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: http://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.
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).
Launched in 2000 as a project of the OECD, the PISA is administered every three years to nationally representative samples of students in each OECD country and in a growing number of partner countries and subnational units such as Shanghai. The 74 education systems that participated in the latest PISA study, conducted during 2009, represented more than 85% of the global economy and included virtually all of the United States’ major trading partners, making it a particularly useful source of information on U.S. students’ relative standing.
The United States’ historical advantage in terms of educational attainment has long since eroded, however. U.S. high-school graduation rates peaked in 1970 at roughly 80% and have declined slightly since, a trend often masked in official statistics by the growing number of students receiving alternative credentials, such as a General Educational Development (GED) certificate.
in many respects the U.S. higher education system remains the envy of the world. Despite recent concerns about rapidly increasing costs, declining degree completion rates, and the quality of instruction available to undergraduate students, U.S. universities continue to dominate world rankings of research productivity. The 2011 Academic Rankings of World Universities, an annual publication of the Shanghai Jiao Tong University, placed eight U.S. universities within the global top 10, 17 within the top 20, and 151 within the top 500. A 2008 RAND study commissioned by the U.S. Department of Defense found that 63% of the world’s most highly cited academic papers in science and technology were produced by researchers based in the United States. Moreover, the United States remains the top destination for graduate students studying outside of their own countries, attracting 19% of all foreign students in 2008. This rate is nine percentage points higher than the rate of the closest U.S. competitor, the United Kingdom.
Abel, H. (1959). Polytechnische Bildung und Berufserziehung in internationaler Sicht. International Review of Education / Internationale Zeitschrift für Erziehungswissenschaft / Revue Internationale de l’Education, 5(4), 369–382. https://doi.org/10.1007/BF01417254
At one time it was left to teachers and administrators to decide exactiy what level of math proficiency should be expected of students. But, increasingly, states, and the federal government itself, have established proficiency levels that students are asked to reach. A national proficiency standard was set by the board that governs the National Assessment of Educational Progress (NAEP), which is administered by the U.S. Department of Education and generally known as the nation’s report card.
a crosswalk between NAEP and PISA. The crosswalk is made possible by the fact that representative (but separate) samples of the high-school graduating Class of 2011 took the NAEP and PISA math and reading examinations. NAEP tests were taken in 2007 when the Class of 2011 was in 8th grade and PISA tested 15-year-olds in 2009, most of whom are members of the Class of 2011. Given that NAEP identified 32 percent of U.S. 8th-grade students as proficient in math, the PISA equivalent is estimated by calculating the minimum score reached by the top-performing 32 percent of U.S. students participating in the 2009 PISA test. (See methodological sidebar for further details.)
++++++++++ dissertations ++++++++++++++
CAO perspectives: The role of general education objectives in career and technical programs in the United States and Europe
by Schanker, Jennifer Ballard, Ed.D., National-Louis University, 2011, 162; 3459884
presence (VR different from other media), virtual pit, haptic devices and environment
4 min: what’s the point?…
VR is a paradox, no rules,
what should you do and what to avoid
Ketaki Shriram dissertation
Gerd Bruder observed the other German person confused between VR and real world.
Common Sense Media – when children can VR and for how long
Jackie Baily worked with children VR Sesame street Grover impossible, counterproductive, rare/expensive, dangerous are the 4 reasons to use it. Not ubiquitous!
12 min. empathy
Tobin Asher “Becoming Homeless” blame the situation or the character (min 17)
June Lubchenko, 2013. NOAA. min 19. natural disasters, not trusting self-report, but actions.
Fio Micheli. counter productive to fly children to the coral in Italy, but VR makes it possible. learning efficacy. Motivation to learn. min 21.
min 26. MOOC – materials are for free. not replacing field trips, just making them more often.
min 27. spherical video to practice football with VR
min 29. Walmart – “academies” Mark Gill the nursing home simulation.
learning to drive.
freedom speech over all media but VR is specific, different. If you won’t do it in the real world, don’t do it in VR
min 33. what is the iPhone for VR.
min 37. disentization. how many times to do something to have effect. Kathy Mayhew and Mark Gill research
min 38. AR and psychology – not much resources. virtual person breaks physics – walks through chairs. Greg Weltch Central Florida – AR breaks physics study.
min 42. if his lab gives grants for art content creation. Immersive Journalism, storytelling syllabus. Mark Gill for our class, Bill Gorcica . Robert Wood Johnson Foundation, Gordon and Betty Moore Foundation, Mayday Foundation