教育領導與管理研究應用IPA、IPGA與IPMA

Applying IPA, IPGA and IPMA in Educational Leadership and Management Researches

重要－表現分析（IPA）、重要－表現差距分析（IPGA）、重要－表現圖示分析（IPMA）分析測量項目或構念的重要性和表現度及進行分類，目前仍存在一些爭議待釐清，其裨益教育領導與管理研究了解測量項目和構念的優劣勢。故聚焦分析IPA、IPGA和IPMA的發展情形，並討論教育領導與管理研究如何應用。本文經文件分析、系統性評論，指出三種研究方法的理論基礎、釐清相關中譯名稱、簡述有關發展構想、說明分析流程，並提出六種新分析方法和21個新評估指數。最後，以實際資料考驗，發現Z值重要──表現分析（ZIPA）、IPGA差距和總合矩陣（IPGA-GCM）表現優於其他方法，使用表現度值進行IPMA是較佳選擇，區別分析、IPA區別指數、IPGA區別指數和IPMA區別指數能有效評估分析模式的表現。

Importance-performance analysis (IPA), importance-performance gap analysis (IPGA) and importance-performance map analysis (IPMA) analyze the importance and performance domains of measured items or constructs as well as conduct classifications. Nowadays, several issues about IPA, IPGA and IPMA need to clarify. They benefit educational leadership and management researches to understand the analysis the strengths and weakness of measurement items and constructs. Therefore the study conducted document analysis and systemic review, focused upon analyzing the development of IPA, IPGA as well as IPMA, and discussed how to use these methods in educational leadership and management researches. For these three research methods, this study pointed out their theoretical bases, clarified the related translations in Chinese, described briefly developmental ideas, illustrated operational processes, as well as proposed six new analytic methods and 21 new assessment indexes. Finally, empirical testing by using practical data showed that zvalue based importance-performance analysis (ZIPA) and IPGA gap and composite matrix (IPGA-GCM) perform better than other methods. Using performance data to conduct IPMA is a better choice. Discriminant analysis, discrimination index for IPA (DIPA), discrimination index for IPGA (DIPGA) and discrimination index for IPMA (DIPMA) also can validly evaluate the performance of analysis models.