Constructing Hopes and Fears Around Technology

Abstract

Graduate students often receive their first training in qualitative methods during an introductory course. The textbook that is chosen often sets the tone for how qualitative research is understood. We conducted a discourse analysis of the ways in which 11 introductory qualitative methods texts took up the relationship between technology and qualitative research. One text included virtually no mention of technology use; five discussed technology only in relation to the data collection, transcription, and analysis domains of research; and the remaining five discussed technology primarily in relation to those three domains with minimal attention to how it could support the additional domains of researcher reflexivity, literature review, representation of findings, ethics, and collaboration. We contrasted texts that took up a discourse of possibility with those that took up a discourse of caution around technology use. We call for greater dialogue around how emergent technologies might inform the qualitative research process.

Keywords

discourse analysis textbooks technology CAQDAS software reflexivity ethics collaboration teaching qualitative research

Introduction

Technology impacts our everyday lives in numerous ways. For many, they have also impacted our research lives. The information explosion, proliferation of computing devices, and emphasis on interdisciplinary, collaborative research all suggest, and perhaps require, new ways of conceptualizing the qualitative research process. Students today enter graduate school with ever more sophisticated experiences with technology. They understandably expect faculty to have some understanding of the affordances and constraints of technology as it is relevant to their research work.

While the earliest debates on the relationship between technology and qualitative research focused on data analysis software (Davidson & di Gregorio, 2011), less attention has been given to the ways in which technology tools can be used to support other aspects of the research process. While researchers may have good reasons for choosing whether or not to use technology in their studies, the growth of Internet and communications technologies in particular make it increasingly difficult to ignore their implications for research into social life. Furthermore, it is crucial for methods instructors to consider the ways in which new technologies can be used to support the entire research process.

Graduate students often receive their first training in qualitative methods during an introductory course. The textbook that is chosen can set the tone for their entry into the field, making relevant how technology may or may not support the research process. Within this article, we present findings from a discourse analysis of the ways in which introductory qualitative methods texts have framed the relationship between technology and qualitative research. The overarching question that guided our study was: How is technology use taken up in introductory qualitative methods texts?

Review of the Literature

Qualitative researchers have long had an uneasy relationship with new technologies. As Seale (2010) has described it, “concerns about the computer imposing a particular analytic logic, alien to the spirit of qualitative research, can be fuelled by the slight paranoia about technology still felt by qualitative researchers” (p. 259). The little attention that has been given to technology has tended to focus on the use of qualitative data analysis software (QDAS). Davidson and di Gregorio (2011) pointed out that the early writing “had the unfortunate consequence of reinforcing the procedural, scientific image of these programs” that “pushed away many experienced qualitative analysts” (p. 632). They noted that QDAS developed as a relatively isolated subfield of qualitative research, one that many researchers still do not fully understand.

Furthermore, researchers retain some “paranoia” around the use of technology, particularly to analyze data. For example, Roberts and Wilson (2002) argued that technology and qualitative data analysis are philosophically incompatible, and that data analysis software is not “sympathetic to the types of qualitative data we are discussing” (p. 13). They emphasized that “computers do not and cannot analyze qualitative data” (p. 6), that computers put distance between the researcher and her data, and that researchers should be wary of the ease with which analysis could become “mechanistic and prescriptive” (p. 11). Taylor, Lewins, and Gibbs’s (2005) described the distance that software puts between the researcher and the data, the potential for superficial analysis, and the allure of easy quantification as typical concerns about the use of QDAS.

In the four editions of Denzin and Lincoln’s The SAGE Handbook of Qualitative Research (1998, 2000, 2005, 2011), only one to two chapters per edition have addressed technology at all (Davidson & di Gregorio, 2011; Gatson, 2011; Markham, 2005; Richards & Richards, 1998; Weitzman, 2000). From the first published chapter (Richards & Richards, 1998) to the most recent chapters (Davidson & di Gregorio, 2011; Gatson, 2011), the conversation around technology began with a focus on QDAS to a recent shift toward the Internet as a source of data (see Table 1). Richards and Richards focused on how data analysis could be supported by software programs, while also highlighting the constraints. They warned of the “real dangers of software constraining and distorting research” (p. 212) and emphasized how technology might inappropriately shape the analysis process, giving minimal attention to how technology might be used for other domains of the research process.

Table 1.

Denzin and Lincoln, The SAGE Handbook of Qualitative Research Chapters That Address Technology.

Edition	Title	Year	Authors	Areas of Focus
First edition	Using computers in qualitative research	1998	Richards & Richards	• How software programs can be used to support data analysis
First edition	Using computers in qualitative research	1998	Richards & Richards	• Constraints of software programs
Second edition	Software and qualitative research	2000	Weitzman	• Major debates and critical concerns around QDAS.
				• Computer use for data analysis, as well as transcribing, recording field notes and sharing findings
				• “Hopes and fears” of software use
Third edition	The methods, politics, and ethics of representation in online ethnography	2005	Markham	• The Internet as a data source, as it is a pervading aspect of human life
Fourth edition	The methods, politics, and ethics of representation in online ethnography	2011	Gatson	• Boundaries between participants and researchers are not as firm online as in other research environments
Fourth edition	Qualitative research and technology: In the midst of a revolution	2011	Davidson and di Gregorio	• Historical overview of the use of technology in qualitative research
				• How technological advancements have shaped qualitative data analysis
				• The Internet as a data source
				• Reasons for qualitative research community’s reluctance to use technology

Weitzman’s (2000) chapter discussed the major debates and critical concerns around using QDAS and provided guidance for selecting the appropriate program. Like Richards and Richards (1998), Weitzman emphasized the place of technology in the data analysis process, with less attention given to other aspects of the research process (e.g., data management). However, he also presented a list of “things computers can be used for” (p. 805) in the analysis process, including transcribing, recording field notes, and sharing findings. He acknowledged the common fear that the “conceptual assumptions behind the program will shape the analysis” (p. 808), arguing that being aware of these assumptions can help the researcher work around them. Weitzman further highlighted the “false hopes and fears” surrounding technology, including the excitement and/or fear that the software will do the analysis or build a theory for the researcher. Alongside this discussion, he presented the “real hopes” for the use of technology in qualitative research, including the potential for added consistency, speed, representation, and consolidation of data.

