Brilliant resource integration for gifted and high talent: a career optimization system for gifted students
Abstract
Brilliant resource integration for gifted and high talent (BRIGHT) was developed as a technology-based educational management system to
help schools identify the potential of gifted and talented students (GTS)
and translate it into personalized talent-development and career recommendations. This study employed a research and development (R&D) design using the analysis, design, development, implementation, and evaluation (ADDIE) model and evaluated the system with 392 senior high school students from Central Java, the Special Region of Yogyakarta, and East Java. BRIGHT integrates student-profile assessment with an analytical hierarchy process (AHP)-based decision mechanism to support more objective potential mapping and career planning. The results show that most students were classified in the moderate-to-high categories across all assessed dimensions. Career readiness and planning recorded the highest proportion in the high category (52.0%), followed by career interest (46.2%), learning style and work environment fit (45.7%), and career personality (45.4%). Spearman’s rho analysis also confirmed significant positive relationships between BRIGHT outputs and all career-development dimensions, with coefficients ranging from 0.672 to 0.762 (p<0.001). These findings indicate that BRIGHT is effective in supporting potential identification, learning-environment alignment, and career readiness among gifted students. The novelty of this study lies in the integration of gifted-student identification, personalized development planning, and data-driven career recommendation within a single school-based educational management system.
help schools identify the potential of gifted and talented students (GTS)
and translate it into personalized talent-development and career recommendations. This study employed a research and development (R&D) design using the analysis, design, development, implementation, and evaluation (ADDIE) model and evaluated the system with 392 senior high school students from Central Java, the Special Region of Yogyakarta, and East Java. BRIGHT integrates student-profile assessment with an analytical hierarchy process (AHP)-based decision mechanism to support more objective potential mapping and career planning. The results show that most students were classified in the moderate-to-high categories across all assessed dimensions. Career readiness and planning recorded the highest proportion in the high category (52.0%), followed by career interest (46.2%), learning style and work environment fit (45.7%), and career personality (45.4%). Spearman’s rho analysis also confirmed significant positive relationships between BRIGHT outputs and all career-development dimensions, with coefficients ranging from 0.672 to 0.762 (p<0.001). These findings indicate that BRIGHT is effective in supporting potential identification, learning-environment alignment, and career readiness among gifted students. The novelty of this study lies in the integration of gifted-student identification, personalized development planning, and data-driven career recommendation within a single school-based educational management system.
Keywords
Analytical hierarchy process; Artificial intelligence–based intervention; Career opportunities; Educational management; Gifted and talented students
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PDFDOI: http://doi.org/10.11591/ijere.v15i5.39724
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Copyright (c) 2026 Rini Sugiarti, Erwin Erlangga, Saifullah Aldeia, Tatas Transinata, April Firman Daru
International Journal of Evaluation and Research in Education (IJERE)
p-ISSN: 2252-8822, e-ISSN: 2620-5440
The journal is published by Institute of Advanced Engineering and Science (IAES).
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