景觀評估中之心理學模式之研究

A Study of the Psychological Model for Scenic Beauty Assessment

李英弘(Ying-Hung Li) ； 梁文嘉(Wen-Chia Liang)

《造園景觀學報》 7卷1期 (2000/08) Pp. 67-87

https://doi.org/10.6950/JL.200008.0067

摘要

在景觀評估研究中，Kaplan & Kaplan 的環境偏好矩陣已被廣泛的應用於心理學評估模式之中。本研究主要目的除了想瞭解受測者對景觀刺激所產生的心理層面感受外，也嘗試研擬出Kaplan & Kaplan 環境偏好矩陣評估因子之中文操作性定義。本研究的景觀調查地點選擇中部東海大學校園，採用兩階段問卷：第一階段在研究地區作景觀點的調查選定，以東海大學的學生為樣本。將東海大學的28個景觀點勾選出十個景觀點，所得的結果，做為第二階段景觀點拍照的依據。每一景觀點隨機抽取三張景觀幻燈片，共得30張幻燈片。景觀偏好調查的受測者以靜宜大學觀光系學生共105人，針對每一張景觀幻燈片回答由語意分析法所研擬出的14對形容詞句。研究結果發現，在10個景觀點中，以文理大道的景觀美質最高，女鬼橋次之，路思義教堂第三。而藝術中心的景觀美質最低，中正紀念堂及圖書館則分佔美質倒數2、3名。在逐步多元迴歸（stepwise）分析中，9對形容詞中以新奇的––無趣、連貫––不連貫、沒規則、次序––有規則、次序三組形容詞具顯著預測能力（R 2 = 0.96，p ＜0.01）。以KapIan & KapIan 的四個評估因子而言，在逐步多元迴歸（stepwise）分析中，除複雜性之外，其餘三個因子（一致性、易讀性、及神秘性）均能顯著的預測景觀美質（R2=0.88，p＜0.01）。

關鍵字

視覺偏好 ； 環境偏好矩陣 ； 語意分析法

並列摘要

The purposes of this study were to understand psychological response of people when they viewed scenery, and to propose Chinese operationalizations of four psychological variables. There were two steps in the survey procedure. First, students in Tunghai University were sampled to select ten scenic spots out of twenty-eight with in Tunghai University. Second, three photos were taken for each scenic point. As a result, 30 photos were taken as stimuli for the scenic beauty survey. Then, 106 students in Providence University were asked to participate this survey. The result showed that Wen-Lei Avenue had the highest scenic beauty, and Art Center had the lowest scenic beauty. Using step-wise regression analysis, pair-wise adjectives suchas novel-- uninterested, continuous -- noncontinuous, unregulated & non-ordered -- regulated & ordered were significant inpredicting scenic beauty(R^2 =0.96, p＜.OI). By way of Kaplan& Kaplan's model to predict scenic beauty, coherence, legibility, and mystery were significant using step-wise regression analysis (R^2=Q.88, p＜. 01). The Chinese operationalizations of four psychological variables were produced as well.

並列關鍵字

visual preference ； environmental preference matrix ； semantic differential