The third edition of the handbook replaced the chapter on “using computers” with Markham’s (2005) chapter on the Internet as a source of data. This chapter marked a shift from a primary concern with QDAS, to an acknowledgment of how the Internet is pervading all aspects of human life and, thus, arenas for qualitative research. She proposed that studying the Internet as a site of social life would require “adjustment of traditional methods to online environments or the creation of new methods” (p. 795). This chapter was further updated in the fourth and most recent edition of the handbook by Gatson (2011). Gatson covered similar territory but from a different stance, arguing that many of us have “inherent membership” in online field sites and that the boundaries between participants and researchers are “especially permeable” (p. 521).

Davidson and di Gregorio’s (2011) chapter provided a historical overview of the use of technology aligned with Denzin and Lincoln’s (2003, 2008) “critical moments . . . in qualitative research” (p. 629). They focused on the ways in which technological advancements have shaped qualitative data analysis, also mentioning the Internet as a data source. Davidson and di Gregorio (2011) suggested that the reluctance of the field to embrace technology may come from not being aware of and/or not having access to the technologies, lingering beliefs that qualitative research is not epistemologically compatible with software (e.g., Roberts & Wilson, 2002), or a simple fear of technology. They further pointed out that some qualitative researchers would like to use the software, but encounter barriers such as the lack of institutional support, access, and/or training. Davidson and di Gregorio noted that “most senior researchers in the field of qualitative research, and many rising researchers, still lack exposure to QDAS use in their graduate training” (p. 635).

With senior scholars positioned as not typically embracing new technologies, we were curious about how those writing introductory methods books might be positioning technology for their readers. The impetus for this study grew out of our professional practices. Two of us are faculty members in graduate programs in which we teach and mentor students in qualitative research methods, the third is currently a doctoral student working on a qualitative dissertation. As individuals involved in delivering and receiving methods instruction, we were drawn to examine the ways in which technology was being taken up in introductory texts. We believe it is important for methods instructors to be familiar with how textbooks frame the use of technology tools, as this framing functions to construct a certain orientation to the affordances and limitations that technology tools bring to the qualitative research process.

Method

We were informed by a theory of discourse that presumes that language is constructive, rather than representative of a reality (Edwards, 1997). We presumed that the metaphors evoked and discourses used around technology were always doing something, for example, setting the tone for how novice qualitative researchers begin to make sense of the relationship between research and technology. We conducted a discourse analysis (Wood & Kroger, 2000) of how technology was made relevant, or not, in 11 introductory qualitative research textbooks (Berg & Lune, 2011; Bogdan & Biklen, 2007; Creswell, 2007; Flick, 2009; Glesne, 2011; Hatch, 2002; Marshall & Rossman, 2011; Maxwell, 2005; Merriam, 2009; Patton, 2002; Silverman, 2010). See Table 2.

Table 2.

Introductory Qualitative Research Textbooks.

Title	Author	Date	Edition
Qualitative research methods for the social sciences	Berg and Lune	2011	8th
Qualitative research for education: An introduction	Bogdan and Biklen	2007	5th
Qualitative inquiry and research design	Creswell	2007	2nd
An introduction to qualitative research	Flick	2009	4th
Becoming qualitative researchers: An introduction	Glesne	2011	4th
Doing qualitative research in educational settings	Hatch	2002	1st
Designing qualitative research	Marshall & Rossman	2011	5th
Qualitative research design: An interactive approach	Maxwell	2005	2nd
Qualitative research: A guide to design and implementation	Merriam	2009	1st
Qualitative research and evaluation methods	Patton	2002	3rd
Doing qualitative research: A practical handbook	Silverman	2010	3rd

Our analysis centered around the following points of inquiry: (a) which technologies were discussed in the texts, (b) how the discussed technologies were positioned as relevant to the domains of the research process, and (c) what discourses around technology were taken up. We considered the extent to which technology use was positioned, for example, as an integral or supplemental aspect of the research process, and whether a discourse of opportunity, a discourse of caution, or some other discourse was taken up when discussing various technologies. For each textbook, we engaged in an emergent, iterative analysis process. Initially, we searched qualitative methods journals, listservs, and forums for articles and discussions that could help us identify the “key” introductory level textbooks. We found no writing around this topic. Thus, we selected texts that were commonly cited in articles about the teaching of methods courses. Furthermore, when presenting initial findings at professional conferences, proposal reviewers and audience members suggested additional texts that we incorporated into our analysis. Our data sources began with 5 and grew to include 11 textbooks.

After selecting the texts, we first scanned the tables of contents and indices for the keywords: technology, computers/computer-assisted, online, Internet, email, software, tape recorders, video recorders, and related terms. We also scanned for mention of the following domains of the research process to specifically see whether technology use was mentioned: reflexivity, literature review, data collection, data analysis, transcription, representation of findings, ethics, and teamwork or collaboration.

