Please have also materials, which might help you organize our thoughts and expedite your Chapter 2 writing….
Do you agree with (did you use) the following observations:
The purpose of the review of the literature is to prove that no one has studied the gap in the knowledge outlined in Chapter 1. The subjects in the Review of Literature should have been introduced in the Background of the Problem in Chapter 1. Chapter 2 is not a textbook of subject matter loosely related to the subject of the study. Every research study that is mentioned should in some way bear upon the gap in the knowledge, and each study that is mentioned should end with the comment that the study did not collect data about the specific gap in the knowledge of the study as outlined in Chapter 1.
The review should be laid out in major sections introduced by organizational generalizations. An organizational generalization can be a subheading so long as the last sentence of the previous section introduces the reader to what the next section will contain. The purpose of this chapter is to cite major conclusions, findings, and methodological issues related to the gap in the knowledge from Chapter 1. It is written for knowledgeable peers from easily retrievable sources of the most recent issue possible.
Empirical literature published within the previous 5 years or less is reviewed to prove no mention of the specific gap in the knowledge that is the subject of the dissertation is in the body of knowledge. Common sense should prevail. Often, to provide a history of the research, it is necessary to cite studies older than 5 years. The object is to acquaint the reader with existing studies relative to the gap in the knowledge and describe who has done the work, when and where the research was completed, and what approaches were used for the methodology, instrumentation, statistical analyses, or all of these subjects.
If very little literature exists, the wise student will write, in effect, a several-paragraph book report by citing the purpose of the study, the methodology, the findings, and the conclusions. If there is an abundance of studies, cite only the most recent studies. Firmly establish the need for the study. Defend the methods and procedures by pointing out other relevant studies that implemented similar methodologies. It should be frequently pointed out to the reader why a particular study did not match the exact purpose of the dissertation.
The Review of Literature ends with a Conclusion that clearly states that, based on the review of the literature, the gap in the knowledge that is the subject of the study has not been studied. Remember that a “summary” is different from a “conclusion.” A Summary, the final main section, introduces the next chapter.
When conducting qualitative data, how many people should be interviewed? Is there a minimum or a max
Here is my take on it:
Simple question, not so simple answer.
Generally, the number of respondents depends on the type of qualitative inquiry: case study methodology, phenomenological study, ethnographic study, or ethnomethodology. However, a rule of thumb is for scholars to achieve saturation point–that is the point in which no fresh information is uncovered in response to an issue that is of interest to the researcher.
If your qualitative method is designed to meet rigor and trustworthiness, thick, rich data is important. To achieve these principles you would need at least 12 interviews, ensuring your participants are the holders of knowledge in the area you intend to investigate. In grounded theory you could start with 12 and interview more if your data is not rich enough.
In IPA the norm tends to be 6 interviews.
You may check the sample size in peer reviewed qualitative publications in your field to find out about popular practice. In all depends on the research problem, choice of specific qualitative approach and theoretical framework, so the answer to your question will vary from few to few dozens.
How many interviews are needed in a qualitative research?
There are different views in literature and no one agreed to the exact number. Here I reviewed some mostly cited references. Based Creswell (2014), it is estimated that 16 participants will provide rich and detailed data. There are a couple of researchers agreed on 10–15 in-depth interviews are sufficient (Guest, Bunce & Johnson 2006; Baker & Edwards 2012).
your methodological choices need to reflect your ontological position and understanding of knowledge production, and that’s also where you can argue a strong case for smaller qualitative studies, as you say. This is not only a problem for certain subjects, I think it’s a problem in certain departments or journals across the board of social science research, as it’s a question of academic culture.
here more serious literature and research (in case you need to cite in Chapter 3)
Sample Size and Saturation in PhD Studies Using Qualitative Interviews
Gaskell, George (2000). Individual and Group Interviewing. In Martin W. Bauer & George Gaskell (Eds.), Qualitative Researching With Text, Image and Sound. A Practical Handbook (pp. 38-56). London: SAGE Publications.
Books on intro to stat modeling available at the library. I understand the major pain borrowing books from the SCSU library can constitute, but you can use the titles and the authors and see if you can borrow them from your local public library
I also sought and shared with you “visual” explanations of the basics terms and concepts. Once you start looking at those, you should be able to further research (e.g. YouTube) and find suitable sources for your learning style.
I (and the future cohorts) will deeply appreciate if you remember to share those “suitable sources for your learning style” either by sharing in this Google Group thread and/or sharing in the comments section of the blog entry: https://blog.stcloudstate.edu/ims/2017/07/10/intro-to-stat-modeling. Your Facebook group page is also a good place to discuss among ourselves best practices to learn and use research methods for your chapter 3.
