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“Like Having a Tiger by the Tail”: A Qualitative Analysis of the Provision of Online Education in Higher Education

by Justin C. Ortagus & R. Tyler Derreth - 2020

Background/Context: Online education has become an increasingly prevalent medium of instruction and the primary source of enrollment growth for colleges and universities. The well-documented growth of online education is often regarded as a response to rising costs in higher education, but the same cost-saving strategies that would allow institutions to increase their net revenue through online education may also serve to endanger the quality of student learning.

Purpose/Objective/Research Question/Focus of Study: This study explores how leading universities reconcile financial and quality considerations when offering online education.

Research Design: Drawing from interviews with 22 administrators, faculty members, and instructional designers, we conduct a qualitative analysis of how to navigate financial and quality considerations pertaining to the development and delivery of online courses and exclusively online degree programs.

Findings/Results: The central finding of this study focuses on the importance and pursuit of quality as an actionable goal when offering online education. We also find emergent themes related to the business model of online education, the influence of online education on the changing faculty role, and the shift toward student-centered learning in online education.

Conclusions/Recommendations: We offer a novel conceptual model, the Model of Quality-Driven Decision-Making in Online Education, to show how universities can navigate financial and quality considerations when offering online education in higher education.


Online education has become an increasingly prevalent medium of instruction and the primary source of enrollment growth for colleges and universities (Sener, 2012). The proportion of college students who enrolled in at least one fully online course has increased from 5.9% in 2000 (Ortagus, 2017) to 42.9% in 2016 (authors’ calculations using NPSAS:16 data). The well-documented growth of online education is often regarded as a response to rising costs in higher education given that online courses and exclusively online degree programs have the potential to offer financial relief to many colleges and universities (Bowen, 2013; Cheslock, Ortagus, Umbricht, & Wymore, 2016; Meyer, 2006; Miller, 2010). However, the same cost-saving strategies that would allow institutions to increase their net revenue through online instruction may also serve to endanger the quality of student learning.

Several researchers have reported that online education can be detrimental to students’ academic outcomes (e.g., Figlio, Rush, & Lu, 2013; Xu & Jaggars, 2011, 2013), but additional studies offer conflicting evidence regarding the effectiveness of online education (Lack, 2013). Online instruction can be leveraged to reduce costs by offering high-enrollment courses and the same digital content each semester, but such decisions may diminish quality by replacing student–faculty interaction with technology (McPherson & Bacow, 2015). Despite questions pertaining to the merit of online education, the vast majority of colleges and universities continue to embrace online education as central to their commitment to increase access and ensure financial viability in future years (Allen & Seaman, 2014). Even within the higher education community, there is widespread disagreement pertaining to whether any cost savings or net revenue increases associated with online offerings would be outweighed by the potentially negative effects on students’ academic outcomes (Bowen, 2013). Allen, Seaman, Lederman, and Jaschik (2012) reported that the level of concern about the effectiveness of online education is far greater among faculty members than higher education administrators.

Although a large number of quantitative studies have compared the outcomes of students enrolled in online courses versus the outcomes of students enrolled in face-to-face courses (Figlio et al., 2013; Means, Toyama, Murphy, & Baki, 2013; Ortagus, 2018; Shea & Bidjerano, 2014; Xu & Jaggars, 2011, 2013), extant literature has limited value for higher education administrators and policymakers seeking to better understand how to navigate financial and quality considerations related to the provision of online education. As a result, this study focuses on how faculty, instructional designers, and higher education administrators reconcile the seemingly opposing motivations of increasing revenue and maintaining quality when offering online education. To do so, we ask the following research question: How do leading universities reconcile financial and quality concerns when providing online education?


Previous studies have examined the extent to which online education can offer financial relief to colleges and universities (Bowen, Chingos, Lack, & Nygren, 2012; Meyer, 2006; Miller, 2010) or the quality of online education in higher education (Figlio et al., 2013; Means et al., 2013; Ortagus, 2018; Shea & Bidjerano, 2014; Xu & Jaggars, 2011, 2013), but the literature is lacking any studies that consider both financial and quality dynamics at the same time (Cheslock et al., 2016). Although online education has the potential to reduce labor costs and consequently increase net revenue through less face-to-face interaction and larger class sizes (Bowen, 2013), little is known about how to navigate these revenue-enhancing strategies without sacrificing high-quality teaching and learning. In addition, the growing body of literature examining the quality of online education in higher education typically uses inconsistent definitions of quality, employs quantitative methodological approaches, and offers conflicting results (Lack, 2013). This review of the literature identifies relevant scholarship and situates the need for a qualitative inquiry that considers both financial and quality complexities related to decision-making when offering online courses and exclusively online programs.