After isolating those sections of each text that discussed technology use, as well as scanning the entire texts for any mention of technology that may have been missed in our initial scans, we engaged in repeated readings, making analytical and theoretical memos throughout. We collaboratively moved to select and organize our findings around broad patterns across the texts. More particularly, we made note of which aspects of the research process were positioned as being supportable by technology. Then, we documented the types of technology mentioned and noted which aspects of the research process were discussed in relation to those technologies. Included within our analysis was how the authors positioned technology use, as we attended to whether they took up, for example, a discourse of possibility and excitement or one of caution and skepticism, of necessity and urgency, or of supplementary and optional. For each reviewed text, we created a summary case analysis representing how, where, and whether the author wrote about technology use. We gave particular attention to variability across the discourse, exploring how different authors might discuss the same idea in divergent ways (Antaki, Billig, Edwards, & Potter, 2003). Finally, we sought to represent our findings in a transparent and reflexive way, recognizing that what we share is a positional and partial description.

Findings

We focus our discussion around two interrelated areas: (a) what technologies were discussed in relation to the specific domains of research and (b) how technology use was made relevant and taken up by the authors. Dispersed throughout our discussion, particularly in the first section of the findings, we introduce some of the new technologies that might be used when engaging in the research process. We do this to contrast that which was made relevant by the authors with the possibilities for technology use in qualitative research.

Relevance of Technology to the Domains of the Research Process

Attention given by the authors to the use of technology varied in terms of the degree to which technology use was discussed. Maxwell’s (2005) text sat at one end of the spectrum with virtually no mention of technology use. Five texts discussed technology only in relation to data collection, transcription, and data analysis (Bogdan & Biklen, 2007; Creswell, 2007; Hatch, 2002; Marshall & Rossman, 2011; Patton, 2002). The remaining five texts discussed technology mainly in conjunction with data collection, transcription, and data analysis, but also with some mention of technology in other domains (Berg & Lune, 2011; Flick, 2009; Glesne, 2011; Merriam, 2009; Silverman, 2010). We next describe this variation in relation to each domain of the research process.

Reflexivity

Understanding the relationship between the researcher, context, and participants is important to most if not all qualitative traditions (Watt, 2007). New technologies such as blogs afford orienting to reflexivity as a dialogic and collaborative rather than solitary process (LaBanca, 2011), enabling researchers the opportunity to share their reflections with mentors, collaborators, and participants. Cloud-based note-taking and archiving systems such as Evernote afford multimodal and nonlinear reflective writing and access to research journals from multiple locations. Constraints in the use of such tools include the speed of change of these technologies and the ethical question of how secure it is to store information or write about aspects of research “in the cloud” (i.e., on servers not directly managed by the researcher). These new technologies test traditional research conventions, changing how qualitative researchers engage with the research process and work through ethical dilemmas. For instance, the Internet has blurred the distinction between private and publication information, with many ethics boards defining the Internet as a public text. Markham (2006) noted that there are no clear-cut answers, particularly as new technologies bring with them novel features and ways of interacting with and defining data, participants, and the research process itself.

Only two of the texts (Flick, 2009; Hatch, 2002) came close to discussing how technology might support reflexivity. Hatch, in his brief discussion of research journals, mentioned that, “entries need not be typed or edited, although high-tech journaling at a desktop will likely be the preferred form for most readers of this book” (p. 88). He then continued, though, by describing a paper-based journaling system that he himself uses. Flick used numerous examples from his own research on the social representation of technology to illustrate certain aspects of the research process. Though he never directly wrote about researcher reflexivity in relation to technology use, his multiple examples hinted at the possibilities. Reflexivity, then, while positioned in the textbooks as an integral aspect of qualitative inquiry, was not explicitly linked to technology.

Reviewing the literature

Identifying relevant literature and managing its sheer quantity can be supported by a variety of tools beyond the databases most scholars are familiar with. In addition to citation managers such as Endnote and Zotero, newer tools such as Mendeley take a social networking approach to connecting researchers with the larger research community. QDAS packages such as ATLAS.ti, MAXQDA, and NVivo can be used not only for analyzing data but also for analyzing the literature (Bringer, Johnston & Brackenridge, 2004; di Gregorio, 2000; Johnston, 2006).

Three of the texts we reviewed (Berg & Lune, 2011; Flick, 2009; Silverman, 2010) explicitly made note of how technology can impact the literature review process. Flick and Silverman discussed online library searches and databases such as the Social Sciences Citation Index. Berg and Lune presented the most thorough description of how the Internet has changed the process of conducting a literature review, highlighting the ways in which Google Books and Google Scholar can be used. Berg and Lune cautioned, however, that these tools must be understood in relation to what they can provide and what they fail to offer. They also compared Internet search engines with academic search tools, suggesting that they are not analogous. The Internet, for example, can provide access to a multitude of popular articles; however, the academic databases are more likely to identify reliable sources. These three texts, then, did orient to the literature review process, even if minimally, in relation to technological tools.

Data collection

There are a variety of tools that can support the data collection process, as well as extend the context for data collection. Mobile devices and new software tools (e.g., Audacity) provide opportunities for researchers to expand how they record, edit, and store audio and video data. Online communities and their persistent conversations make the Internet a vast source of data, appealing to ethnographers in particular. Tools such as the Blog Analysis Toolkit and Mozenda are radically changing how this data can be collected and analyzed, as well as seriously complicating the ethical decision points around what constitutes public versus private spaces (Estalella & Ardèvol, 2007; Markham, 2012).

We found that all textbooks addressed technology as it pertained to data collection, with many discussing strategies and tools for effectively recording interviews (Creswell, 2007; Hatch, 2002; Patton, 2002; Silverman, 2010). Several authors discussed online focus groups (Berg & Lune, 2011; Creswell, 2007; Patton, 2002). Berg and Lune, for example, discussed the potential use of email, listservs, online discussion boards, and mailing lists as ways to generate asynchronous focus group data. Merriam (2009) provided an overview of various types of computer-mediated communication that can allow people to interact for research purposes. Berg and Lune took the discussion a step further by addressing how computer-assisted interviewing provides the researcher with an opportunity to type the data as it is being spoken.

