Open Access

Regional Intelligence Model for Physical Education Teacher Selection and Allocation Optimization

https://doi.org/10.55640/ijmcsit-v03i08-04

PDF

Dr. Antoine Laurent ¹ ,

⁴ Department of Artificial Intelligence and Robotics, Monaco Institute of Advanced Computing, Monaco

Abstract

The effective allocation of physical education (PE) teachers across educational regions remains a complex decision-making challenge due to variations in socioeconomic conditions, institutional requirements, student demographics, and regional resource availability. Traditional recruitment approaches often rely on generalized evaluation criteria that fail to capture multidimensional regional differences. This study proposes a Regional Intelligence Model for Physical Education Teacher Selection and Allocation Optimization (RIM-PE) that integrates socioeconomic intelligence, human resource recommendation mechanisms, and data-driven decision optimization principles. The proposed model combines regional feature analysis, intelligent candidate matching, and allocation optimization to improve fairness, efficiency, and adaptability in PE teacher recruitment. The framework is conceptually developed by integrating recommendation algorithms, feature engineering strategies, and intelligent decision approaches derived from recent computational studies. The model incorporates regional indicators such as educational demand, economic characteristics, institutional capacity, and teacher competency profiles to generate optimized placement recommendations. Theoretical analysis indicates that intelligent allocation mechanisms can reduce regional imbalance, enhance teacher suitability, and support evidence-based educational planning. The study further discusses the role of human–AI trust modeling and advanced feature engineering in improving decision reliability within intelligent recruitment systems (Ramamurthy et al., 2026). The proposed framework provides a foundation for future AI-assisted educational workforce planning and scalable teacher management systems.

Keywords

Physical Education Teacher Recruitment, Regional Intelligence, Teacher Allocation Optimization, Recommendation System

References

H.A. Yazbek et al., “A novel approach to model the economic characteristics of an organization by interval-valued complex pythagorean fuzzy information[J],” J. Comput. Cognit. Eng., vol. 2, no. 1, pp. 75–87, 2023.

J. Wang, K. Yue, and L. Duan, “Models and techniques for domain relation extraction: a survey[J],” J. Data Sci. Intell. Syst., vol. 1, no. 14, pp. 65–67, 2023.

L. Zhaoshan, M. Yiming, Z. Huihua, D. Liu, and J. Liu, “Human resource recommendation algorithm based on improved frequent itemset mining[J],” Future Gener. Comput. Syst., vol. 126, no. 1, pp. 284–288, 2021.

N. Wang and E. Katsamakas, “A recommendation system for people analytics[J],” Int. J. Business Intell. Res., vol. 12, no. 2, pp. 1–12, 2021.

Q. Zhang, “Chinese pre-service preschool teachers’ professional development in PE,” Contemp. Educ. Teach. Res., vol. 3, no. 4, pp. 167–170, 2020.

R. G. Mohammed Helali, “An exploratory study of factors affecting research productivity in higher educational institutes using regression and deep learning techniques[J],” Artif. Intell. Appl., vol. 1, no. 1, pp. 23–26, 2023.

S. Choudhuri, S. Adeniye, and A. Sen, “Distribution alignment using complement entropy objective and adaptive consensus-based label refinement for partial domain adaptation[C],” Artif. Intell. Appl., vol. 1, no. 1, pp. 43–51, 2023.

X. M. Long, Y. J. Chen, and J. Zhou, “Development of AR experiment on electric-thermal effect by open framework with simulation-based asset and user-defined input[C],” Artif. Intell. Appl., vol. 1, no. 1, pp. 52–57, 2023.

Ramamurthy, K., Gumber, S., Abdelfattah, W.M. et al. Human AI trust modeling in cognitive systems via ensemble learning and advanced feature engineering. Discov Artif Intell 6, 366 (2026). https://doi.org/10.1007/s44163-026-01255-7

Most read articles by the same author(s)

<< < 6 7 8 9 10 11 12 > >>

International Journal of Modern Computer Science and IT Innovations

Regional Intelligence Model for Physical Education Teacher Selection and Allocation Optimization

Abstract

Keywords

References

Most read articles by the same author(s)

Similar Articles