By Greta Underhill

In my last post, I outlined my search for a computer-assisted qualitative data analysis software (CAQDAS) program that would fit our Research Unit’s needs. We needed a program that would enable our team to collaborate across operating systems, easily adding in new team members as needed, while providing a user-friendly experience without a high learning curve. We also needed something that would adhere to our institution’s IRB requirements for data security and preferred a program that didn’t require a subscription. However, the programs I examined were either subscription-based, too cumbersome, or did not meet our institution’s IRB requirements for data security. It seemed that there just wasn’t a program out there to suit our team’s needs.

However, after weeks of continued searching, I found a YouTube video entitled “Coding Text Using Microsoft Word” (Harold Peach, 2014). At first, I assumed this would show me how to use Word comments to highlight certain text in a transcript, which is a handy function, but what about collating those codes into a table or Excel file? What about tracking which member of the team codes certain text? I assumed this would be an explanation of manual coding using Word, which works fine for some projects, but not for our team.

Picture of a dummy transcript using Lorem Ipsum placeholder text. Sentences are highlighted in red or blue depending upon the user. Highlighted passages have an associated “comment” where users have written codes.

Fortunately, my assumption was wrong. Dr. Harold Peach, Associate Professor of Education at Georgetown College, had developed a Word Macro to identify and pull all comments from the word document into a table (Peach, n.d.). A macro is “a series of commands and instructions that you group together as a single command to accomplish a task automatically” (Create or Run a Macro – Microsoft Support, n.d.). Once downloaded, the “Extract Comments to New Document” macro opens a template and produces a table of the coded information as shown in the image below. The macro identifies the following properties:

  • Page: the page on which the text can be found
  • Comment scope: the text that was coded
  • Comment text: the text contained in the comment; for the purpose of our projects, the code title
  • Author: which member of the team coded the information
  • Date: the date on which the text was coded

Picture of a table of dummy text that was generated from the “Extract Comments to New Document” Macro. The table features the following columns: Page, Comment Scope, Comment Text, Author, and Date.

You can move the data from the Word table into an Excel sheet where you can sort codes for patterns or frequencies, a function that our team was looking for in a program as shown below:

A picture of the dummy text table in an Excel sheet where codes have been sorted and grouped together by code name to establish frequencies.

This Word Macro was a good fit for our team for many reasons. First, our members could create comments on a Word document, regardless of their operating system. Second, we could continue to house our data on our institution’s servers, ensuring our projects meet strict IRB data security measures. Third, the Word macro allowed for basic coding features (coding multiple passages multiple times, highlighting coded text, etc.) and had a very low learning curve: teaching someone how to use Word Comments. Lastly, our institution provides access to the complete Microsoft Suite so all team members including students that would be working on projects already had access to the Word program. We contacted our IT department to have them verify that the macro was safe and for help downloading the macro.

Testing the Word Macro       

Once installed, I tested out the macro with our undergraduate research assistant on a qualitative project and found it to be intuitive and helpful. We coded independently and met multiple times to discuss our work. Eventually we ran the macro, pulled all comments from our data, and moved the macro tables into Excel where we manually merged our work. Through this process, we found some potential drawbacks that could impact certain teams.

First, researchers can view all previous comments made which might impact how teammates code or how second-cycle coding is performed; other programs let you hide previous codes so researcher can come at the text fresh.

Second, coding across paragraphs can create issues with the resulting table; cells merge in ways that make it difficult to sort and filter if moved to Excel, but a quick cleaning of the data took care of this issue.

Lastly, we manually merged our work, negotiating codes and content, as our codes were inductively generated; researchers working on deductive projects may bypass this negotiation and find the process of merging much faster.

Despite these potential drawbacks, we found this macro sufficient for our project as it was free to use, easy to learn, and a helpful way to organize our data. The following table summarizes the pro and cons of this macro.