In terms of the Internet as a context for collecting data, several authors discussed various digital archives (Berg & Lune, 2011; Creswell, 2007), virtual ethnography methods (Berg & Lune, 2011; Creswell, 2007; Patton, 2002), and other ways of mining Internet data such as blogs (Berg & Lune, 2011; Merriam, 2009; Silverman, 2010). Merriam (2009), Flick (2009), and Glesne (2011) also included discussions of visual documents, describing the strengths and weaknesses of the various data sources.

Transcribing

Transcribing of audio and video data has been a mainstay of the qualitative research process, though not without its own controversies (Hammersley, 2010a; Lapadat & Lindsey, 1999). New transcription tools (e.g., Inqscribe) and QDAS programs afford synchronization of audio and video files with the transcript, calling into the question the practice of considering transcripts rather than the media file to be the focus of analysis. The necessity of transcribing at all has come into question with the affordances of QDAS and other programs (e.g., ELAN) that enable direct coding of media files (Evers, 2011). Voice recognition software (Johnson, 2011) and online data sources challenge our traditional notions of transcribing, including a potential loss of this initial layer of analysis.

These topics were not extensively taken up in the textbooks we reviewed. Technology topics around transcription primarily emphasized the importance of selecting reliable equipment (Bogdan & Biklen, 2007; Merriam, 2009; Patton, 2002), ensuring high-quality recordings (Glesne, 2011; Patton, 2002; Silverman, 2010), evaluating microphones (Bogdan & Biklen, 2007; Patton, 2002), and understanding the time required for transcribing (Merriam, 2009; Patton, 2002). Some, but not much, attention across the texts was given to the use of voice-activated equipment (Bogdan & Biklen, 2007; Glesne, 2011) and the potential use of digital, nonspecialized devices such as MP3 players and iPods for data collection (Bogdan & Biklen, 2007; Glesne, 2011).

Data analysis and management

QDAS has received the most attention from the qualitative research community, with the Computer-Assisted Qualitative Data Analysis Software (CAQDAS) project at the University of Surrey being at the forefront of work in this area. Analysis of field notes, transcripts, and other documents can look much different with the use of QDAS packages (Konopasek, 2008). For example, these packages support the storage and analysis of large data sets, data visualization and systematic approaches to analysis that would be impossible by hand. They also afford new ways of making sense of the data as well as collaborating with others. That the features of the software will no doubt impact how we shape our analysis is something to be considered carefully by the researcher.

Nearly all texts listed various software programs and their various functions, along with suggestions on how to choose the best program (Creswell, 2007; Flick, 2009; Glesne, 2011; Merriam, 2009; Patton, 2002; Silverman, 2010). Berg and Lune (2011), along with others, distinguished between various categories of QDAS such as code-and-retrieve programs and conceptual network builders. Authors noted advantages of QDAS including speed and efficiency (Bogdan & Biklen, 2007; Flick, 2009; Hatch, 2002; Patton, 2002; Silverman, 2010), particularly with large data sets (Creswell, 2007; Hatch, 2002; Merriam, 2009), increased rigor of analysis (Creswell, 2007; Flick, 2009; Hatch, 2002; Silverman, 2010), support for team research (Merriam, 2009), provision of graphic displays and visualization features to show relationships between data (Creswell, 2007; Flick, 2009; Hatch, 2002; Merriam, 2009), and the opportunity to consider data from multiple frames (Bogdan & Biklen, 2007).

Authors also claimed a variety of “limitations” of QDAS, including a narrow, inappropriate, or a priori approach to analysis (Flick, 2009; Glesne, 2011; Hatch, 2002); limited usefulness of software for small data sets (Merriam, 2009); the added distance between the data and researcher (Creswell, 2007; Hatch, 2002; Merriam, 2009); cost (Merriam, 2009); concerns regarding potential quantification of data (Glesne, 2011); and a steep learning curve (Bogdan & Biklen, 2007; Creswell, 2007; Merriam, 2009; Patton, 2002). Overall, each textbook was careful to emphasize that qualitative data analysis software does not actually do the analysis for you in the same way that quantitative software programs do (Bogdan & Biklen, 2007; Flick, 2009; Hatch, 2002; Patton, 2002), which could be interpreted as either a disappointing truth or a relief depending on the reader’s perspective.

Representing the findings

In 1996, Coffey and Atkinson outlined their vision around how hypertext could change the way that qualitative findings were represented. While the arts-based research movement (Barone & Eisner, 2012; Woo, 2008) has received a good bit of attention, most researchers still choose print outlets for their findings despite the accessibility and relative ease of developing photography, videography, and software skills that would make it possible to represent findings in new ways. Visualization tools may be particularly relevant to researchers (Emmel & Clark, 2011; Weisgerber & Butler, 2009). While alternative modes of representation provide an opportunity for innovative findings to be shared with a larger audience, there is an inherent risk of such representations being viewed as art forms versus empirically based understandings (Hammersley, 2010b). There is also the problem of publication outlets for findings that are in forms other than what typically appear in peer-reviewed journals.

Few textbook authors discussed how technology could support alternative ways of representing findings. Glesne (2011), in contrast to most of the authors, mentioned creating nonlinear text representations of findings and emphasized that: “without dispute, computers make the writing and rewriting process easier” (p. 205). Flick (2009) also presented alternate ways to represent findings, including Internet publishing linked to photos, videos, and data excerpts. While Creswell (2007) addressed alternate representations of findings, it was not in relation to new technology but rather examples such as “split-page writings, theater, poetry, photography, music, collage, drawing, sculpture, quilting, stained glass and dance” (p. 179).

