本研究目的旨在探討大專籃球選手之情緒智力、壓力因應策略與運動成績之關係。本研究以自編之大專籃球選手情緒智力量表及黃清如(2000)之壓力因應策略量表為研究工具;「101學年度大專籃球運動聯賽」公開組第二級及一般組選手為研究對象,針對樣本採立意抽樣問卷調查方式,由研究者選取45所學校進行問卷調查。回收622份問卷後,計得有效問卷528份,有效回收率為84.9%。所得資料以獨立樣本t檢定、單因子變異數分析、相關分析及邏輯斯迴歸等統計方法進行分析,獲得以下結論: 一、大專籃球選手之情緒智力在不同性別、不同訓練年資及是否具備體保生資格上有顯著差異。 二、大專籃球選手之壓力因應策略在不同性別、不同訓練年資及是否具備體保生資格上有顯著差異。 三、情緒智力與壓力因應策略具有顯著的正向關係。 四、大專籃球選手之情緒智力會正向影響運動成績。 五、大專籃球選手之壓力因應策略會正向影響運動成績。 關鍵詞:公開組第二級、一般組、體保生、全國賽、邏輯斯迴歸分析
This study focuses on exploring the relationship between college basketball players’ emotional intelligence, stress copping strategy, and athletic performance. This study adopts self-edited emotional intelligence scale and the stress copping strategy scale of Huang, Ching-Ju (2000) as research tools, selects players from the open group second level and the general group in the “101 Academic Year College Basketball Sports Union Competition” as the research subjects, uses purposive sampling method for the selected samples, and conducts surveys on 45 researcher selected schools. Within the 622 recovered questionnaires, the valid questionnaires total 528 copies with effective recovering ratio of 84.9%. The obtained data is inspected with independent sample t test, one way ANOVA, related analysis, and logistic regression; the following conclusions are achieved: 1. The emotional intelligence of college basketball player shows significant differences in gender, training seniority, and eligibility of recommended athletic student. 2. The stress copping strategy of college basketball player shows significant differences in gender, training seniority, and eligibility of recommended athletic student. 3. Emotional intelligence and stress copping strategy has significant positive correlation. 4. The emotional intelligence of college basketball player can positively affect the athletic performance 5. The stress copping strategy of college basketball player can positively affect the athletic performance Keyword: Open group second level, General group, Recommended athletic student, National competition, Logistic regression analysis