Costs in higher education continue to rise at a faster pace than costs in the overall economy (Bowen, 2013). Despite this trend, public funding for higher education has declined significantly across the United States. Total state appropriations for public colleges and universities in the United States declined from $54.5 billion in 2002 to $45 billion in 2012 (Jaquette & Curs, 2015). Private institutions have faced their own financial issues due to declining enrollment numbers (Belkin, 2013) and calls to curb rising tuition prices, despite an increasing reliance on tuition revenue throughout higher education (Cheslock et al., 2016). In response to these financial challenges, higher education institutions have increased their dependence on entrepreneurial activities and alternative streams of revenue (Cheslock & Gianneschi, 2008; Jaquette & Curs, 2015; Slaughter & Leslie, 1997; Slaughter & Rhoades, 2004), particularly online education. Ortagus and Yang (2017) found that public four-year institutions responded to declines in state appropriations by increasing the number and percentage of students enrolled in online courses.

The cost structure of online education is often associated with economies of scale, which implies that the cost advantages of online courses are generally present at larger enrollment numbers (Cheslock et al., 2016). Morris (2008) noted that economies of scale are typically viewed as a primary driver for the provision of online education. Previous studies have outlined many of the potential cost efficiencies associated with online delivery (Bowen et al., 2012; Meyer, 2006; Miller, 2010), but these studies failed to seriously consider quality when identifying cost savings generated through online offerings (Bowen, 2013). Previous scholars have suggested that research failing to account for both financial and quality considerations offers little value to higher education administrators and policymakers, as instructional policies that reduce costs or increase revenue would need to do so without unduly harming the quality of teaching and learning (Cheslock et al., 2016).

Numerous researchers have empirically examined the quality of online education in higher education (Ary & Brune, 2011; Daymount & Blau, 2008; Driscoll, Jicha, Hunt, Tichavsky, & Thompson, 2012; Figlio et al., 2013; Lewis & Harrison, 2012; Means et al., 2013; Mentzer, Cryan, & Teclehaimanot, 2007; Poirier & Feldman, 2004; Shea & Bidjerano, 2014; Wagner, Garippo, & Lovaas, 2011; Xu & Jaggars, 2011, 2013). In a meta-analysis of empirical research examining the effectiveness of online learning, Means et al. (2013) reported that students enrolled in hybrid or blended courses produced modestly better academic outcomes when compared to their peers enrolled in face-to-face courses. The authors found no significant difference between the academic outcomes of students enrolled in purely online courses versus students enrolled in face-to-face courses. In contrast to these findings, Figlio et al. (2013) presented the first experimental study of face-to-face instruction versus online instruction and found that students enrolled in the face-to-face version of the same large-enrollment economics course performed better than their online peers.

Xu and Jaggars (2011, 2013) found that online students were more likely to withdraw from a course and receive a lower grade than their peers enrolled in face-to-face courses. However, Shea and Bidjerano (2014) reported a positive relationship between online enrollment and student achievement, claiming that online students had a better chance of earning a postsecondary credential than their peers enrolled solely in face-to-face courses. Additional quasi-experimental work has shown that students who enroll in some online courses are less likely to drop out of college when compared to their otherwise-similar peers enrolled solely in face-to-face courses (Ortagus, 2018). These studies serve as examples of the varying narratives and lack of conclusive evidence pertaining to the quality of online education in higher education. Empirical studies comparing the academic outcomes of online and face-to-face students typically offer high internal validity but focus solely on a single higher education institution or the community college sector. This study complements previous quantitative work related to the academic outcomes of online students by examining the process behind how university actors balance quality and financial concerns when offering online education.

