qualitative method research

Cohort 7

By miltenoff | View this Toon at ToonDoo | Create your own Toon

Qualitative Method Research

quote

Data treatment and analysis

Because the questionnaire data comprised both Likert scales and open questions, they were analyzed quantitatively and qualitatively. Textual data (open responses) were qualitatively analyzed by coding: each segment (e.g. a group of words) was assigned to a semantic reference category, as systematically and rigorously as possible. For example, “Using an iPad in class really motivates me to learn” was assigned to the category “positive impact on motivation.” The qualitative analysis was performed using an adapted version of the approaches developed by L’Écuyer (1990) and Huberman and Miles (1991, 1994). Thus, we adopted a content analysis approach using QDAMiner software, which is widely used in qualitative research (see Fielding, 2012; Karsenti, Komis, Depover, & Collin, 2011). For the quantitative analysis, we used SPSS 22.0 software to conduct descriptive and inferential statistics. We also conducted inferential statistics to further explore the iPad’s role in teaching and learning, along with its motivational effect. The results will be presented in a subsequent report (Fievez, & Karsenti, 2013)

Fievez, A., & Karsenti, T. (2013). The iPad in Education: uses, benefits and challenges. A survey of 6057 students and 302 teachers in Quebec, Canada (p. 51). Canada Research Chair in Technologies in Education. Retrieved from https://www.academia.edu/5366978/The_iPad_in_Education_uses_benefits_and_challenges._A_survey_of_6057_students_and_302_teachers_in_Quebec_Canada

unquote

 The 20th century notion of conducting a qualitative research by an oral interview and then processing manually your results had triggered in the second half of the 20th century [sometimes] condescending attitudes by researchers from the exact sciences.
The reason was the advent of computing power in the second half of the 20th century, which allowed exact sciences to claim “scientific” and “data-based” results.
One of the statistical package, SPSS, is today widely known and considered a magnificent tools to bring solid statistically-based argumentation, which further perpetuates the superiority of quantitative over qualitative method.
At the same time, qualitative researchers continue to lag behind, mostly due to the inertia of their approach to qualitative analysis. Qualitative analysis continues to be processed in the olden ways. While there is nothing wrong with the “olden” ways, harnessing computational power can streamline the “olden ways” process and even present options, which the “human eye” sometimes misses.
Below are some suggestions, you may consider, when you embark on the path of qualitative research.
The Use of Qualitative Content Analysis in Case Study Research
Florian Kohlbacher
http://www.qualitative-research.net/index.php/fqs/article/view/75/153

excellent guide to the structure of a qualitative research

Palys, T., & Atchison, C. (2012). Qualitative Research in the Digital Era: Obstacles and Opportunities. International Journal Of Qualitative Methods, 11(4), 352-367.
http://login.libproxy.stcloudstate.edu/login?qurl=http%3a%2f%2fsearch.ebscohost.com%2flogin.aspx%3fdirect%3dtrue%26db%3dkeh%26AN%3d89171709%26site%3dehost-live%26scope%3dsite
Palys and Atchison (2012) present a compelling case to bring your qualitative research to the level of the quantitative research by using modern tools for qualitative analysis.
1. The authors correctly promote NVivo as the “jaguar’ of the qualitative research method tools. Be aware, however, about the existence of other “Geo Metro” tools, which, for your research, might achieve the same result (see bottom of this blog entry).
2. The authors promote a new type of approach to Chapter 2 doctoral dissertation and namely OCR-ing PDF articles (most of your literature as of 2017 is mostly either in PDF or electronic textual format) through applications such as
Abbyy Fine Reader, https://www.abbyy.com/en-us/finereader/
OmniPage,  http://www.nuance.com/for-individuals/by-product/omnipage/index.htm
Readirus http://www.irislink.com/EN-US/c1462/Readiris-16-for-Windows—OCR-Software.aspx
The text from the articles is processed either through NVIVO or related programs (see bottom of this blog entry). As the authors propose: ” This is immediately useful for literature review and proposal writing, and continues through the research design, data gathering, and analysis stages— where NVivo’s flexibility for many different sources of data (including audio, video, graphic, and text) are well known—of writing for publication” (p. 353).
In other words, you can try to wrap your head around huge amount of textual information, but you can also approach the task by a parallel process of processing the same text with a tool.
 +++++++++++++++++++++++++++++
Here are some suggestions for Computer Assisted / Aided Qualitative Data Analysis Software (CAQDAS) for a small and a large community applications):