Pros and Cons of the “Extract Comments to New Document” Word Macro

Pros

  • Easy to learn and use: simply providing comments in a Word document and running the macro
  • Program tracks team member codes which can be helpful in discussions of analysis
  • Team members can code separately by generating separate Word documents, then merge the documents to consensus code
  • Copying Word table to Excel provides a more nuanced look at the data
  • Program works across operating systems
  • Members can house their data in existing structures, not on cloud infrastructures
  • Macro is free to download

Cons

  • Previous comments are visible through the coding process which might impact other members’ coding or second round coding
  • Coding across paragraph breaks creates cell breaks in the resulting table that can make it hard to sort
  • Team members must manually merge their codes and negotiate code labels, overlapping data, etc.

Scientific work can be enhanced and advanced by the right tools; however, it can be difficult to distinguish which computer-assisted qualitative data analysis software program is right for a team or a project. Any of the programs mentioned in this paper would be good options for individuals who do not need to collaborate or for those who are working with publicly available data that require different data security protocols. However, the Word macro highlighted here is a great option for many research teams. In all, although there are many powerful computer-assisted qualitative data analysis software programs out there, our team found the simplest option was the best option for our projects and our needs.

References 

Create or run a macro—Microsoft Support. (n.d.). Retrieved July 17, 2023, from https://support.microsoft.com/en-us/office/create-or-run-a-macro-c6b99036-905c-49a6-818a-dfb98b7c3c9c

Harold Peach (Director). (2014, June 30). Coding text using Microsoft Word. https://www.youtube.com/watch?v=TbjfpEe4j5Y

Peach, H. (n.d.). Extract comments to new document – Word macros and tips – Work smarter and save time in Word. Retrieved July 17, 2023, from https://www.thedoctools.com/word-macros-tips/word-macros/extract-comments-to-new-document/

by Greta Underhill

Are you interested in qualitative research? Are you currently working on a qualitative project? Some researchers find it helpful to use a computer-assisted qualitative data analysis software (CAQDAS) program to help them organize their data through the analysis process. Although some programs can perform basic categorization for researchers, most software programs simply help researchers to stay organized while they conduct the deep analysis needed to produce scientific work. You may find a good CAQDAS program especially helpful when multiple researchers work with the same data set at different times and in different ways. Choosing the right CAQDAS for your project or team can take some time and research but is well worth the investment. You may need to consider multiple factors before determining a software program such as cost, operating system requirements, data security, and more.

For the Ecampus Research Unit, issues with our existing CAQDAS prompted our team to search for another program that would fit our specific needs: Here’s what we were looking for:

NeedsReasoning
General qualitative analysisWe needed a program for general analysis for multiple types of projects; Other programs are designed for specific forms of analysis such as Leximancer for content analysis
Compatibility across computer operating systems (OS)Our team used both Macs and PCs
Adherence to our institution’s IRB security requirementsLike many others, our institution and our team adhere to strict data security and privacy requirements, necessitating a close look at how a program would manage our data
Basic coding capabilitiesAlthough many programs offer robust coding capabilities, our team needed basic options such as coding one passage multiple times and visually representing coding through highlights
Export of codes into tables or Excel booksThis function is helpful for advanced analysis and reporting themes in multiple file formats for various audiences
A low learning-curveWe regularly bring in temporary team members on various projects for mentorship and research experience, making this a helpful function
A one-time purchaseA one-time purchase was the best fit for managing multiple and temporary team members on various projects

Testing a CAQDAS

I began systematically researching different CAQDAS options for the team. I searched “computer-assisted qualitative data analysis software” and “qualitative data analysis” in Google and Google Scholar. I also consulted various qualitative research textbooks and articles, as well as blogs, personal websites, and social media handles of qualitative researchers to identify software programs. Over the course of several months, I generated a list of programs to examine and test. Several programs were immediately removed from consideration as they are designed for different types of analysis: DiscoverText, Leximancer, MAXQDA, QDA Miner. These programs are powerful, but best suited for specific analysis, such as text mining. With the remaining programs, I signed up for software trials, attended several product demonstrations, participated in training sessions, borrowed training manuals from the library, studied how-to videos online, and contacted other scholars to gather information about the programs. Additionally, I tested whether programs would work across different operating systems. I kept recorded details about each of the programs tested, including how they handled data, the learning curve for each, their data security, whether they worked across operating system, how they would manage the export of codes, and whether they required a one-time or subscription-based payment. I started with three of the most popular programs, NVivo, Dedoose, and ATLAS.ti. The table below summarizes which of these programs fit our criteria.