The conceptual framework of this study is guided by the concept of cost–benefit analysis (Drèze & Stern, 1987), which can be used as a lens through which to view the causes and consequences of decisions related to the provision of online education in higher education. In its simplest form, the concept of cost–benefit analysis provides a consistent procedure for institutional leaders seeking to balance seemingly opposing dynamics as they arise during their university’s pursuit of efficiency and excellence. The majority of participants we interviewed described some version of a process in which they identified the relevant costs and benefits (financial and otherwise) of providing online education. Previous work has noted that institutional decisions to lower costs (and potentially increase net revenue) may harm quality, whereas decisions to increase quality would likely increase costs (Immerwahr, Johnson, & Gasbarra, 2008).

An application of this logic can be used when making enrollment decisions for online courses. For example, the pursuit of large enrollment numbers (financial) may come at the expense of student–faculty interaction (quality), leaving institutional decision-makers to weigh the costs and benefits associated with providing online education. The concept of cost–benefit analysis, which can be applied to measure quantitative or qualitative benefits, allows for a systemic way of understanding how decisions are made when attempting to balance competing dynamics related to the efficiency and effectiveness of a given program (Cellini & Kee, 2010; Drèze & Stern, 1987).

Although the concept of cost–benefit analysis provides a useful lens through which to view our research question and organize our findings, many of the complexities of developing and delivering online education cannot be captured in this general framework. As a result, we propose a novel conceptual model, the Model of Quality-Driven Decision-Making in Online Education, to be presented in the Results section and described in greater detail within the Discussion section. This novel conceptual model centers our core findings to show the process behind leading universities’ navigation of complex financial and quality considerations when providing online education, suggesting that quality- and revenue-driven considerations can work in complementary ways to allow online programs to center quality while meeting their financial goals.



Because this study asks how to reconcile financial and quality considerations when offering online education, we employ a qualitative methodology (Miles & Huberman, 1994). A basic qualitative inquiry allows researchers to explore a phenomenon in depth within its individual context, relying on interviews with participants to gain insights into the phenomenon being studied and the context in which it is situated (Merriam, 1998). This study used a comparative inquiry including multiple universities to better understand the extent to which decisions related to the provision of online education are institutionally situated (Merriam & Tisdell, 2016).

Although we sought to better understand the experiences and practices of participants at four institutions, this exploratory study did not seek to describe the process within each site in extreme detail or attempt to explain the phenomenon being studied in a generalizable or causal way. Through the use of a constructionist approach, we acknowledge the value of each administrator’s perspective and individual context regardless of his or her position within the institutional hierarchy (Crotty, 1998). In addition, we use a constructivist approach to examine interview data, discover emergent themes, and draw upon researcher–participant interactions to co-construct the meaning of the interviews (Charmaz, 2006), recognizing that researchers introduce subjectivity and cannot completely remove themselves from the process of data collection or analysis (Creswell, 2012).


The sampling strategy for this qualitative inquiry was a combination of purposeful, snowball, and theoretical sampling (Morse, 2010). Because our research question emphasizes leading universities related to the development and delivery of online education, each institution included in this study was selected as one of the “Best Online Programs” in the 2018 edition of U.S. News & World Report. We chose universities from this specific list of online leaders because the metrics for selection incorporate a host of quality indicators, such as student engagement, faculty credentials, student services, peer reputation, and admission selectivity. We focus specifically on interviewing decision-makers from public research universities for two primary reasons. First, we originally sought to better understand how leading institutions, specifically, navigate the complex dynamics associated with developing and delivering online education, and the vast majority of institutions listed among the aforementioned “Best Online Programs” were public research universities. Second, many public research universities face financial pressures to generate alternative revenue sources due to decreases in state funding (Cheslock et al., 2016; Cheslock & Gianneschi, 2008; Jaquette & Curs, 2015), and previous researchers have identified the potential of online education to offer financial relief to higher education institutions (Bowen, 2013; Cheslock et al., 2016; Meyer, 2006; Miller, 2010). As a result, we selected public research universities identified as national leaders in online education due to our expectation that these specific institutions are navigating financial and quality concerns in a highly effective manner.

Participants from each university were chosen based on their roles, expertise, and experiences related to the decision-making process regarding the provision of online education. Our initial wave of interviews followed a method in which each participant was selected based on the desire to interview high-level decision-makers (Morse, 2010), focusing specifically on higher education administrators with the positional authority to make key decisions related to the development and delivery of online education. Through those initial interviews, we discovered that we needed to include additional perspectives that considered the critical role of instructional designers and faculty members when offering online education.