– RQDA (the small one): http://rqda.r-forge.r-project.org/ (see on youtube the tutorials of Metin Caliskan); one active developper.
GATE (the large one): http://gate.ac.uk/ | https://gate.ac.uk/download/

text mining: https://en.wikipedia.org/wiki/Text_mining
Text mining, also referred to as text data mining, roughly equivalent to text analytics, is the process of deriving high-quality information from text. High-quality information is typically derived through the devising of patterns and trends through means such as statistical pattern learning. Text mining usually involves the process of structuring the input text (usually parsing, along with the addition of some derived linguistic features and the removal of others, and subsequent insertion into a database), deriving patterns within the structured data, and finally evaluation and interpretation of the output.
https://ischool.syr.edu/infospace/2013/04/23/what-is-text-mining/
Qualitative data is descriptive data that cannot be measured in numbers and often includes qualities of appearance like color, texture, and textual description. Quantitative data is numerical, structured data that can be measured. However, there is often slippage between qualitative and quantitative categories. For example, a photograph might traditionally be considered “qualitative data” but when you break it down to the level of pixels, which can be measured.
word of caution, text mining doesn’t generate new facts and is not an end, in and of itself. The process is most useful when the data it generates can be further analyzed by a domain expert, who can bring additional knowledge for a more complete picture. Still, text mining creates new relationships and hypotheses for experts to explore further.

quick and easy:

intermediate:

advanced:

http://tidytextmining.com/

Introduction to GATE Developer  https://youtu.be/o5uhMF15vsA


 

use of RapidMiner:

https://rapidminer.com/pricing/

– Coding Analysis Toolkit (CAT) from University of Pittsburgh and University of Massachusetts
– Raven’s Eye is an online natural language ANALYSIS tool based
– ATLAS.TI
– XSIGTH

– QDA Miner: http://provalisresearch.com/products/qualitative-data-analysis-software/

There is also a free version called QDA Miner Lite with limited functionalities: http://provalisresearch.com/products/qualitative-data-analysis-software/freeware/

– MAXQDA

–  NVivo

– SPSS Text Analytics

– Kwalitan

– Transana (include video transcribing capability)

– XSight

– Nud*ist

(Cited from: https://www.researchgate.net/post/Are_there_any_open-source_alternatives_to_Nvivo [accessed Apr 1, 2017].

– OdinText

IBM Watson Conversation
IBM Watson Text to Speech
Google Translate API
MeTA
LingPipe
NLP4J
Timbl
Colibri Core
CRF++
Frog
Ucto
– CRFsuite

– FoLiA
PyNLPl
openNLP
NLP Compromise
MALLET
Cited from: https://www.g2crowd.com/products/nvivo/competitors/alternatives [accessed April 1, 2017
+++++++++++++++++++++++++
more on quantitative research:

Asamoah, D. A., Sharda, R., Hassan Zadeh, A., & Kalgotra, P. (2017). Preparing a Data Scientist: A Pedagogic Experience in Designing a Big Data Analytics Course. Decision Sciences Journal of Innovative Education, 15(2), 161–190. https://doi.org/10.1111/dsji.12125
++++++++++++++++++++++++
literature on quantitative research:
Borgman, C. L. (2015). Big Data, Little Data, No Data: Scholarship in the Networked World. MIT Press. https://mplus.mnpals.net/vufind/Record/ebr4_1006438
St. Cloud State University MC Main Collection – 2nd floor AZ195 .B66 2015
p. 161 Data scholarship in the Humanities
p. 166 When Are Data?
Philip Chen, C. L., & Zhang, C.-Y. (2014). Data-intensive applications, challenges, techniques and technologies: A survey on Big Data. Information Sciences, 275(Supplement C), 314–347. https://doi.org/10.1016/j.ins.2014.01.015

5 Comments on qualitative method research

  1. Vlad Tverdohleb http://scribbleandscroll.com
    March 21, 2018 at 3:48 pm (1 year ago)

    Thank you for sharing. This is an interesting article.

    Reply

Leave a Reply