NVivoDedooseATLAS.ti
General Qualitative Analysis
Cross-OS Collaboration
Data security
Basic coding capabilities
Export codes
Low learning curve
One-time purchase
A table demonstrating whether three programs (NVivo, Dedoose, and ATLAS.ti) meet the team’s requirements. Details of requirements will be discussed in the text of the blog below.

NVivo

I began by evaluating NVivo, a program I had used previously. NVivo is a powerful program that adeptly handled large projects and is relatively easy to learn. The individual license was available for one-time purchase and allowed the user to maintain their data on their own machine or institutional servers. However, it had no capabilities for cross-OS collaboration, even when clients purchased a cloud-based subscription. Our team members could download and begin using the program, but we would not be able to collaborate across operating systems.

Dedoose

I had no prior experience with Dedoose, so I signed up for a trial of the software. I was impressed with the product demonstration, which significantly helped in figuring out how to use the program. This program excelled at data visualization and allowed a research team to blind code the same files for interrater reliability if that suited the project. Additionally, I appreciated the options to view code density (how much of the text was coded) as well as what codes were present across transcripts. I was hopeful this cloud-based program would solve our cross-OS collaboration problem, but it did not pass the test for our institution’s IRB data security requirements because it housed our data on Dedoose servers.

ATLAS.ti

ATLAS.ti was also a new program for me, so I signed up for a trial of this software. It is a well-established program with powerful analysis functions such as helpful hierarchical coding capabilities and institutive links among codes, quotations, and comments. But the cross-OS collaboration, while possible via the web, proved to be cumbersome and this too did not meet the data security threshold for our institution’s IRB. Furthermore, the price point meant we would need to rethink our potential collaborations with other organizational members.

Data Security

Many programs are now cloud-based, which offer powerful analysis options, but unfortunately did not meet our IRB data security requirements. Ultimately, we had to cut Delve, MAXQDA, Taguette, Transana, and webQDA. All of these programs would have been low-learning curve options with basic coding functionality and cross-OS collaboration; however, for our team to collaborate, we would need to purchase a cloud-based subscription, which can quickly become prohibitively expensive, and house our data on company servers, which would not pass our institutional threshold for data security.

Note-taking programs

After testing multiple programs, I started looking beyond just qualitative software programs and into note-taking programs such as DevonThink, Obsidian, Roam Research, and Scrintal. I had hoped these might provide a work around by organizing data on collaborative teams in ways that would facilitate analysis. However, most of them did not have functionalities that could be used for coding or had high learning curves that precluded our team using them.

It seemed like I had exhausted all options and I still did not have a program to bring back to the Research Unit. I had no idea that a low-cost option was just a YouTube video away. Stay tuned for the follow-up post where we dive into the solution that worked best for our team.

 

By Cat Turk and Mary Ellen Dello Stritto

In this time of rapid change in online education, we can benefit from leveraging the expertise of faculty who have experienced the evolution of online education. At the Oregon State University (OSU) Ecampus Research Unit, we have been learning from a group of instructors who have taught online for ten years or more. A review of recent research uncovered that these instructors are an untapped resource. Their insights can provide valuable guidance for instructors who are just beginning their careers or instructors who may be preparing to teach online for the first time. Further, their perspectives can also be enlightening for online students.

In 2018-2019 we conducted interviews with 33 OSU faculty who had been teaching online for 10 years or more as a part of a larger study. Two of the questions we asked them were the following:

  1. What skills do you think are most valuable for online instructors to have?
  2. What skills do you think are most valuable for online students to have?