As a result, we interviewed instructional designers, faculty members, and higher education administrators from three research universities identified as national leaders in online education. The professional role and background of participants varied considerably to ensure diverse perspectives in the sample, but each participant in this study was actively involved in either teaching online courses or administering online programs at his or her university. In total, we interviewed 22 participants for this study, including six instructional designers, seven faculty members, and nine administrators. To protect the anonymity of the participants, Table 1 provides a pseudonym for their name, a pseudonym for their institution, and their general professional role.

Table 1. Pseudonyms and Professional Roles of Participants

Name (Pseudonym)

Institution (Pseudonym)

Professional Role


University of Granite

Former University President


University of Granite

Director of Academic Affairs


University of Granite

Fixed-Term Faculty Member and Online Program Coordinator


University of Granite

Tenured Faculty Member


University of Granite

Tenured Faculty Member


University of Granite

Undergraduate Instructor


University of Granite

Undergraduate Instructor


University of Granite

Instructional Designer


University of Granite

Instructional Designer


University of Granite

Instructional Designer


University of Granite

Vice President


Quartz State University

Associate Provost


Laminate State University

Instructional Designer


Laminate State University

Tenure-Track Faculty Member


Laminate State University

Fixed-Term Faculty Member


Laminate State University



Laminate State University

Instructional Designer


Laminate State University

Tenured Faculty Member


Laminate State University

Instructional Designer


Laminate State University

Director of Online Programs


Laminate State University

Associate Dean


Laminate State University

Director of Teaching and Learning Center


Data sources for this study included interviews that lasted between 45 and 75 minutes and were subsequently transcribed verbatim. All interviews were one-on-one and semi-structured to allow the participants to describe their own experiences related to teaching and administering online education. The interview protocol used for this study was designed to yield relevant information about how participants offer high-quality online courses, leverage online programs to generate revenue, and navigate quality and financial considerations when providing online courses and exclusively online programs. In the interviews, we typically asked separate questions regarding quality and financial considerations in online education before asking how to balance both dynamics at the same time. To allow the data to drive the conversation, the interviews were intentionally conversational in that follow-up questions varied according to the role and responses of the participants (see Appendix A).

For the data analysis, both researchers coded all of the transcripts. To ensure inter-researcher reliability, the researchers examined each other’s coding. The researchers discussed the code in question when any discrepancies were discovered between their interpretive analyses. Based on investigator triangulation methods, we would explain our interpretation and decide whether to eliminate a perspective, merge the interpretations based on further discussion, or maintain both perspectives in order to preserve the depth of each interpretive analysis (Carter et al., 2014). In our analysis, we interpreted the interview data using line-by-line codes (see Appendix B). We synthesized those initial codes into the categories that repeatedly emerged within the data. During the next stage of coding, we pulled the fractured data into subcategories to identify how the emerging themes related to how universities balance quality and financial considerations when offering online education (see Appendix C). Following the process described above, we drew the following major categories from our data: “quality,” “the business model,” “the changing faculty role,” and “student-centered learning.”


Trustworthiness refers to the credibility of qualitative studies, as indicated by the rigor displayed throughout the data collection and analysis. Lincoln and Guba (1986) noted that qualitative studies are inherently bound by context and require different criteria than conventional measures of validity and objectivity. Instead, this study has achieved trustworthiness through practices of credibility, transferability, confirmability, and triangulation. We developed a rich description of our data by reporting detailed processes in place from multiple perspectives within a university setting and established credibility by employing methods for investigator triangulation, as discussed above (Carter, Bryant-Lukosius, DiCenso, Blythe, & Neville, 2014; Golafshani, 2003; Stake, 2010).

In addition, peer debriefers, experts with significant experience using qualitative methodology, confirmed a portion of the codes, categories, and rationale employed in this study (Charmaz, 2006; Creswell, 2012; Lincoln & Guba, 1986). As an additional measure of credibility and confirmability, we conducted member checks with participants by sharing the transcript and a summary of emerging themes to confirm the accuracy of our findings (Creswell, 2012; Lincoln & Guba, 1986). Participants found our study to be thorough and confirmed the findings of our analysis. We also continually tracked and discussed our subjectivities in order to recognize biases when discussing perspectives drawn from the data (Creswell, 2012; Lincoln & Guba, 1986; Shenton, 2004).


