MAPPING MULTIPLE INTELLIGENCES OF DISTANCE EDUCATION STUDENTS - Fatia Fatimah; Andriyansah (International Journal of Social Science, Educational, Economics, Agriculture Research and Technology (IJSET), 2026)
This study maps the multiple intelligence profiles of distance education students at Universitas Terbuka Padang, Indonesia. A total of 105 students from the even semester of the 2024/2025 academic year participated, with data collected in January 2025 using the TIA (Talent and Interest Allocation) mobile application. Six intelligence dimensions were assessed: linguistic, logical-mathematical, kinesthetic, musical, interpersonal, and intrapersonal. The N-Soft Sets decision-making algorithm was applied for data analysis, with a threshold of r ≥ 3 (rating of “often” or “always”) and a conclusion that 75% of parameters in an intelligence group must meet the threshold for categorization. Results revealed that intrapersonal intelligence and interpersonal intelligence were the dominant dimensions, while musical intelligence scored lowest. The demographic profile showed that 87.6% of participants were female, 61.0% were from the Faculty of Teacher Training and Education, and 68.6% were enrolled in fully online programs without face-to-face tutorials. These findings provide empirical foundations for personalized talent allocation through the TIA application in distance higher education. The study contributes empirical evidence on student multiple intelligences distribution in distance education contexts, providing a foundation for personalized talent allocation and activity recommendation systems. Implications for mobile-based talent management applications in distance higher education are discussed.