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.
Here a short presentation on the basics:
Further, if you wish to expand your knowledge, on qualitative research (QR) in this IMS blog:
Workshop on computational practices for QR:
Here is a library instruction session for your course
Once you complete the overview of the resources above, please make sure you have Zotero working on your computer; we will be reviewing the Zotero features before we move to nVivo.
Here materials on Zotero collected in the IMS blog:
Of those materials, you might want to cover at least:
Familiarity with Zotero is a prerequisite for successful work with nVivo, so please if you are already working with Zotero, try to expand your knowledge using the materials above.
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
Tooms, A. K., Kretovics, M. A., & Smialek, C. A. (2007). Principals’ perceptions of politics. International Journal of Leadership in Education, 10(1), 89–100. https://doi.org/10.1080/13603120600950901
It is very important to be familiar with the articles when we start working with nVivo.
How to use Zotero
How to use nVivo for bibliographic analysis
The following guideline is based on this document:
Bibliographical data analysis using Nvivo
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:
Plamen Miltenoff, Ph.D., MLIS
Professor | 320-308-3072 | firstname.lastname@example.org | http://web.stcloudstate.edu/pmiltenoff/faculty/ | schedule a meeting: https://doodle.com/digitalliteracy | Zoom, Google Hangouts, Skype, FaceTalk, Whatsapp, WeChat, Facebook Messenger are only some of the platforms I can desktopshare with you; if you have your preferable platform, I can meet you also at your preference.
more on nVIvo in this IMS blog
more on Zotero in this IMS blog
How to Turn Bad Data Into Good Data
Date: Wednesday, January 22, 2020 Time: 1:00 pm CT
a panel of data and education experts about how to make the most of your education data. In this webinar you’ll learn about:
- How rapid data turnover can hurt you (and your bottom line)
- How to access “good‘‘ data and what it looks like
- Opportunities open to you when your data is clean
- Avoiding the pitfalls of using outdated or irrelevant data and making decisions that are not data informed
- Navigating the unique challenges of working in education, such as privacy regulations that might hinder communication
more on big data in this IMS blog
The Smartphone Generation Needs Computer Help
Young people may be expert social-media and smartphone users, but many lack the digital skills they need for today’s jobs. How can we set them up for success?
Kenneth Cole’s classroom at the Boys & Girls Club of Dane County, located on a quiet residential street in Madison, Wisconsin.
The classes Cole teaches use Grow with Google’s Applied Digital Skills online curriculum.
One day he may lead Club members in a lesson on building digital resumes that can be customized quickly and make job-seeking easier when applying online. Another day they may create a blog. On this particular day, they drew up a budget for an upcoming event using a spreadsheet. For kids who are often glued to their smartphones, these types of digital tasks, surprisingly, can be new experiences.
The vast majority of young Americans have access to a smartphone, and nearly half say they are online “almost constantly.”
But although smartphones can be powerful learning tools when applied productively, these reports of hyperconnectivity and technological proficiency mask a deeper paucity of digital skills. This often-overlooked phenomenon is limiting some young people’s ability—particularly those in rural and low-income communities—to succeed in school and the workplace, where digital skills are increasingly required to collaborate effectively and complete everyday tasks.
According to a survey by Pew Research Center, only 17 percent of Americans are “digitally ready”—that is, confident using digital tools for learning. Meanwhile, in a separate study, American millennials ranked last among a group of their international peers when it came to “problem-solving in technology-rich environments,” such as sending and saving digital information
teach his sophomore pupils the technology skills they need in the workplace, as well as soft skills like teamwork.
more on digitally native in this IMS blog
more on millennials in this IMS blog
K-12 IT leaders need to work with people, not just tech
My note: this is the first step toward the conclusion of my dissertation: the CIO in education must wear three hats: computer geek, educator and administrator.
District Administration reports.
Since edtech varies from district to district and state to state, it’s unlikely that an IT candidate will be up-to-speed on the current system in use. Alabama solves this problem by offering the Alabama Chief Technology Officer certification program.
It is critical for those in K-12 IT leadership to understand the unique customer service needs of the education industry. When technology doesn’t work, it throws a wrench into an entire day of learning. Educators need a fast fix and responsive service. Effective tech leaders will delegate by teaming up with tech-savvy teachers who can serve as school tech leaders. This strategy allows for an on-site tech expert to step in to put out fires before the tech expert arrives.
Former teachers can also make strong chief technology officers because they understand both tech and education. This allows them to build trust with the staff, which is a critical component to launching new technology initiatives.
more on digital literacy for EDAD in this IMS blog
Twelve Years Later: What’s Really Changed in the K-12 Sector? (Part 1)
In fall 2007, Larry Berger, CEO of Wireless Generation (now Amplify) was invited to submit a paper to an “Entrepreneurship in Education”
As education entrepreneurs know, growth in K-12 comes hard. Sometimes very hard. We were living Marc Andreessen’s startup mantra: “You only ever experience two emotions: euphoria and terror.”
The edtech boom of the past two decades promised efficacy and new instructional models. Many teachers instead experience it as “clutter.” But poorly integrated standards, curriculum, assessment, and intervention materials have always been a problem.