This study has several limitations. Although we examined course materials and university documents to confirm selected findings, complete triangulation was not achieved (Guba & Lincoln, 1989). In addition, the interviews took place over a two-year period, which created some complexities given various changes in the online education market, such as the diminishing role of for-profit institutions. Finally, this qualitative inquiry can only be considered applicable to institutions where instructional designers are an active part of online course design and development, as other institution types have different organizational structures and financial pressures to navigate when offering online education.


The instructional designers, faculty members, and higher education administrators who participated in this study addressed topics associated with the decision-making process when offering online education at their university. Although we began this study asking participants how to balance quality and financial considerations in online education, a core category emerged in which personnel at all levels described the importance of making “quality” an actionable goal when developing and delivering online courses and exclusively online programs. The data revealed three other emergent categories: (1) the business model of online education, (2) the changing role of faculty, and (3) the shift toward student-centered learning.

Each of these categories points to a component of the decision-making process associated with reconciling financial investments and quality-centered initiatives in online education. Because quality was repeatedly identified as a central function of online education, we first explore how participants understood quality. In the following three sections of our findings, we examine how participants enacted quality-centered initiatives in online education while navigating a host of financial considerations. First, through a business model approach, participants monetize quality as a distinctive “brand” for their online program. Second, by changing the faculty role for online education, participants discussed leveraging the specific skillsets of both tenure-track or tenured faculty and adjuncts. Finally, participants highlighted the power of creating online courses designed for student-centered learning when seeking high quality, high enrollment, and high retention in online education. Given the themes of this study, quality appears to be centralized in the decision-making process when offering online education, even if the aim is to commodify quality indicators to facilitate enhanced revenue. Through our emergent conceptual model (to be described later), we contend that quality and financial considerations are inextricably linked, and certainly not diametrically opposed, for any university seeking to become a leader in the provision of online education.


The participants identified quality in online education as difficult to define, as the definition of “quality” varied according to the professional role of the user of the term. Devin, an instructional designer at Laminate State University, labeled the design of any online course as critical and the “the straw that stirs the drink,” but most faculty members identified faculty presence as paramount in any discussion of the quality of an online course. More generally, participants described quality (a) as measurable indicators, (b) in comparison with face-to-face instruction, or (c) as wholly perspective bound.

Measuring Quality Indicators

A number of our participants were hesitant to define quality for all of online education but instead referred to various indicators of quality. These indicators act as measurements for the value and relative success of online education at their institution. Quality indicators ranged widely, but the following subcategories eventually emerged: student outcomes, the student experience, faculty, and curriculum and design. The student outcomes and student experience codes revealed that instructional designers, faculty members, and administrators use student feedback, retention data, and labor market outcomes as measures of quality.

Several administrators noted the importance of buy-in from tenure-track and tenured faculty members, particularly in relation to the development of online courses. There was not a consensus among the participants about whether tenure-track and tenured faculty provide a higher-quality course experience relative to fixed-term instructors, as most participants suggested that quality stems more from faculty engagement rather than the status of the faculty member. Susan, a fixed-term faculty member at the University of Granite, shared that “the most important piece for quality or success for online instruction and in-person instruction has to do with the instructor’s own engagement with the course, engagement with the students, commitment to the course.” These data do not reveal whether instructor type impacts the quality of the online course, but a central focus on faculty engagement with students appears to be a more widely accepted way to ensure the quality of online courses. The participants also discussed the labor-intensive process of developing and designing a quality online course. Online education is different than face-to-face courses because the fixed costs associated with the development of an online course are significantly higher than the fixed costs of developing a face-to-face course. Derek, a tenured faculty member, explained the importance of investing a substantial amount of time and resources upfront when developing online courses:

[F]aculty members can’t just put their syllabus up. You have to design a course. You have to work with our instructional designer for two semesters. All that’s complicated, expensive, lots of payroll, but when faculty understand that’s what’s necessary in order to have quality and move their program forward and get all the goodies from it, that’s why programs get successful.

The development of quality online courses requires a team of experts who can put together an academically rigorous, pedagogically sound, and user-friendly platform for online students.

Quality Comparison

All participants in this study discussed quality through a framework of comparison, particularly in relation to the comparison of online courses to face-to-face courses. Several participants took exception to those who claim that online education may be inferior to face-to-face education. Barbara, a Director of Academic Affairs at the University of Granite, provided institutional data to show that the academic outcomes of online students at her institution compare favorably to the academic outcomes of their face-to-face peers.

