GIS Talent Training Paradigm in the Era of Spatial Intelligence: Reconstruction of Education System Driven by Generative AI

DOI: https://doi.org/10.62517/jike.202504204

Author(s)

Lin Li*, Zhiwei Chen

Affiliation(s)

Heilongjiang University of Technology, Jixi, Heilongjiang, China *Corresponding Author.

Abstract

The fourth industrial revolution with generative AI as the core driving force is reshaping the ecology of geographic information science education. Aiming at the development trend of AI technology and its far-reaching influence on the field of GIS, this paper systematically discusses the reconstruction path of GIS education and talent training system in the era of spatial intelligence. The research points out that traditional GIS education faces challenges such as lagging course content, insufficient intelligence of practice platform and single evaluation mechanism, while generative AI technology further aggravates the demand for interdisciplinary talents by enabling data processing, model construction and decision support. To this end, this paper proposes a ' knowledge-ability-quality ' trinity training framework, emphasizing the iteration of knowledge system, the strengthening of AI tool application ability and the improvement of scientific aesthetic literacy, and constructs specific implementation paths from the dimensions of progressive teaching reform, AI technology integration practice, production and education collaborative education. The research results aim to provide theoretical support for the innovation of GIS education in colleges and universities, help the education chain, talent chain and industrial chain to connect deeply, and promote the high-quality development of GIS in the era of spatial intelligence.

Keywords

AI Era; General Big Model; GIS Education; Talent Training; Reconstruction

References

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