Software Review: NVivo as a Teaching Tool

nvivo-logoFor the past few weeks, DASIL has been publishing a series of blog posts comparing the two presidential candidates this year – Hillary Clinton and Donald Trump – using NVivo, a text analysis software. Given the increasing demand for qualitative data analysis in academic research and teaching, this blog post will discuss the strengths and weaknesses of NVivo as a teaching tool in qualitative analysis.

Efficiency and reliability

Using software like NVivo in content analysis can add rigor to qualitative research. Doing word search or coding using NVivo will produce more reliable results than doing so manually since the software rules out human error. Furthermore, NVivo proves to be really useful with large data sets – it would be extremely time-consuming to code hundreds of documents by hand with a highlighter pen.

Ease of use

NVivo is relatively simple to use. Users can import documents directly from word processing packages in various forms, including Word documents and pdfs, and code these documents easily on screen via the point-and-click system. Teachers and students can quickly become proficient in use of this software.

NVivo and social media

NVivo allows users to import Tweets, Facebook posts, and Youtube comments and incorporate them as part of their data. Given the rise of social media and increased interest in studying its impact on our society, this capability of NVivo may become more heavily employed.

Segmenting and identifying patterns 

NVivo allows users to create clusters of nodes and organize their data into categories and themes, making it easy for researchers to identify patterns. At the same time, the use of word clouds and cluster analysis also provides insight into prevailing themes and topics across data sets.

Limitations

While NVivo seems to be a great software that serves to provide a reliable, general picture of the data, it is important to be aware of its limitations. It may be tempting to limit the data analysis process to automatic word searches that yield a list of nodes and themes. While it is alluring to do so, in-depth analyses and critical thinking skill are needed for meaningful data analysis.

Although it is possible to search for particular words and derivations of those words, various ways in which ideas are expressed make it difficult to find all instances of a particular usage of words or ideas. Manual searches and evaluation of automatic word searches help to ensure that the data are, in fact, thoroughly examined.

Once individual themes in a data set are found, NVivo doesn’t provides tools to map out how these themes relate to one another, making it difficult to visualize the inter-relationships of the nodes and topics across data sets. Users need to think critically about ways in which these themes emerge and relate to each other to gain a deeper understanding of the data.

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Data Across the Curriculum: Using Real Data in Classes

mapblacksoldiercotton    F7 Maya Andelson grub eater       Figure 5       SarahMappic1      homosexuality-gender

What does eating a grub have to do with interviewing children in Costa Rica?  What does studying Don Quixote or Shakespeare have to do with examining business transactions, consulting for an NGO or designing a visualization on terrorist incidents?

ANSWER:  They all describe ways that Grinnell students are engaging with real-world data.

Well-educated individuals should be able to create, evaluate, and analyze data, so that they can ultimately engage in the most well-informed decision-making.  They will then need to be able to effectively communicate patterns in the data to others, using statistics and/or visualization tools in addition to, of course, well-crafted words.

None of these analytic or communicative skills are easy to learn and acquiring expertise demands both theory and the opportunity for practice. In an age of ubiquitous data (much of it of dubious quality) and numerous computer-assisted visualization and analytic tools (all of which can be both used and misused) the pitfalls are many, although the rewards for are great.  Employers love the data-savvy, but data analysis is an important part of decision-making in daily life as well!

Grinnell College classes in disciplines ranging from Anthropology to Spanish, History to Biology, Psychology to English, and Political Science to Statistics are engaging with real data in a variety of ways.  Some classes include data collection as well as analysis and display; others are more focused on evaluating data, interpreting it and communicating the results.

DASIL’s mission is to assist faculty and students explore the world using data.  We are embarking on a series of profiles designed to highlight some of the innovative ways the Grinnell faculty incorporate data in their classes.

See future posts for more details about how grubs, high school students, Don Quixote , and even baboons, all fit into the picture.

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Investigating the Spatial & Temporal Trends of Declaring a Major

The start of the school year is a time many students start putting thought into what disciplines to study for the remainder of their collegiate careers. Many on-campus resources such as the Center for Careers, Life, and Service are already in the full swing of advising students, such as the “Choosing Your Major” info session on Sept 21st from noon to 1 in the Joe Rosenfield Center. Here in DASIL, we thought it would be fun to investigate what Grinnell College students majored in over the years to illustrate the transformation of student academic patterns. Using data from the Office of Academic Affairs, Office of the Registrar, and the Office of Analytic Support and Institutional Research, we created two interactive graphics. One is a line graph presenting the number of declared majors over time from 1991 to 2015 by major and rank compared to other majors. Our second visualization is a geographic map with two layers: the US layer breaks down the proportion of students by state and major from 1985 to 2015, while the world layer illustrates the proportion of international students by country and major.

Click on the Details button below to find out more about the data for each visualization.

For the map:

    • The Contents button(contentsbutton) will display all layers. Unclick the checkbox next to the layer name to hide the layer. To view the legend, click on the “Show Legend” icon (contentsbutton) below the layer name.
    • To examine other majors, find the “Change Style” button (contentsbutton) below the layer name you wish to view, then select the desired major from the “Choose an attribute to show” drop-down menu.  You may alter the map with colors, symbols or size.
    • Click on an individual country or US state to see available data on all majors.

For the line graph:

  • Choose your major(s) of interest in the “Select a major to display” field.
  • Hover over each point to display information on a major’s rank by class year and the number of students declared. Hover over a line to view the path of a major over time.


 

 

The Biology major holds the record for most students declared within this time frame, at 53 students for the Class of 1995. Since its creation, the number of students who major in Biological Chemistry increased leaps and bounds, ranking as the second most-declared major in the Class of 2015, tied with Psychology. Economics shows a general increasing trend over time, while majors like English and Sociology show erratic variability throughout.

American Studies majors appears to be representing the South and Southwest regions of the US, while Sociology is prominent in states located in the Midwest and, similarly, the South. A large proportion of students hailing from California study the hard sciences, especially Biological Chemistry. Surprisingly, there is a significant proportion of biology majors represented in most of the states.

Scoping out, the social sciences and hard sciences are popular disciplines among international students. Economics, Biological Chemistry, and Math are popular, especially in countries like China and India. Several humanities majors are not well-represented by international students, such as Theatre and Gender, Women, & Sexuality Studies.

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We the People Data Explorer

This site allows researchers to filter petitions from the White House’s We the People site by subject, keyword, and minimum and maximum number of signatures. Users can also download the total number of signatures by ZIP code for individual petitions, or a list of the timestamps (in Eastern time) and ZIP codes of every signature on an individual petition. Downloads are in CSV format.

Note that only petitions with 150 or more signatures are included in this dataset.

Data is current as of January 18, 2017.

Enter petition criteria:

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