While the comparison of student performance between online and traditional, face-to-face programs was a major point of emphasis for administrators, quality comparisons were broadened to the rigor of design and instruction methods. Donald, Associate Provost at Quartz State University, suggested that face-to-face courses are not subject to the same level of assessment as online courses: “People always talk about the quality of face-to-face instruction, yet we don’t see any studies on what that looks like. We know what works and what doesn’t work in an online setting, but we have yet to see the same level of research for face-to-face instruction.” Paul, a tenured faculty member at Laminate State University, claimed that broad comparisons between online and face-to-face programs are extremely problematic:

The devil is in the details. I feel that sometimes administrators forget that. . . . Certain disciplines [like hard sciences and math] have right and wrong answers that may be more amenable to automated grading technologies and may not require the individualized support of a discussion-based course. Quality [online] instruction looks very different across disciplines.  

Perspective-Bound Quality

Many of the instructional designers, faculty members, and administrators addressed the most commonly coded problem with defining quality. Quality of instruction is inherently perspective bound, which creates problems when attempting to define quality. Allison, an Instructional Designer at the University of Granite, stated, “[Quality] is a general term, and I think it’s something we struggle with as a university as a whole because quality is very different for different people.” James, who is a tenured faculty member, also commented on the perspective-bound nature of quality: “The definition of quality varies quite a bit from context to context. It’s hard to even agree upon what we mean conceptually when we say quality.” Administrators referenced the importance of the perception of quality, particularly considering the crowded market of online education. Even if the actual quality of the online program is unclear, various administrators suggested that the perception of the quality of the affiliated university offering the program is paramount to potential students. Allison noted, “There are plenty of business schools online, but it’s that we’re [the University of Granite], and we have a lot to offer.”


Another category of data that emerged through the interview process was drawn from the challenges associated with attempts to reconcile financial imperatives and quality concerns when offering online education. The participants in this study described (a) online education as an alternative revenue source, (b) the process in which greater revenue leads to investments in greater quality, and (c) the importance of making data-driven decisions before engaging online courses and programs. One key dynamic outlined by several higher education administrators related to the importance of online programs attracting students without detracting from already-existing face-to-face programs. Brad, Director of Online Programs at Laminate State University, shared that one rule trumps all others from a financial perspective: “Thou shalt not cannibalize or impact any opportunities or poach any of the enrollments from existing on-campus programs.”

Online Education as an Alternative Revenue Source

Nearly every participant referenced the potential of online education as an alternative revenue source for the university. Several administrators noted that revenue generated from online programs is typically used to subsidize other on-campus programs. Frank, a fixed-term faculty member and online program coordinator, stated that “decreases in state funding force you to be more entrepreneurial and look for alternative revenue streams” before noting that online programs have the potential to improve the financial outlook at a given university:

At my previous [regional] institution, I would tell people we’re doing well with our online program. We had about 300 students and graduated about 75 students per year. We were making about $2.5 million per year in net profit. People’s eyes would light up. You can be profitable to compensate for those revenue decreases from the state. The chair of the board at [a public research university] said that [offering online education] is like having a tiger by the tail. It’s an area of profit and enormous growth. You’d better not let it go.

Greater Revenue Leads to Investments in Quality Online Instruction

Derek suggested that high-quality online instruction comes at a high price: “We’re more expensive than just about everybody and we’re not expensive because we jack the price up. It’s expensive, it’s just expensive to do it the way we do and have that kind of quality.” James noted that investing in quality is worthwhile because you’ll be paid back for that investment, “which will allow you to either charge higher tuition or bring more students to your institution.” Similar to other administrators interviewed for this study, Terry, an Associate Dean at Laminate State University, claimed that “quality of instruction is the primary cost” and additional revenue generated from online programs is “really important in order to maintain that quality.”  

Donald, who serves as an Associate Provost, pointed out that higher tuition is not the solution for online programs. “What you don’t want to happen is for people to say, ‘Why are you charging so much? You’re gouging students.’” James also suggested that online education poses an

interesting ethical question of how you think about money in higher education. You have to generate some net revenues, but you don’t want to generate too much to the extent that focusing so much on revenue will negatively impact quality.

