本文試著以空間統計分析方法探討台灣地區教育成就之城鄉差距。空間自我相關性可估計資料區域聚集的關聯及強度,並可反映資料空間分佈的特性。分析資料以96年大學學科能力測驗成績為主,並利用學生戶籍地郵遞區號的資料,輔以台灣地理資訊系統的應用,以地理區域圖形描繪出在台灣地區學測成績的城鄉差距及其分佈聚集的型態,除了可進一步了解358個鄉鎮之間在學測成績空間分布,並以空間聚集統計值呈現出城鄉教育發展失衡的程度。本文的貢獻在於以空間群聚指標分析學習成就之城鄉差別,避免以人為的行政區域劃分資料,因而可降低估計上的加總偏差;其次,實證結果發現部分鄉鎮的學測表現並不亞於大都會地區,然而部分都會區之教育成就並不如預期中表現優異;最後,從空間例外區之分佈特性隱含改善教育資源分配的問題與契機。
In this paper we take a spatial statistics approach to examine the Taiwan's urban-rural gap in educational attainment. The spatial autocorrelation statistics measure the degree of dependency among observations in a geo-space so that the spatial clustering association and intensity of the data at proximal locations can be analyzed. Based on the data on the subject competency test in 2007, along with the zip code of students' permanent residence, we integrate spatial statistics and Geographic Information Systems (GIS) to graphically map the clustering patterns of test scores across the 358 townships of Taiwan. In that sense, the spatial clustering index provides a better view into the spatial distribution of test performance, and highlights the magnitude of the unbalanced education development over the Taiwan region. The contributions of this paper are threefold: First, we spatially depict the urban-rural disparity in educational attainment so as to avoid artificial data division imposed by administrative districts. As a result, the problem of the aggregation bias can be eliminated. Second, our empirical finding indicates that the academic performance in a part of the townships is significantly greater than that in metropolitan areas. But contrary to common belief, test outcomes in several urban areas are not as exceptional as observed by the previous studies. Finally, the scattering of spatial outliers reveals the inherent problems and the promising solutions for improvement of educational resources allocation.