Ethical dilemmas

Ethical dilemmas related to new ways of collecting, analyzing, and sharing data were explicitly covered in five of the texts (Berg & Lune, 2011; Flick, 2009; Glesne, 2011; Marshall & Rossman, 2011; Merriam, 2009). Merriam (2009), for example, identified issues around online data collection (e.g., informed consent, confidentiality/security of information, and whether information should be considered public or private). Glesne (2011) provided a section on “privacy and the Internet” in which she addressed what constitutes informed consent and/or whether such consent is needed when investigating Internet communities. Berg and Lune (2011) also addressed “active versus passive consent in Internet research” (p. 78). Marshall and Rossman (2011) covered ethical concerns around uploading digital storytelling projects to the Internet, while Hatch (2002) highlighted ethical issues around the use of video data. While Berg and Lune (2011) acknowledged that the Internet was a useful and comprehensive electronic archive of materials, they also highlighted that this new data source presents new challenges for institutional review boards. Within their discussion of ethics related to the Internet, they pointed to the potential risks in relation to the protection of children and provided strategies for avoiding such risks.

There is no question that the introduction of any new method or technology will require consideration of ethical consequences for the participants, the setting and/or the researcher. Ethical implications remain significant and require the researcher to consider the limitations and benefits of using new technologies. Table 3 presents some of the ethical questions that a qualitative researcher might be faced with when using technologies across the research process.

Table 3.

Ethical Questions Raised by New Technologies.

Research Phase	Ethical Questions
Reviewing the literature	• How can a researcher avoid unintentional plagiarism when working with electronic sources of literature?
Generating and managing data	• How might a researcher determine whether the participants in an online environment are members of a vulnerable population (e.g. children)?
	• Is it ethical to treat publically visible social networking sites as research data?
	• How covert should researchers be in collecting data in public places with handheld devices?
	• Is it ethical to use direct quotations from online data sources that are traceable back to the authors through a simple Internet search?
Transcribing	• When should a researcher anonymize data? Prior to, during, or after transcription?
Transcribing	• In what situations should researchers do their own transcribing to protect participants?
Analyzing data	• Should large data sets ever be made publically available? How can they safely be stored and shared?
Analyzing data	• Should a researcher ever alter the audio or video data to protect the identity of the participants?
Representing the findings	• When a researcher uses the Internet to disseminate research findings, how might they protect their participants’ identities?

While new technologies demand that a researcher delve into ethical domains that are novel for most, this should not discourage researchers from exploring their use. Rather these new technologies require the researcher to remain reflexive as they work to make thoughtful, ethical decisions.

Teamwork

Large-scale interdisciplinary research teams are becoming more prevalent in qualitative work (Anderson & Kanuka, 2003). Synchronous conferencing software, desktop sharing applications, cloud storage, file sharing, and collaborative writing tools afford the ability to manage projects with collaborators at a distance. Merriam (2009) and Silverman (2010) mentioned that QDAS supports teamwork, but neither described this in great detail. Other texts (Hatch, 2002; Patton; 2002; Silverman, 2010) introduced email discussion lists, websites, online journals, professional organizations, and other ways to connect with the research community. Yet they did not explicitly address how the Internet could be harnessed to support collaboration and teamwork. Glesne (2011) noted simply that computer technologies such as the Internet are “powerful ways to share studies” (p. 203). She did, however, mention the use of email for participant recruitment, documentation, and communication. Glesne’s discussion stands as a prime example of how the majority of the texts only minimally addressed the ways in which technology might support teamwork.

While indeed the mere absence or presence of discussion around technology positions its use as more or less important, we also attended in our analysis to how technology, when mentioned, was discussed. How technology use was positioned ultimately functioned to construct particular versions of the possibilities and limitations around the use of technology in research.

Discourses of Technology Use

To illustrate the ways in which technology was discursively framed, we next contrast four texts (Flick, 2009; Glesne, 2011; Merriam, 2009; Silverman, 2010) that (a) discussed technology use across more domains of the research processes than other texts and (b) illustrated variability around how technology use was taken up. Flick (2009), for instance, emphasized opportunity in relation to technology use, whereas Merriam (2009) emphasized caution around the use of technology.

Transcribing data

Glesne’s (2011) and Silverman’s (2010) discussion around interviewing and transcribing illustrated this contrast. Glesne, for example, did not assume that interviews would be recorded, minimizing the use of even audio-recording technology. Her section on “Recording and Transcribing” began with “How will you note your face-to-face interviews? Whether by hand, audiotape or videotape is a matter of your needs and the respondents’ consent” (p. 115). She continued with a discussion of the advantages and disadvantages of taking notes by hand, transitioning to a discussion of audio-recording with, “Many persons will agree to the use of a tape recorder” (p. 115), followed by the suggestion to wait until after the first session to request permission to record if participants are “uneasy.” She highlighted that recording “requires an electrical outlet,” that the use of batteries is “risky,” and that there may be “added frustration” of trying to decipher recordings. These examples show how at times Glesne took up a cautionary discourse in her text, here around the use of recording technologies.

In contrast, Silverman (2010) began his chapter on data collection with, “It goes without saying that your interviews should always be recorded. With improved technologies and a growing recognition of the advantages of being able to play back interviews, the old days of pen and paper recording are long gone!” (p. 200). Silverman positioned the use of technology as something that “goes without saying,” placing the use of audio-recording technology as central to the interviewing process. It was not left as an option that could be trumped by handwritten notes. Rather, the “improved technologies” were oriented to as advantageous in comparison with the old days. We noted the variation in the authors’ choices to highlight the affordances of either the recording devices or by hand methods of data recording. We argue that this choice matters.