We will share some of the results of a qualitative analysis of these questions and highlight the similarities and differences.

When asked about the most valuable skills for online instructors, three key skills emerged: communication, organization, and time management. When asked about the most valuable skills for online students to have, the same skills were among the most frequently mentioned by these instructors.

As the table below shows, in the responses about skills for online instructors, communication emerged as the most prominent skill, with 85% of instructors in the study emphasizing its importance, while time management and organization were split evenly at 45%. In their response about skills for students, 64% of the instructors emphasized both communication and time management, while 42% discussed organization. When discussing communication for instructors, they indicated that effective communication is essential for building rapport with students, providing clear instructions, and facilitating meaningful interactions in the online environment. Organization (such as structuring course materials or their weekly work process) and time management skills (such as scheduling availability to connect with students) were also highly valued by these instructors. Read more about the analysis of instructor skills here.

 Skills for InstructorsSkills for Students
Communication    28 responses (85%)   21 responses (64%)
Time Management15 responses (45%)  21 responses (64%)
Organization15 responses (45%)   14 responses (42%)
Self-Motivation   —21 responses (64%)            
Frequency of responses of skills for instructors and students.

The responses to both questions emphasized the significance of communication skills in written assignments and in proactive connections within the scope of the online learning environment. Instructors articulated that online students needed to be proactive communicators themselves. Examples of this include contacting their instructors about questions and clarification in a timely way, interacting with their peers in a respectful manner, and turning in quality written assignments that demonstrate comprehension of their learning material. For students, clear and effective communication ensures understanding and engagement, while organization facilitates seamless navigation through course materials, and time management ensures that students are able to make the most of the asynchronous environment.

While time management and organization were both considered by instructors to be just as crucial for students, their responses demonstrated that these skills were needed for different reasons than would be the case for instructors. Instructors personally valued time management and organization due to the nature of facilitating courses online. When the online classroom can travel from place to place, setting blocks of intentional time and structuring hours accordingly were considered essential to instructors for maintaining a work-life balance and so tasks would not be missed.

On the other hand, according to these instructors, students need time management and organization due to the asynchronous and sometimes isolating nature of online courses. One instructor stressed that:

 “[Students] do need to be more organized than on-ground students, because there’s not that weekly meeting to keep students on track.”

These instructors indicated some online students may need to structure their study time to accommodate a different time zone, while others may need to structure their academic pursuits around careers or children. Another instructor emphasized that:

“A lot of our [online students] actually work full-time, so they have families and kids and have to be much more organized too.”

While there were overlaps with the responses to the two questions, a notable difference was the emergence of another skill for students: self-motivation. This concept of self-motivation emerged from the instructor responses about students’ capacity to persevere in online courses. This included their level of motivation, capacity to learn on their own, and comfort with self-paced learning.

One instructor said the following about students’ self-motivation,

“Some people would say it’s self-discipline, but I think it’s more of they have to have a purpose for that class.”

Self-motivation was not mentioned by the instructors as a skill for online instructors, suggesting that these instructors perceive this as more pertinent to students for success in managing their own learning process. It is worth noting that proactive communication was highlighted as an essential aspect of self-motivation, with instructors emphasizing that students who take the initiative in reaching out to them tend to be more successful. This observation suggests that self-motivated individuals are more likely to actively seek support and clarification, which can enhance their learning experience and overall success. 

Another noteworthy aspect was the need for students to be comfortable with learning in physical isolation. Instructors acknowledged that online learners must navigate the challenges of studying independently without the immediate presence of peers and instructors. For online students specifically,

“They need to be motivated because they’re not going to have peers sitting in a classroom with them, and they don’t have a place that they have to physically go every week.”

This finding underscores the importance of maintaining motivation and engagement, as students ideally possess an intrinsic drive to succeed despite the absence of a physical connection to the university and their classmates.