Watching the video, you may remember the same #BooleanSearch techniques from our BI (bibliography instruction) session of last semester.
Considering the fact of preponderance of information in 2017: your Chapter 2 is NOT ONLY about finding information regrading your topic.
Your Chapter 2 is about proving your extensive research of the existing literature.
The techniques presented in the short video will arm you with methods to dig deeper and look further.
If you would like to do a decent job exploring all corners of the vast area called Internet, please consider other search engines similar to Google Scholar:
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)
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.
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).
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.
Pros and Cons of Computer Assisted Qualitative Data Analysis Software
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:
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
Shortly: Limitations are influences that the researcher cannot control. They are the shortcomings, conditions or influences that cannot be controlled by the researcher that place restrictions on your methodology and conclusions. Any limitations that might influence the results should be mentioned. Delimitationsare choices made by the researcher which should be mentioned. They describe the boundaries that you have set for the study. Assumptions are accepted as true, or at least plausible, by researchers and peers who will read your dissertation or thesis.
Roberts, C. (2010). The Dissertation Journey. A Practical and Comprehensive Guide to Planing, Writing, and Defending Your Dissertation. Corwin, Thousand Oaks, CA.
Purpose and scope
We talked about “themes” and the need to be careful with breaking them into “subthemes”: if you do a historical overview, avoid chunking it into “dates” and rather keep the thematic relation. Make sure that the relate to your topic; that’s why it is good to keep your title (even if preliminary), outline (even if in progress), thesis (even if under work) etc. on the first page of your Chapter 2 manuscript / draft.
focus the purpose of your study more precisely.
Avoid postponing finalizing the title, the thesis, the outline.
From the The EDUCAUSE Blended and Online Learning Constituent Group Listserv <BLEND-ONLINE@LISTSERV.EDUCAUSE.EDU>
Can you recommend a peer-reviewed research article that addresses the learning outcomes/learning effectiveness of asynchronous vs. synchronous teaching approaches in online courses?
We have a program that has required weekly synchronous sessions (held via Bb Collaborate) that support the otherwise asynchronous courses in the program. The department is considering making that requirement optional to accommodate worldwide learners, but there are faculty who are concerned about the impact to the learning and transfer of knowledge to the students.
Any research that addresses the differences in these teaching modalities when it comes to learning outcomes?
Thanks in advance, Kristen Kristen Brown Assistant Director, Online Learning Delphi Center for Teaching and Learning
I am happy to share my own dissertation research which specifically focused on this topic as well. Please email me and I will share. firstname.lastname@example.org My note: I emailed Andy and will attach his dissertation to this blog, if interest
Here is a preliminary plan. We will not follow it strictly; it is just an idea about the topics we would like to cover. Shall there be points of interest, please feel free to contribute prior and during the session.
Keeping in mind the ED 610 Learning Goals and Objectives, namely:
Understand and demonstrate how to write literature review in the field of the C&I research
Understand the related research methods in both quantitative and qualitative perspectives from the explored research articles
Understand how to use searching engine to find meaningful articles
Interpret and do critical thinking in C&I research articles
lets review our search and research skills:
How do we search?
Google and Google Scholar (more focused, peer reviewed, academic content)
What is a DOI? A Digital Object Identifier (DOI) is assigned to electronic journal articles (and selected other online content) to specifically and permanently identify and access that article. Most of the standard academic citation formats now require the inclusion of DOIs within a citation when available.
How to find a DOI: Most current academic journal articles include a DOI (usually listed on the first page of the article). Most library databases list a DOI with the record for recent academic journal articles. Most non-academic articles (including magazine and newspaper articles) as well as many older academic journal articles do not have a DOI. Crossref.org provides a DOI Lookup service that will search for a DOI based on citation information (author’s last name, journal name, article title, etc.).
How to access an article via a DOI: Use the CSU Stanislaus Library DOI Look-up for options provided by the library, including access to the full-text via the publisher’s site or a library database service when available. Other, general DOI look-up systems (CrossRef & DOI.org) usually link to the article’s “homepage” on the publisher’s site (which usually include a free abstract but full-text access is restricted to subscribers).
Bibliographical data analysis with Zotero and nVivo
Bibliographic Analysis for Graduate Students, EDAD 518, Fri/Sat, May 15/16, 2020
This session will not be about qualitative research (QR) only, but rather about a modern 21st century approach toward the analysis of your literature review in Chapter 2.