Glesne’s (2011) tone shifted, however, when discussing the “technological advances” of digital voice recorders, technology that she said may cause transcription machines to be “relegated to museums, next to mimeograph machines” (p. 116). She went on to describe how some researchers use speech recognition software to transcribe interview data. While she noted the limitations of this, she also indicated that “repeating aloud each word of the interview could evoke thoughts and possible insights that simply typing the words would not” (p. 116). This example positioned technology as able to change how we understand the data in a powerful way.

While Glesne (2011) provided a two-page discussion of issues around transcription, including technology use, she dedicated less overall space than did Silverman (2010), who used five pages to discuss the same topics. The amount of space given to the discussion can function to emphasize the importance, or lack thereof, of new technologies. For instance, Silverman incorporated examples of students using minidisc recorders, lavaliere microphones, digital cameras, and mobile devices to facilitate data collection. Silverman stated: “Make use of the technology you already possess” and described downloading MP3 files from the recorder “to my iPod to allow easy transcription from the comfort of my sofa!” (p. 215). Technology, then, was positioned as something that is likely already within easy reach and able to be integrated into the research process in convenient ways (“from the comfort of my sofa”).

The Internet and qualitative research

We next contrast Merriam’s (2009) and Silverman’s (2010) discussion of the Internet as a source of data. In Merriam’s chapter titled “Mining Data for Documents” she allocated 17 pages to covering various data sources: public records, personal documents, popular culture documents, visual documents, physical materials/artifacts, and researcher-generated documents. Following this lengthy discussion, an additional seven-page section titled “Online Data Sources” was introduced. The choice to create a separate section on “online data sources” positioned online sources as different from other types of documents, even though all of the documents mentioned are likely to be available online. The section on “online data sources” itself comes across as rather dated, with the Internet described as an “information superhighway” accessible to anyone “with a computer and a modem” (p. 156). This description of the Internet ignores the collaboration and communication inherent to Web 2.0, as well as the ever more prevalent broadband connections common in higher education contexts.

Dated and even inaccurate descriptions of the “online world” were noted, such as the claim that

. . . when collecting data from the Internet, the researcher is no longer the primary instrument for data collection; a variety of software tools must be used to locate, select, and process information. Like the researcher, these tools have inherent biases that may affect the study, but their biases may be very subtle—and often much more difficult for a researcher to detect and describe. (Merriam, 2009, p. 160)

One of the overarching tenets of qualitative research is that the researcher is the instrument of the study. Thus, the quote above positioned technology as in opposition to the very essence of qualitative research, as well as making the Internet as a data source seem like an arduous (“a variety of software tools must be used”) and biased endeavor that is out of the researcher’s control (“inherent biases that . . . may be very subtle”). The summary section on online data sources ended with a very short paragraph, “Data gathering online is an emerging area of keen interest for qualitative researchers. However, a number of issues must be considered when using data from an online interaction; I reviewed some of these issues in this chapter” (p. 163). This sentence leaves the reader with an overall impression of needing to be cautious and wary around the “issues” of online data such as the instability of websites, the lack of participant authenticity, and even deception.

Silverman (2010), in contrast, included student examples of qualitative studies throughout the text, some of which included the use of the Internet as a natural choice for a qualitative study. For instance, Silverman included a description of an ethnographic study on “newsgroups on the Internet.” He stated, “Danny’s topic is the Internet. He is concerned with how people assemble themselves as a community via the net . . .” (p. 51). No cautions or warnings against doing such a study were included, though terms such as “newsgroup” and “the net” are by now rather outdated. Moreover, in contrast to Merriam (2009), Flick (2009) included an 8-page chapter on “using documents as data,” immediately followed by a 17-page chapter covering the Internet not only as an object to be studied, but also as a tool for data collection (e.g., online interviewing, online focus groups, and virtual ethnography). Flick opened this particular chapter by highlighting that technology has become a natural part of our lives, is here to stay, and will no doubt impact our research lives. Flick framed technology as something that the qualitative researcher is affected by on multiple levels. He also described “some advantages and possibilities of using” technology, as well as “limitations of research based on Internet methods” (p. 264). In this way, Flick’s discussion centered the importance of considering the affordances and constraints inherent to technology use.

Rather than cautionary warnings or outdated claims, Flick’s (2009) chapter provided ideas for new topics of study and ways of conducting research. He outlined what he called “preconditions” for doing research online (e.g., computer competence/enjoyment, familiarity with the Internet, and access to the Internet). The problems and limitations of using online tools were addressed only after, and with less attention, than the practicalities of doing this kind of work, focusing on how to do it well rather than reasons not to do it at all. This approach did not frame technology as something to be feared and avoided by qualitative researchers. Flick closed the chapter by noting that if ethical and technical issues are taken into account, Internet research “can be fruitful and helpful” and that “the development of qualitative Internet research has only just started and will continue in the future” (p. 279). Technology tools, then, were framed as playing a potentially useful and central, if not inevitable, role within qualitative research.

