Identifying the Components of an Innovative School Model Based on the Identification and Development of Students’ Multiple Intelligences
Keywords:
Innovative School, Multiple Intelligences, Talent Identification, Educational Innovation, Talent Development, Intelligence-Based EducationAbstract
Purpose: The present study aimed to identify and conceptualize the components of an innovative school model grounded in the systematic identification and development of students’ multiple intelligences.
Methods and Materials: This study employed a qualitative research design using grounded theory methodology to construct an empirically derived model of an innovative school. The research was conducted in Tehran and involved 22 educational experts, including school principals, experienced teachers, curriculum specialists, educational psychologists, and policymakers selected through purposive sampling with maximum variation. Data were collected through semi-structured in-depth interviews supported by field notes and document analysis. Data collection continued until theoretical saturation was achieved. Analysis was conducted simultaneously with data collection using open coding, axial coding, and selective coding procedures based on the constant comparative method. Strategies including member checking, peer debriefing, and audit trail documentation were applied to enhance credibility, dependability, confirmability, and transferability of findings.
Findings: The analysis resulted in the emergence of a comprehensive innovative school model composed of interconnected structural, pedagogical, and developmental dimensions. The model indicated that innovative schooling requires visionary and participatory leadership, intelligence-based curriculum design, multidimensional talent identification and assessment systems, continuous professional development for teachers, flexible and technology-supported learning environments, and active collaboration with families and community institutions. Findings further suggested that innovation in schools is achieved through systemic integration rather than isolated reforms, leading to improved student engagement, recognition of diverse talents, strengthened creativity, enhanced socio-emotional development, and increased institutional adaptability.
Conclusion: The study concludes that developing innovative schools depends on aligning leadership practices, teaching-learning processes, assessment mechanisms, organizational culture, and educational ecosystems around the philosophy of multiple intelligences.
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References
Al Shahrani, M. (2021). Methods of Thinking and Its Relation to the Multiple Intelligences for the Talented Students in Makkah Al-Mukarramah. Arid International Journal of Educational and Physcological Sciences, 42-67. https://doi.org/10.36772/arid.aijeps.2021.232
Bian, Y., Xie, L., & Li, J.-q. (2022). Research on Factors Influencing the Training of Artificial Intelligence Applied Talents Based on DEMATEL-TAISM. https://doi.org/10.21203/rs.3.rs-1705932/v1
Cai, X. (2024). Digital Intelligent Transformation and Promotion Path of New Business Talent Training Model Under the Background of Artificial Intelligence. 2(1), 51-56. https://doi.org/10.62517/jiem.202403108
Chen, Z. (2025). Transformation in the Context of Digital Intelligence: A New Paradigm for Cultivating Financial and Economic Talents at Guangdong Technology College. Advances in Education Humanities and Social Science Research, 13(1), 511. https://doi.org/10.56028/aehssr.13.1.511.2025
CrenguȚA, S. (2023). Învățarea Școlară Din Perspectiva Inteligențelor Multiple. 87-91. https://doi.org/10.46727/c.17-11-2023.p87-91
Daswati, D., & Fitriani, W. (2023). Studi Analisis Psikologi Belajar Pendidikan Agama Islam Berdasarkan Kreativitas, Minat, Bakat, Dan Intelegensi. Itqan Jurnal Ilmu-Ilmu Kependidikan, 14(1), 67-82. https://doi.org/10.47766/itqan.v13i2.811
Duan, Y. (2023). Discussion on the Construction of College English Teaching Model Based on Multi-Intelligence Theory. International Journal of New Developments in Education, 5(9). https://doi.org/10.25236/ijnde.2023.050916
Ellis, B. J., Abrams, L. S., Masten, A. S., Sternberg, R. J., Tottenham, N., & Frankenhuis, W. E. (2023). The Hidden Talents Framework. https://doi.org/10.1017/9781009350051
Guo, X. (2024). Intelligent Internet of Things and Privacy Protection Technology for IPE Data Analysis. Jes, 20(7s), 75-83. https://doi.org/10.52783/jes.3250
Jumarlis, M., Mirfan, M., Suardi, M., & Sharma, V. (2025). Naïve Bayes-Based Intelligent Model for Identification and Analysis of Learners' Intelligence Potential. Inspiration Jurnal Teknologi Informasi Dan Komunikasi, 15(1), 90-101. https://doi.org/10.35585/inspir.v15i1.109
Koh, A. S., Ahmad Zabidi Bin Abdul, R., & Shamsudin, S. B. (2024). Systematic Literature Review: What Factors Influence Talent Management Among Secondary School Teachers in Malaysia? Malaysian Journal of Social Sciences and Humanities (MJSSH), 9(3), e002746. https://doi.org/10.47405/mjssh.v9i3.2746
Liang, H., & Zhang, L. (2023). Design of Knowledge Model and Training Mode of Business Foreign Language Composite Talents Based on the Background of Digital Economy Under the Current Pattern of "Dual Circulation". Advances in Education Humanities and Social Science Research, 1(3), 202. https://doi.org/10.56028/aehssr.3.1.202
