Articles
The Inner Patterns of High-Level Talent Development in Geology: An Interpretation Based on Educational Principles
Abstract
The development of high-level innovative talents in geology cannot be achieved through the independent effects of knowledge accumulation, intellectual advantages, or educational resources. Rather, it is constituted by the long-term interaction among individual endowment, intrinsic motivation, cognitive development, practical activities, and the educational environment. This developmental process generally exhibits a series of characteristics, including interest-driven engagement, problem-based guidance, differentiation of abilities, practice-generated outcomes, and nonlinear transitions. When educational practice relies excessively on examination scores, competition achievements, and uniformly designed curricula, it tends to overlook the complexity of innovative potential and the differences in developmental pace. Based on educational principles such as subjectivity, individual differences, practice-based generation, and environmental support, this paper analyzes the internal laws governing the development of high-level innovative talents in geology, the deviations emerging in current cultivation practices, and possible paths for improvement, thereby providing reference for the establishment of a more open, continuous, and adaptive talent cultivation model.
Keywords
References
Zhang Y ,Chen J .Enhancing the Quality of Talent Cultivation to Consolidate the Core Driving Force for Innovative Development[J].Technological Innovation and Science Management(TISM),2025,1(2)
Eryong X ,Jian L .Cultivating high-level innovative talents by integration of science and education in China: A strategic policy perspective[J].Educational Philosophy and Theory,2022,54(9)1419-1430.
Caiyun S .Research on Training Mode of High-Level Innovative Talents in Computer Science inColleges[J].ProcediaEngineering,2012,29(C)2749-2753.
Wei Z ,Jin Q .A Comprehensive Assessment of Cultivation Environment of Top Innovative High-Level Talents Based on Deep Learning Algorithm[J].Journal of Environmental and Public Health,2022,20224846103-4846103.
Wu X .Research on the construction of evaluation system for high-level scientific and technological talents based on big data analysis[J].Applied Mathematics and Nonlinear Sciences,2024,9(1)