QDAS packages

In this section, we contrast how Merriam (2009) and Flick (2009) discussed the use of software for data analysis. Merriam (2009) allocated four pages to a section titled, “Computers and Qualitative Data Analysis,” which was placed after the entire discussion on data analysis. In this way, technology was positioned as an afterthought to the analysis process, something that may or may not support the process. The first sentence of this section noted that “the computer has a great capacity for organizing massive amounts of data, facilitating analysis, and assisting communication among members of a research team” (p. 193). Merriam went on to point out that “the use of computers has evolved into something of a subfield labeled CAQDAS, which stands for Computer-Assisted Qualitative Data Analysis Software” (pp. 193-194). The description “something of a subfield” positioned it as outside of the mainstream of the community of qualitative researchers. The next sentence emphasized Bogdan and Biklen’s (2007) focus on the “assisted” part of CAQDAS, noting that computers do “not do the analysis for the researcher” (p. 194). In fact, Ruona (2005) is cited as claiming “that basic word processing programs are quite adequate for most qualitative data analysis” (p. 194). Software programs, then, were minimized and positioned as no more than sophisticated word processors.

This minimization was continued as computer software programs were described as being mainly useful for “data management” (typing, transcribing, entering data, and editing) (Merriam, 2009, p. 194). It was next emphasized that “it is the researcher, not the computer program, who assigns codes . . . this is why we say analysis is ‘assisted’ by these programs” (p. 195). A short paragraph near the end of this section outlined the advantages of software (e.g., taking care of “boring clerical work,” encouraging a close examination of data, providing a way to visualize relationships, and working with large data sets and team projects). This, however, was then followed by a longer paragraph on the limitations of the software including its expense, its limited usefulness for small data sets, the steep learning curve, and the inability to support certain types of analysis. A good number of these limitations would likely be contested by researchers who use these QDAS programs (as will be addressed in the discussion). Merriam also positioned word processing as being just as efficient as QDAS programs. Such a move functioned to place the use of technology as something that offered few, if any, useful benefits to the researcher. Merriam’s overarching concern seemed to be that QDAS places a “machine” between the research and the “actual data” (p. 196). Ultimately, then, the reader was left questioning the appropriateness of using software packages.

Flick (2009) in his chapter “Using computers in qualitative analysis” took a different approach, positioning data analysis as just one way that technology is changing the nature of research: “Qualitative research is undergoing technological change and this is influencing the essential character of qualitative research” (p. 359). He acknowledged that technological developments still have a way to go, noting that “if these developments become more established than they have up to now, considerable impacts on qualitative research and its practices will probably result” (p. 359). Flick’s opening section was called “new technologies: hopes, fears and fantasies,” and he acknowledged the “mixed feelings” the qualitative research community has had about technology. He acknowledged these mixed feelings, immediately pointing out, as did many of the authors, that “QDA software does not do qualitative analysis in itself or in an automatic way like SPSS can do a statistical operation or factor analysis” (p. 359). This statement, echoed across the texts, seemed to be designed to counter any hopes or mistaken beliefs that newcomers might have about what the software can or cannot “really” do. Flick (2009), like Merriam (2009), compared the software with a word processor in that it “makes it somewhat easier for you to write a text” (p. 359) but did not suggest, as Merriam did, that software programs are not much more useful than word processors.

Flick (2009) focused on the various ways to use computers, the “real hopes” (speed, increased quality, data management, data representation), and guiding questions as to how to select the right program. Rather than solely warning the researcher to remember that the software “only assists,” he cited and countered common fears about QDAS; for example, that it would bias the analysis process. Flick cited research showing that the grounded theory influence on software development does not result in researchers only taking up grounded theory methodologies. Flick encouraged the reader to, instead of avoiding the tools, be attentive to how software might shape, for better or worse, their research process, while remembering that research with technology, just like research without technology, provides advantages and disadvantages.

Overall, Flick (2009) positioned the researcher, who is the instrument, as capable of thinking through how technology might create new possibilities and limitations to their research process. He stated, “computers and software are pragmatic tools that support qualitative research. Their users should reflect on the technology’s impact on the research itself. Neither should they be overloaded with hopes and expectancies, nor should they be demonized” and that in general no “technology revolution of qualitative research” (p. 370) has yet occurred.

Discussion and Conclusion

In our analysis of the 11 introductory qualitative texts, we noted that nearly all the texts limited their discussion to how technology could support the data collection, transcription and data analysis domains. We noted that the ways in which these tools are discussed vary, with consequences for how novice researchers are likely to understand the relationship between methodology and technology. While texts specializing in online data collection and analysis methods are proliferating (Fielding, Lee, & Blank, 2008; Kozinets, 2010; Lewins & Silver, 2007), introductory qualitative research texts have not yet systematically taken up a comprehensive view of how technology can be used to support the entire research process. We are reminded of Davidson and di Gregorio’s (2011) claim that technological developments and methodological developments have not been in step in the qualitative research community.

This became particularly clear to us as we noted that when textbooks did address the use of technology it tended to be in “traditional” ways—selecting the best devices to record interviews, ways to transcribe recordings, and the use of data analysis software. In terms of the discussions around QDAS, it often was not clear whether the authors used QDAS programs in their own research practice. We noted that many of the claims around QDAS were supported by referencing Weitzman’s (2000) handbook chapter as well as Weitzman and Miles (1995) Computer programs for qualitative data analysis. Of greater concern was that the claims made would likely be contested by experienced users of QDAS and seem to be perpetuating some “myths” around the use of software for qualitative research (see Bong, 2002; MacMillan & Koenig, 2004; Taylor, Lewins, & Gibbs, 2005). For example, the suggestion that QDAS places “distance” between the researcher and the data is a claim that is repeated but never fully explained. If an event is recorded with audio or video equipment and then transcribed, is this not already “distancing” the researcher from the event being studied? Or perhaps the concern is that experienced researchers are used to manipulating index cards, handwritten notes, or transcripts by hand—and the idea of doing so via the computer feels more “distant.” However, for the newer generation of researchers, using computers is part of everyday life, and so this concern about “distance” may well resolve itself over time.