Liao, F., & Lai, H. (2023). A Collaborative Training Mechanism for Accounting Digital Intelligence Talents Based on the Triple Helix Theory. 1(3), 1-8. https://doi.org/10.62517/jike.202304301
Liu, F. (2025). Research on the AI Talent Granary Model Based on "Optimal Design of Mechanical Engineering" Module in the Age of Digital Intelligence for Mechanical Majors. Higher Education and Practice, 2(10), 1-7. https://doi.org/10.62381/h251a01
Lu, L. (2023). Research on the Innovation of the Meta-Universe Vocational Talent Training Model From the Perspective of Resource Dependence Theory. Eeer, 3(1). https://doi.org/10.37420/j.eeer.2023.008
Manasikana, O. A., Mayasari, A., Siswanto, M. B. E., Kusumawati, I. R., Wijayadi, A. W., Af’idah, N., & Kusumaningsih, D. (2022). Pelatihan Penelusuran Bakat Dan Minat Dengan Pendekatan Multiple Intelegences Di MA Midanut Ta’lim Jogoroto Jombang. Real Coster Jurnal Pengabdian Kepada Masyarakat, 5(1), 42-52. https://doi.org/10.53547/rcj.v5i1.172
Mao, Z., Wu, J., & Xu, X. (2024). Exploration of the Training Model of Applied Management Accounting Talent in the Context of Digital Intelligence. Journal of Economics and Business, 7(1). https://doi.org/10.31014/aior.1992.07.01.570
Meng, X., Xu, C., & Sun, X. (2024). Research and Practice on Innovative Talent Cultivation Model in the Field of Educational Technology From the Perspective of Education Artificial Intelligence. Advances in Vocational and Technical Education, 6(3). https://doi.org/10.23977/avte.2024.060302
Mossberg, F., Lundqvist, J., & Sund, L. (2024). An International Scoping Review Focused on Gifted and Talented Children: Early Identification and Inclusive Education. Journal of Childhood Education & Society, 5(3), 407-423. https://doi.org/10.37291/2717638x.202453488
Murniviyanti, L. (2023). Educational Service Model for the Special Intelligence and Special Talents of Students: Literature Review. Pijed, 2(2), 278-287. https://doi.org/10.59175/pijed.v2i2.110
Nirwan, N. P. (2026). Model of Management for Implementing a Multiple Intelligences Based Talent Program in Optimizing Students Potential. Didaktik Jurnal Ilmiah PGSD Stkip Subang, 12(01), 46-56. https://doi.org/10.36989/didaktik.v12i01.11813
Səfərova, E., & Məmmədova, G. (2024). Ümumtəhsi̇l Məktəbləri̇ndə Bi̇ologi̇yanin Tədri̇si̇ndə İstedadli Şagi̇rdlərlə İşi̇n Təşki̇li̇. Heoap, 2(2024), 267-270. https://doi.org/10.62021/0026-0028.2024.3.267
Singh, P., & Bisht, A. S. (2024). Significance of Discriminant Analysis for Classification and Talent Identification in Sports – A Thematic Review. Shodhkosh Journal of Visual and Performing Arts, 5(4). https://doi.org/10.29121/shodhkosh.v5.i4.2024.5752
Thambu, N., Prayitno, H. J., & Zakaria, G. A. N. (2021). Incorporating Active Learning Into Moral Education to Develop Multiple Intelligences: A Qualitative Approach. Indonesian Journal on Learning and Advanced Education (IJOLAE), 17-29. https://doi.org/10.23917/ijolae.v3i1.10064
Toshpulatov, K. (2025). Theoretical Foundations of Teaching Talented Students in Higher Education Institutions Based on a Differentiated Approach. Информатика Экономика Управление - Informatics Economics Management, 4(1), 4001-4006. https://doi.org/10.47813/2782-5280-2025-4-1-4001-4006
Uyduran, M. A. C., & Abakay, U. (2021). Investigation of the Multiple Intelligence Areas of Students Introducing the Special Talent Examination for Higher Education Institution. European Journal of Physical Education and Sport Science, 7(1). https://doi.org/10.46827/ejpe.v7i1.3787
Wang, D. (2025). Application and Significance of Multiple Intelligences Theory in General Educational Development Planning. Journal of Higher Education Research, 6(4), 436. https://doi.org/10.32629/jher.v6i4.4302
Wang, J. (2023). Developing Intelligent Education in China. 514-518. https://doi.org/10.2991/978-2-38476-068-8_64
Wang, Q. (2025). Research on the Training Mode of Animation Professionals in the Era of Artificial Intelligence. Advances in Education Humanities and Social Science Research, 13(1), 444. https://doi.org/10.56028/aehssr.13.1.444.2025
Xiang, C., Kamalden, T. F. T., Liu, H., & Ismail, N. (2022). Exploring the Multidisciplinary Factors Affecting Sports Talent Identification. Frontiers in psychology, 13. https://doi.org/10.3389/fpsyg.2022.948121
Xie, M., & Xu, X. (2022). Construction of a College Physical Education Teaching Model Using Multiple Intelligences Theory. Scientific Programming, 2022, 1-10. https://doi.org/10.1155/2022/1837512
Xu, Z. (2025). Exploring the Integrated Transformation of Intelligence and Efficiency in Public Sector Human Resource Management From a Big Data Perspective. JSSHL, 8(4), 30-37. https://doi.org/10.53469/jsshl.2025.08(04).05
Yan, J., Li, Y., & Zheng, Z. (2024). Enhancing Decision-Making Framework for Talent Cultivation Quality Evaluation Using Dual Hamy Mean and Prioritized Aggregation Operators. International Journal of Knowledge-Based and Intelligent Engineering Systems, 28(3), 553-570. https://doi.org/10.3233/kes-230289
Ye, S. (2023). Research on Undergraduate Vocational Education Talent Training Based on the Deep Integration of Artificial Intelligence and Education. Advances in Vocational and Technical Education, 5(1). https://doi.org/10.23977/avte.2023.050110
Yin, X. (2023). Art Education in Colleges and Universities Based on the Theory of Multiple Intelligence. Edu, 6(8), 142. https://doi.org/10.31058/j.edu.2023.68018
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