aid", evaluates three decision analysis methods—Multi-Attribute Utility Theory (MAUT), Elimination Et Choix Traduisant la Realité (ELECTRE), and Simple Multi-Attribute Rating Technique (SMART). Focused on factors like usability, effectiveness, cost, and adaptability, it guides educators in choosing the best learning tools. Using a multi-criteria decision analysis framework, the research systematically assesses MAUT, ELECTRE, and SMART, emphasizing their strengths and limitations in physics education. Beyond immediate decision-making, it prompts discussions on technology integration, encouraging innovative approaches. Findings offer insights for future research at the intersections of technology, pedagogy, and decision science. In conclusion, the study illuminates decision analysis methods for optimal physics learning media tools. PhyWiz's consistent top-ranking performance highlights its potential for enhancing physics education. The research recommends PhyWiz integration, emphasizing regular evaluation and adoption of innovative tools to improve physics education quality. It provides a practical guide for educators, contributing to continuous enhancements in teaching and learning experiences