The concern that QDAS may lead to “quantifying” the data, resulting in a shallow analysis of increasingly larger data sets, or be unsuitable for certain analytic approaches all seem to directly contradict the claim, made across the textbooks, that qualitative software does not analyze the data for you in the way that, for example, SPSS can run an ANOVA for you. Even Maxwell (2005), who did not overtly discuss technology anywhere in the text, included a call out box in the methods chapter titled “A Mismatch Between Questions and Analysis.” This call out box described a 1991 study in which the use of The Ethnograph software resulted in “destroying the contextual unity of each historian’s views and allowing only a collective presentation of shared concerns” (p. 99). Maxwell clarified that “the fault was not with The Ethnograph, which is extremely useful for answering questions that require categorization, but its misapplication” (p. 99). The assumption here seems to be that software programs have a mind of their own and/or are designed for a particular kind of analysis and no other—in this case “categorization.” That the referenced study was published in 1991 implied that little to nothing about this particular software package, or software in general, had changed in the intervening 14 years.

While it is true that QDAS can handle large data sets efficiently and that code and retrieve features make it possible to count and quantify (and categorize), it does not follow that these are the only, or even most useful, features of the software. Nor does it mean that the software requires researchers to collect more data or take a quantitative approach to understanding that data. We found it ironic that Seale’s (2010) chapter in Silverman (2010) claimed that QDAS was not particularly useful for conversation analysis or discourse analysis studies, given that we ourselves began using the memoing, coding, and commenting features of ATLAS.ti as part of our discourse analysis research (Lester & Paulus, 2011). Some, such as di Gregorio and Davidson (2008), have argued that QDAS has gone beyond simply assisting with data analysis to serving as a comprehensive “container” for documenting the entire study.

In addition to these somewhat outdated notions of what data analysis software programs can and cannot do, the lack of attention in most of the textbooks to the nature of Web 2.0 tools for fostering collaboration, transparency, and reflexivity suggested that the majority of introductory texts present a limited and limiting “read” of technology for qualitative research. It could be that the minimal attention given by The SAGE Handbook of Qualitative Research to new technologies sets a precedent for the introductory textbook writers. Authors and researchers may want to explore Hesse-Biber and Leavy’s (2008) Handbook of Emergent Methods for more recent and comprehensive treatments of the possibility of integrating technology into qualitative research. This handbook dedicates an entire section (albeit it the last section) of eight chapters to exploring “The Impact of Emergent Technologies on Qualitative Methods.” Hesse-Biber’s more recent (2011) Handbook of Emergent Technologies in Social Research provides an even more comprehensive review of new tools for qualitative, quantitative, and mixed methods research—including a section on “audiovisual, mobile and geospatial technologies’ impact on the social research process.”

New technologies always challenge, to some extent, the way work is currently being done, and that can often result in resistance. Diffusion of innovations (DOI) theory can help explain the variation in how scholars are taking up new technologies (Rogers, 2003). DOI is the process “by which (1) an innovation (2) is communicated through certain channels (3) over time (4) among the members of a social system” (p. 11). An innovation is an idea or object that is considered new by either a single person or a group of people. Once introduced to an innovation, communication occurs between those who quickly embrace the innovation, known as “early adopters,” and those who are not ready to accept, and who may ultimately even reject, the innovation. In the research context, those who are already using technology to support their research can be classified as “early adopters.” They have learned of the affordances of the tools and, over time, integrated them into their work. Those who are resisting the use of these tools have either learned about the programs and rejected their use or have been influenced by others to do so. The communication channels used are an important component of this theory. Rogers (2003) stated that most people rely on the opinion of a new innovation relayed to them by someone who has already adopted it. If senior scholars and graduate faculty are not using the tools in informed ways, it makes it less likely that the next generation will, either.

Those with power (established faculty, those who write the textbooks) may be hesitant to embrace new technologies, but graduate student demand for informed conversation around the use of technology is growing. Our findings can serve as a starting point for greater dialogue among scholars and methods instructors seeking to better understand and evaluate technologies as they increase in prevalence and use. We are not arguing that technology should be used all the time by all researchers. Yet neither should the affordances of new technologies be ignored or misrepresented, especially not by textbook authors or those mentoring new researchers. While new technologies should not necessarily be adopted wholesale, neither should they be immediately feared, avoided, or rejected. Instead, we suggest that a greater awareness of technological developments and an understanding of how to evaluate the affordances and constraints of these tools are critical for researchers. The socialization of new qualitative researchers into a stance that is open to examining the ways in which new technologies generate, for instance, new ways to engage with research participants, collect data, and represent findings, has the potential to result in methodological innovation and enrich understandings. We see no better place to explore such possibilities than in an introductory methods course.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Trena M. Paulus holds an MS and PhD in instructional systems technology from Indiana University and an MA in applied linguistics from Ohio University. She is currently an associate professor in the Department of Educational Psychology and Counseling at the University of Tennessee. Her areas of research and teaching include online learning environments, computer-mediated communication, and discourse analysis methodology.

Jessica Nina Lester is an assistant professor in inquiry methodology at Indiana University. She holds a PhD in educational psychology and research from the University of Tennessee, as well as a certificate in qualitative research methods in education and autism spectrum disorders. Her research interests include qualitative methodologies, critical notions of human learning and development, and the educational experiences of targeted youth in educational settings.

Virginia G. Britt is a doctoral candidate in the Instructional Technology PhD program at The University of Tennessee, Knoxville. She holds a master’s degree in educational media and technology with a concentration in school library media from East Tennessee State University. Her research interests include qualitative methodologies, the development of technology courses in teacher preparation programs, and the impact of teacher professional development programs.

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