This study investigates the spatiotemporal evolution of China’s regular higher education institutions (HEIs) from 1952 to 2023 using ArcGIS spatial analysis to determine spatial patterns and evolutionary trends. By integrating the Geographical Detector and Multi-scale Geographically Weighted Regression (MGWR) models, we analyze the driving factors of—and their spatial heterogeneity in shaping—HEI distribution. Findings reveal that (1) the spatial distribution of China’s HEIs has become increasingly clustered, transitioning from a “point-like” to a “network-like” and finally to a “surface-like” pattern, with its center shifting southwestward. (2) HEIs’ spatial differentiation results from multiple interacting factors, with significant variations in their explanatory power. Key drivers include the number of full-time faculty, regional GDP, national universities’ presence during the Republic of China era, and fiscal expenditure on education. Regional population size also exerts a notable influence. (3) The impact of these factors exhibits significant spatial heterogeneity, with pronounced local imbalances. In short, multi-scale processes operating at different geographical levels have shaped HEIs’ spatial pattern. These findings provide critical insights for optimizing higher education resource allocation, promoting balanced regional development, and advancing the construction of a high-quality education system in China.

China’s higher education system is the largest globally but faces significant spatial imbalance issues. While studies have examined the spatial distribution of universities, long-term dynamic analysis, quantitative exploration of influencing factors, and investigation of spatial heterogeneity are lacking. This study investigates the spatiotemporal evolution of China’s regular higher education institutions (HEIs) from 1952 to 2023 by using ArcGIS spatial analysis and integrating the Geographical Detector and Multi-scale Geographically Weighted Regression (MGWR) models. Findings reveal that (1) the spatial distribution of China’s HEIs has become increasingly clustered, transitioning from a “point-like” to a “network-like” and finally to a “surface-like” pattern, with its center shifting southwestward—this evolution reflects the gradual formation of a spatially sustainable layout that adapts to regional development needs. (2) Multiple interacting factors influence distribution—including the number of full-time faculty, regional GDP, national universities’ presence during the Republic of China era, and fiscal expenditure on education—with significant variations in their explanatory power. Regional population size also exerts a notable influence. (3) The impact of these factors exhibits significant spatial heterogeneity, with pronounced local imbalances. Thus, multi-scale processes operating at different geographical levels have shaped HEIs’ spatial pattern and addressing this heterogeneity is a key prerequisite for achieving sustainable and equitable development of higher education. These findings provide critical insights for optimizing higher education resource allocation, promoting balanced regional development, and advancing the construction of a high-quality education system in China.