However, the computational approach toward qualitative research is not much different than computational approach for your quantitative research; you need to be versed in each of them, thus familiarity with nVivo for qualitative research and with SPSS for quantitative research should be pursued by any doctoral student.
Please use this link to install nVivo on your computer. Even if we were not in a quarantine and you would have been able to use the licensed nVivo software on campus, for convenience (working on your dissertation from home), most probably, you would have used the shareware. Shareware is fully functional on your computer for 14 days, so calculate the time you will be using it and mind the date of installation and your consequent work.
For the purpose of this workshop, please install nVivo on your computer early morning on Saturday, May 16, so we can work together on nVivo during the day and you can continue using the software for the next two weeks.
Please familiarize yourself with the two articles assigned in the EDAD 815 D2L course content “Practice Research Articles“ :
Brosky, D. (2011). Micropolitics in the School: Teacher Leaders’ Use of Political Skill and Influence Tactics. International Journal of Educational Leadership Preparation, 6(1). https://eric.ed.gov/?id=EJ972880
whereas the snapshots are replaced with snapshots from nVivol, version 12, which we will be using in our course and for our dissertations.
Concept of bibliographic data
Bibliographic Data is an organized collection of references to publish in literature that includes journals, magazine articles, newspaper articles, conference proceedings, reports, government and legal publications. The bibliographical data is important for writing the literature review of a research. This data is usually saved and organized in databases like Mendeley or Endnote. Nvivo provides the option to import bibliographical data from these databases directly. One can import End Note library or Mendeley library into Nvivo. Similar to interview transcripts, one can represent and analyze bibliographical data using Nvivo. To start with bibliographical data representation, this article previews the processing of literature review in Nvivo.
Importing bibliographical data
Bibliographic Data is imported using Mendeley, Endnote and other such databases or applications that are supported with Nvivo. Bibliographical data here refers to material in the form of articles, journals or conference proceedings. Common factors among all of these data are the author’s name and year of publication. Therefore, Nvivo helps to import and arrange these data with their titles as author’s name and year of publication. The process of importing bibliographical data is presented in the figures below.
select the appropriate data from external folder
Coding strategies for literature review
Coding is a process of identifying important parts or patterns in the sources and organizing them in theme node. Sources in case of literature review include material in the form of PDF. That means literature review in Nvivo requires grouping of information from PDF files in the forms of theme nodes. Nodes directly do not create content for literature review, they present ideas simply to help in framing a literature review. Nodes can be created on the basis of theme of the study, results of the study, major findings of the study or any other important information of the study. After creating nodes, code the information of each of the articles into its respective codes.
Nvivo allows coding the articles for preparing a literature review. Articles have tremendous amount of text and information in the forms of graphs, more importantly, articles are in the format of PDF. Since Nvivo does not allow editing PDF files, apply manual coding in case of literature review. There are two strategies of coding articles in Nvivo.
Code the text of PDF files into a new Node.
Code the text of PDF file into an existing Node. The procedure of manual coding in literature review is similar to interview transcripts.
The Case Nodes of articles are created as per the author name or year of the publication.
For example: Create a case node with the name of that author and attach all articles in case of multiple articles of same Author in a row with different information. For instance in figure below, five articles of same author’s name, i.e., Mr. Toppings have been selected together to group in a case Node. Prepare case nodes like this then effortlessly search information based on different author’s opinion for writing empirical review in the literature.
Nvivo questions for literature review
Apart from the coding on themes, evidences, authors or opinions in different articles, run different queries based on the aim of the study. Nvivo contains different types of search tools that helps to find information in and across different articles. With the purpose of literature review, this article presents a brief overview of word frequency search, text search, and coding query in Nvivo.
Word frequency in Nvivo allows searching for different words in the articles. In case of literature review, use word frequency to search for a word. This will help to find what different author has stated about the word in the article. Run word frequency on all types of sources and limit the number of words which are not useful to write the literature.
For example, run the command of word frequency with the limit of 100 most frequent words . This will help in assessing if any of these words remotely provide any new information for the literature (figure below).
Text search is more elaborative tool then word frequency search in Nvivo. It allows Nvivo to search for a particular phrase or expression in the articles. Also, Nvivo gives the opportunity to make a node out of text search if a particular word, phrase or expression is found useful for literature.
For example: conduct a text search query to find a word “Scaffolding” in the articles. In this case Nvivo will provide all the words, phrases and expression slightly related to this word across all the articles (Figure 8 & 9). The difference between test search and word frequency lies in generating texts, sentences and phrases in the latter related to the queried word.