When it comes to instruction, the work consists of four segments: core curriculum, supplemental (intervention, test prep, little books) curriculum, assessment, and technology (hardware, infrastructure and connectivity). Each of these workstreams are run by separate teams, using independent funding streams, only rarely coordinating. Schools rely—as they always have—on the hero in the classroom, who has to somehow synthesize everything for a roomful of children, every single day.
Twelve Years Later: How the K-12 Industry and Investment Landscape Has Shifted (Part 2)
Twelve years ago, Amplify CEO Larry Berger and I wrote about the “pareto distribution” of companies in the K-12 sector.
The “oligopoly” was the natural outcome of a highly decentralized system and fragmented demand. To serve 15,000-plus districts and more than 100,000 school buildings, a company needed huge sales and service teams; to afford them, the company needed a bookbag full of products across content areas, grade ranges, and use cases. The structure of demand created the “Big Three”—McGraw-Hill, Houghton Mifflin Harcourt and Pearson.
Meanwhile, the number of small players—further right on the pareto distribution—has grown dramatically. Online distribution and freemium business models have enabled companies like Flocabulary, Newsela, Nearpod, and others
few alternative models to consider:
companies like Remind, ClassDojo, and Edmodo, who all adopted a “West Coast” approach: collect active users now, with plans to monetize later.
The second includes the “platform” players—Schoology, itslearning, Canvas, and other LMS-like platforms. They have set out to do something differently, only possible by means of technology—to be the search, storage and distribution platform for instructional content. Google Classroom has instead emerged as the de facto standard platform, fueled by the runaway adoption of Chromebooks.
The third includes “policy responsive” players—companies like Panorama, Ellevation or Wireless Generation. hese companies help school systems meet a new policy requirement—social-emotional learning, English Language Learning, and reading assessment, respectively.
But we’re not “decluttering” our classrooms or in our schools. What would it take for the private and public sectors to work shoulder-to-shoulder?
a catch-22: so long as buying is fragmented, it’s hard to justify the integrated product investment; so long as products are fragmented, it’s hard for a district to create an integrated instructional model.
Fact or Myth?
Device Implementation Is Possible Without the Headache!
Presented by the Classcraft Learning Team
Eric Davis & Kinshasa Marshall @classcraftgame email@example.com firstname.lastname@example.org
https://www.edweb.net/.5b97fbb8/ Gaming 03-28-19 Slides1-1qgto1x
! Tasks with motivational gamified mechanics → improvement in 21st-century learning skills, technical competencies,
independence, and personal accountability for devices and their readiness
! Student-led, independent, and sophisticated use of devices increased roughly 100%
! “Gamification as a motivational tool and platform for online delivery of learning activities and resources is a critical element of
integrating technology into schools”
! Students placed a greater value on their devices being present and ready to use in order to enjoy gamified content
! The use of gamification capitalized on the curiosity aspect being at the center of intrinsic motivation — encouraging students to
explore what their devices can do for them in general and what they are capable of given the task, some direction, and a
Planning, care FOR and ABOUT the device
What the World Can Teach the US About Education Technology
By Wade Tyler Millward Mar 24, 2019
Omidyar Network’s report on what works in scaling education technology in different regions worldwide. Governments, educators, advocacy groups and companies large and small need to work better together. Long-term planning and investment in infrastructure for widespread and improved access to the internet and mobile devices is critical.
But what may surprise some readers of the report, released Monday, is what the United States can learn from developing nations when it comes to bringing together all parties interested in edtech.
Chief Privacy Officers: The Unicorns of K-12 Education
Last month, the nonprofit Center for Democracy and Technology (CDT) published a report arguing schools and districts should go the way of other industries and hire a Chief Privacy Officer to oversee their organization’s privacy policies and practices.
But the reality is that Chief Privacy Officers in K-12 education are about as common as unicorns.
Two years ago, Denver Public Schools created a new role, the Student Data Privacy Officer, after the Colorado legislature passed a law to promote student data privacy and transparency.
Profile of a technologically literate graduate
By Jorge Valenzuela 1/7/2019
digital equity and digital citizenship
use your divisionwide or statewide profile of a graduate.
STEP 1: Have a model and unpack it
In my state of Virginia (like many other states), we focus on these four:
- Content knowledge
- Workplace skills
- Community engagement and civic responsibility
- Career exploration
STEP 2: Tag team with colleagues to plan instruction
In step one we created our graduate profile by brainstorming and identifying both the personal and professional knowledge and skills that our future graduates need. Now it’s time to formulate plans to bring the profile to fruition. To ensure student success, implementation should take place in the classroom and tap the expertise of our colleagues.
Student success is never due to one teacher, but a collaborative effort.
STEP 3: Identify and leverage the right industry partners
Technological literacy requires students to create authentic products using appropriate edtech, therefore developing technologically literate graduates should not be left entirely to teachers and schools.
Soliciting the help of our industry and business partners is so crucial to this process
Step 4: Create career pathways in schools
schools create systemic K-12 career pathways — or pipelines — for their students and give teachers ample time and space to plan and work together to maximize the learning aligned to well-developed graduate profiles.