高級職業學校圖書館於校園位置與周圍設施對圖書館使用之關聯研究

Abstract

本研究旨在探索我國高級職業學校（簡稱高職學校）圖書館於校園內所在位置周圍設施對於圖書館使用量的關聯。分析面向包含高職學校圖書館於校園內所在位置周圍設施型態之分佈、周圍設施與學校規模中的員生人數與招生狀況、圖書館資源配置程度中的圖書館平均服務員生人數、每人館藏擁有量與館藏成長量、以及圖書館使用量之平均圖書借閱量等研究變項之間的關聯。 研究對象為全國129所高職學校。研究變項包括了圖書館統計和各校圖書館所在位置周圍設施。圖書館統計資料係取自於高級中學圖書館現況資料庫之105學年度上下學期間各高職學校圖書館統計資料。各校圖書館所在位置周圍設施則是從各校網頁上公開之校區平面圖進行編碼分類。本研究的分析方法採兼具多維度、數值式與限制性的教育資料探勘之關聯規則分析，分析工具為資料探勘工具開放軟體Weka中的HotSpot演算法，透過將各校學校圖書館周圍的不同設施作為前提規則，再將學校規模、圖書館資源配置程度和圖書館使用量中的各個研究變項之高與低分群聚焦為結果規則，以關聯規則指標找出關聯程度較高的關聯規則來歸納研究結果。 研究結果歸納如下：（一）高職學校圖書館周圍最常見的設施依序為「通道區」、「專科教室」或「普科教室」，最少見的則為「校園生活區」或「其他設施」；（二）當圖書館鄰近「校園生活區」或「景觀休憩區」時，與員生人數低分群的關聯程度較高：而其他設施則是與員生人數高分群的關聯程度較高；（三）當圖書館周圍有「景觀休憩區」、「校園生活區」或「通道區」時，與招生狀況正常分群的關聯程度較高；而當周圍有「其他設施」、「普科教室」或「教職員行政區」時，則與招生狀況不順分群的關聯程度較高；（四）當圖書館周圍有「景觀休憩區」或「專科教室」時，與圖書館平均服務員生人數負擔低分群的關聯程度較高；當周圍有「普科教室」時，與圖書館平均服務員生人數負擔高分群的關聯程度較高；（五）當圖書館周圍有「動態活動區」、「景觀休憩區」或「其他設施」時，與每人館藏擁有量高分群的關聯程度較高；當周圍有「校園圍牆與邊界」、「校園生活區」或「普科教室」時，與每人館藏擁有量低分群的關聯程度較高；（六）當圖書館周圍有「校園出入口」、「通道區」、「行政服務區」或「教職員行政區」時，與館藏成長量高分群的關聯程度較高；當周圍有「普科教室」、「校園生活區」或「其他設施」時，與館藏成長量低分群的聯程度較高；（七）當圖書館周圍有「教職員行政區」、「動態活動區」、「景觀休憩區」或「專科教室」，與平均圖書借閱量高分群的關聯程度較高；當周圍有「校園生活區」、「其他設施」或「行政服務區」時，與平均圖書借閱量低分群的關聯程度較高；（八）除了員生人數之外，館藏成長量的多寡與圖書借閱量的高低有較高的關聯程度，值得後續研究注意。總結以上所述，當高職學校圖書館鄰近「動態活動區」、「景觀休憩區」或「專科教室」時，可能會與圖書館之擁有資源與使用量有正面的關聯；當圖書館鄰近「校園生活區」或「其他設施」時，則可能會有負面的關聯。 根據以上研究結果，本研究提出以下建議：（一）高職在規劃新館或調整校園設施時，可參酌使用本研究歸納之關聯規則；（二）建議高職學校圖書館儘量增加館藏量以提升圖書館使用量；（三）建議校方及館方多加利用學校圖書館統計來發現圖書館有待改善之處；（四）建議高級中學圖書館現況資料庫提供學校代碼並納入更多種類的圖書館統計數據，並且改善資料填報的正確性。The purpose of this study was to explore the association between the locations of Taiwanese vocational senior high school libraries in campuses and library usage. The analysis included the following research variables: campus facilities surrounding every library and their distribution, school population, school enrollment, number of patrons served per library faculty, number of library holdings per capita, growth rate of library holdings, and average borrowing rate. The valid objects of this study were 129 Taiwanese vocational senior high schools. The research variables were library statistics and the facilities surrounding every library. Library statistics were extracted from the Database of High School Libraries collected by Ministry of Education, and the reference period ran throughout the 2016/17 academic year. As for the facilities surrounding the libraries, they were determined and then categorized though the interpretation of campus facility maps. The maps were open information taken from the official website of each school. The method of analysis in this study was association rules mining of educational data mining with hybrid-dimensional, quantitative and constraint-based features. HotSpot algorithm in the open source data mining tool Weka was the analysis tool for this study. The surrounding facilities were set on the left-hand side, while other research variables were each clustered into high or low group before setting on the right-hand side. The research results were concluded by the indicators with strong associations. The research results were concluded as fellows. First, the three most common campus facilities surrounding school libraries were "passageway", "subject-based classroom", and "regular classroom", while the two least common facilities were "campus living area" and "other facilities". Second, there were strong associations between the libraries located near "campus living area" or "campus landscape" and the low-scored group of school population, while the libraries near “other facilities” and the high-scored group of school population were strongly associated. Third, there were strong associations between libraries located near "campus landscape", "campus living area", or "passageway" and the high-scored group of enrollment, while the libraries near other facilities, “regular classroom”, or “teaching faculty office” and the low-scored group of enrollment were strongly associated. Fourth, there were strong associations between the libraries located near "campus landscape" or "subject-based classroom" and fewer patrons served per library faculty, while the libraries near "regular classroom" and more patrons served per library faculty was strongly associated. Fifth, there were strong associations between the libraries located near "physical activities facility", "campus landscape", or “other facilities” and a higher number of library holdings per capita, while the libraries near “campus boundary”, “campus living area” or “regular classroom” and a lower number of library holdings per capita were strongly associated. Sixth, there were strong associations between the libraries located near "campus entrance gate", "passageway", "administrative service area", or "teaching faculty office" and a higher growth rate of library holdings, while the libraries near “regular classroom”, “campus living area” or “other facilities” and a lower growth rate were strongly associated. Seventh, there were strong associations between the libraries located near "teaching faculty office", "physical activities facility", "campus landscape", or "subject-based classroom" and a higher average borrowing rate, while the libraries near “campus living area”, “other facilities”, or “administrative service area” and a lower average borrowing rate were strongly associated. Eighth, in addition to school population, there was a strong association between growth rate of library holdings and average borrowing rate, which was worthy of further research. To sum up, there could be positive associations between vocational high school libraries located near "physical activities facility", "campus landscape" or "subject-based classroom" and library resource or library usage while there could be negative associations when libraries were located near "campus living area" or "other facility". The researcher's recommendations based upon this study include the following: First, the association rules concluded in this study could be considered when planning for new vocational senior high school library building or rearranging school facilities. Second, library holdings in vocational senior high school should be enhanced to improve library usage. Third, library statistics can be used to discover the inadequacies of a library. Fourth, the Database of High School Library should include school codes and more types of library statistics and to improve data accuracy.