Apart from text search and word frequency search Nvivo also provides the option of coding query. Coding query helps in literature review to know the intersection between two Nodes. As mentioned previously, nodes contains the information from the articles. Furthermore it is also possible that two nodes contain similar set of information. Therefore, coding query helps to condense this information in the form of two way table which represents the intersection between selected nodes.
For example, in below figure, researcher have search the intersection between three nodes namely, academics, psychological and social on the basis of three attributes namely qantitative, qualitative and mixed research. This coding theory is performed to know which of the selected themes nodes have all types of attributes. Like, Coding Matrix in figure below shows that academic have all three types of attributes that is research (quantitative, qualitative and mixed). Where psychological has only two types of attributes research (quantitative and mixed).
In this way, Coding query helps researchers to generate intersection between two or more theme nodes. This also simplifies the pattern of qualitative data to write literature.
Please do not hesitate to contact me with questions, suggestions before, during or after our workshop and about ANY questions and suggestions you may have about your Chapter 2 and, particularly about your literature review:
News and Media Literacy (and the lack of) is not very different from Information Literacy
An “information literate” student is able to “locate, evaluate, and effectively use information from diverse sources.” See more About Information Literacy
Developing Your Research Topic/Question
Research always starts with a question. But the success of your research also depends on how you formulate that question. If your topic is too broad or too narrow, you may have trouble finding information when you search. When developing your question/topic, consider the following:
Is my question one that is likely to have been researched and for which data have been published? Believe it or not, not every topic has been researched and/or published in the literature.
Be flexible. Consider broadening or narrowing the topic if you are getting a limited number or an overwhelming number of results when you search. In nursing it can be helpful to narrow by thinking about a specific population (gender, age, disease or condition, etc.), intervention, or outcome.
Discuss your topic with your professor and be willing to alter your topic according to the guidance you receive.
Getting Ready for Research
Library Resources vs. the Internet
How (where from) do you receive information about your professional interests?
Advantages/disadvantages of using Web Resources
Become a member of professional organizations and use their online information
Use the SCSU library page to online databases
Building Your List of Keywords
Why Keyword Searching?
Why not just type in a phrase or sentence like you do in Google or Yahoo!?
Because most electronic databases store and retrieve information differently than Internet search engines.
A databases searches fields within a collection of records. These fields include the information commonly found in a citation plus an abstract (if available) and subject headings. Search engines search web content which is typically the full text of sources.
The bottom line: you get better results in a database by using effective keyword search strategies.
To develop an effective search strategy, you need to:
determine the key concepts in your topic and
develop a good list of keyword synonyms.
Why use synonyms?
Because there is more than one way to express a concept or idea. You don’t know if the article you’re looking for uses the same expression for a key concept that you are using.
Consider: Will an author use:
Hypertension or High Blood Pressure?
Teach or Instruct?
Therapy or Treatment?
Don’t get “keyword lock!” Be willing to try a different term as a keyword. If you are having trouble thinking of synonyms, check a thesaurus, dictionary, or reference book for ideas.
How to find the SCSU Library Website
SCSU online databases
SCSU Library Web page
Test your knowledge:
******* !! *************
Basic Research Skills
Identifying a Scholarly Source
How do you evaluate a source of information to determine if it is appropriate for academic/scholarly use. There is no set “checklist” to complete but below are some criteria to consider when you are evaluating a source.
Does the author cite reliable sources?
How does the information compare with that in other works on the topic?
Can you determine if the information has gone through peer-review?
Are there factual, spelling, typographical, or grammatical errors?
Who do you think the authors are trying to reach?
Is the language, vocabulary, style and tone appropriate for intended audience?
What are the audience demographics? (age, educational level, etc.)
Are the authors targeting a particular group or segment of society?
Who wrote the information found in the article or on the site?
What are the author’s credentials/qualifications for this particular topic?
Is the author affiliated with a particular organization or institution?
What does that affiliation suggest about the author?
Is the content current?
Does the date of the information directly affect the accuracy or usefulness of the information?
What is the author’s or website’s point of view?
Is the point of view subtle or explicit?
Is the information presented as fact or opinion?
If opinion, is the opinion supported by credible data or informed argument?
Is the information one-sided?
Are alternate views represented?
Does the point of view affect how you view the information?
What is the author’s purpose or objective, to explain, provide new information or news, entertain, persuade or sell?
Does the purpose affect how you view the information presented?