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In this study, we adopt a geo-spatial perspective to examine the spatial distribution of a 12-years enrollment pattern in a Taiwanese highly selective technological university. Geocoding 17,381 college students’ home addresses at the village level, our dataset includes the geodemographic variables of the villages and the number of enrolled students from each village. Our analysis contributes to the literature by showing that geodemographic segmentation of enrollment patterns is only partially driven by socioeconomic conditions of villages and primarily driven but geographic proximity. Additionally, we confirm that spatial clustering is evident and that it influences enrollment patterns. Finally, villages with more well-educated residents were more likely to benefit when the university adopted a non-traditional admission pipeline.