The findings from this study highlight the importance of certain similar skills for both online instructors and students. Effective communication, organization, and time management are vital for success in the online learning environment for both instructors and students. We found this to be an interesting connection that online students might benefit from understanding: these are key skills that students and instructors have in common.

Our findings about self-motivation may be useful for online instructors. Consider incorporating strategies that foster student self-motivation, such as goal-setting exercises, regular check-ins, and providing opportunities for self-reflection. By empowering students to take ownership of their learning, instructors might enhance student engagement and success in the online environment.

Further, students can learn from the instructors’ emphasis on communication, organization, and time management skills. They can intentionally work on improving their communication skills, seeking clarification when needed, and actively participating in online discussions. Developing effective organization and time management strategies, such as creating schedules, prioritizing tasks, and breaking them down into manageable chunks, may significantly enhance their online learning experience.

The field of online education is evolving rapidly, and here we can see how educators and students alike are adapting to these changes. The experiences of long-term online instructors provide valuable insights into the skills necessary for success in the online learning environment. In the future, what answers would we find if we asked students the same question: what do online students think are the skills needed to succeed in the online classroom? By understanding the shared and distinct perspectives of instructors and students, educators can design effective online courses and support systems that foster meaningful learning experiences and empower students to succeed.

The changes in higher education precipitated by the COVID-19 pandemic have reignited questions and misconceptions about online education.  This is a time that we should draw on the insights and experience of online faculty. At Oregon State University (OSU) we have a significant number of faculty who have been teaching online for over a decade. In the 2018-2019 academic year, the Ecampus Research Unit interviewed 33 OSU instructors who had taught online for 10 years or more. In a series of interviews, the instructors were asked to reflect on their experiences as an online educator and how their perspectives have changed over time. More information about the broader study can be found on the study website. The final question asked of the instructors was, “What do you think is the future of online learning?” We conducted a qualitative analysis of their responses to this question. The findings were recently published in the Online Journal of Distance Learning Administration. Below, we discuss some of the key findings from this analysis.

Key finding #1: Online and blended learning will continue to grow

Two-thirds (22) of the instructors expected online learning to expand as higher education moves toward increased access and accessibility, and as employers show increased expectations of continuing education. They acknowledged that online learning would continue to be the choice of adult learners as they balance work and life responsibilities.

Key finding #2: Online learning will increase access and accessibility

More than half (18) of the instructors predicted that online learning would increase access to education. These instructors discussed how online learning increases accessibility because online courses can be taken anywhere (location flexibility) and online courses can be accessed anytime (time flexibility). While these instructors were interviewed before the COVID-19 pandemic, their responses are now particularly timely and relevant, as the pandemic shifted higher education’s focus to remote and online teaching.  

Key finding #3: Will online learning replace brick and mortar institutions?

One third (11) of the instructors discussed the possibility that online learning may grow to become the primary modality used in higher education, replacing face-to-face learning.  However, 13 instructors indicated that they did not think the face-to-face learning should be eliminated in the future. Many of these instructors hoped that online education could provide more options for students rather than replacing brick and mortar institutions.

Key finding #4: Technology development will increase

Nearly 40% of the instructors (13) discussed the role of technology development in the future of online education. Acknowledging that the development of technology has already made teaching online easier and more effective, many optimistically predicted this would continue to improve the teaching and learning experience. Others were more pessimistic about technology replacing elements like face-to-face communication.

Overall, instructors’ ideas of the future aligned with some themes in the broader field of higher education, such as diversity, opportunity, and access. These key findings have implications for the professional development of online instructors. As more faculty transition to online teaching, it is important that they be well prepared for the online learning landscape. As the population of students in online education continues to evolve, it is also important that instructors understand the diversity of their students and the needs of adult learners. As technology is rapidly changing, timely and accessible training that can be used across multiple modalities is needed for future faculty development. Enhancing instructors’ pedagogy and technology skills across a range of modalities will enhance the educational experience for online learners around the globe.