NVivo 9.1是質性研究的萬靈丹或科學怪物？

Is NVivo 9.1a Panacea or Frankenstein for Qualitative Research?

本文簡介紮根理論與電腦輔助質性資料分析軟體（Computer-Assisted Qualitative Data Analysis Software， CAQDAS）的關係，提及NVivo 9.1 的歷史與功能，這是一套為質性研究者所設計的套裝軟體，也是NVivo 最新的版本，由Tom 和Lyn Richards 首創。NVivo 9.1 可協助研究者處理無結構資料例如文件、調查、聲音，影像和照片等資訊。同時輸入多元文件是可能的，研究者也可一次輸入它們，NVivo 9.1 在2011 年六月發行，在CAQDAS 中開創豐富文本，隨心所欲地編輯與編碼，且可用質性連結、塑形、過濾、精煉、搜尋和模組。它具備許多工具來探索節點間關係，也提供一些工具從觀察、訪談、文件分析與文獻探討來處理資料、想法、資訊與理論建立。總之，NVivo 的最新版本是一套適當的工具，提供許多功能與布林邏輯促進質性分析，有人視之為萬靈丹，然而，過度倚賴或誤用CAQDAS 分析的成果而缺乏研究者自身的反省，容易簡化實際現場的複雜現象，因此有人視其為科學怪物。當然，這些研究軟體無法取代質性研究者本身，他們只是讓研究繁複的工作更有效率，重點是研究者如何慎選順手的工具。

This article briefly presents the relationship of grounded theory and CAQDAS. The history and functions of NVivo， a software package for qualitative researchers originally created in 1991by Tom and Lyn Richards and its latest version， NVivo 9.1 will be discussed. NVivo 9.1assists researchers to qualitatively analyze unstructured information， such as document， survey， audio， video and picture files， and enables simultaneous multiple documents import. NVivo 9.1was released in June 2011. It pioneered rich text in CAQDAS， which is freely edited and coded， and the integration of coding with many methods of qualitative linking， shaping， filtering， refining， searching and modeling. It is equipped with many tools for examining the relations of nodes and provides various tools to process operating data， ideas， information and theories based on interviews， observations， document analysis， and literature reviews. NVivo is an appropriate tool， which provides many new functions and Boolean logics in its latest version， to improve qualitative analysis. It is therefore that some view it as a panacea. However， if one is excessively dependent upon the outcomes of CAQDAS but who lacks of reflections， it will overly simplify the complicated phenomena of the practical fields. It is the reason that others deem it as a Frankenstein. These packages， of course， won’t study for a qualitative researcher. But they just might make his/her hard work more efficient. It is momentous to confirm that CAQDAS fits appropriately with the data a researcher produces.