In addition, nearly all participants discussed issues associated with offering online education at a larger scale due to the potential for adverse effects on the quality of the course.

Data-Driven Decisions

Several participants, particularly administrators, referenced the importance of leveraging available data before launching a given online program. Barbara referenced the importance of looking at labor market data before choosing to undertake an additional online program:

We look for programs that will have a 10–12 year shelf life. If we get into a graduate degree, it’s typically three to five years to recover our costs. For an undergraduate program, it could take . . . 7–10 years before we’re paid back for our investment we would make in creating the courses and building the program. We have to be careful that majors we choose aren’t narrow. That’s not financially sustainable.

Donald also referenced data-driven decisions when talking about the importance of labor market outcomes when considering which programs to offer online, referencing “strategic enrollment management” and the goal of “gainful employment” throughout the state before targeting which programs to launch online.


The impact of online education on the changing faculty role in higher education was a recurring theme for participants in the study, noting (a) the reluctance of faculty to embrace online education, (b) the unbundling of the faculty role, and (c) the extent to which online education breeds adjunctification.

Faculty Reluctance to Embrace Online Education

Participants described online education as a medium of instruction that has faced significant skepticism from faculty at their institution. Frank claimed that tenure-track faculty have “a concern that their incentive system and reward system won’t be there to recognize [online education] from a tenure perspective.” Several administrators acknowledged that developing online content and responding to online students may decrease the likelihood of obtaining tenure. James suggested that developing online courses may also be a poor use of a tenured faculty member’s time because it would “divert attention” from responsibilities factored more heavily during the promotion process.

Donald appeared skeptical of faculty who are hesitant to embrace online education. He stated that

During the summer, we don’t offer face-to-face courses. They’re all online. So it always kind of blows me away when faculty say that [online education] is “not any good” or “we’re threatened.” But it’s like, in the summertime, it sure works for you.

Charles, a Vice President, described his interactions with tenured or tenure-track faculty as “frustrating” because “professors can hold 10 different competing theories, but when it comes to technology, it’s black or white.” Although faculty suggested that developing online courses and teaching online may not be in their best interest, Derek offered an alternative approach to the reward structure in place in higher education:

Online [education] is the only new source of revenue [faculty] have. So if they want their teaching assistants, they want their graduate assistants, they want their PhD candidates who don’t have to pay full freight, and they want all the goodies of being a faculty member . . . the old model of the faculty member who teaches eight doctoral students doesn’t work anymore financially.

The Unbundling of the Faculty Role

Faculty members and instructional designers acknowledged the increasing importance of collaboration on the instructional side of online education. Bill, an instructional designer at the University of Granite, labeled the partnership between instructional designers and faculty as an “interesting shift” for faculty who may not be accustomed to deferring to others for pedagogical decisions, adding that “faculty are experts in the content they’re teaching, not necessarily on learning.” James noted that “the person who develops the course can be different from the person who delivers the course, and that’s a gigantic change that alters the nature of faculty work.” Derek described the operational distinctions between what it means to be a scholar and an online instructor:

You don’t get the PhD after your name unless you’re a lone wolf. You have got to stand on your own two feet and create knowledge. We get rewarded in this business for standing on our own two feet . . . at the very heart of becoming who you are as a faculty member, as a scholar, it is a lonely business, but teaching and learning online is a team sport. And [it’s challenging] if you’re not into teaming, if you’re not into working with people and collaborating with people, and giving away your content and giving away your control.

Several administrators identified the unbundling of the faculty role as a positive development for faculty productivity. Donald claimed that technology “frees up faculty from the grunt work of instruction.” Charles added that faculty “could have a videographer, an analytics specialist who’s going to look at the data related to performance and how groups are interacting, and then you have the instructional designer,” noting that faculty can focus on teaching because “the other stuff is going to be taken care of.”

Online Education and Adjunctification

The term “adjunctification” was used repeatedly by participants as a way to describe the increasing reliance on adjunct or fixed-term instructors in lieu of tenure-track or tenured faculty. James suggested that most adjunct or fixed-term instructors at his institution taught online, while tenure-track and tenured faculty typically taught in a face-to-face setting:

There are two sets of faculty. One set of faculty teach face-to-face and the other set teaches online. If it turns out that those who teach face-to-face have greater credentials, there’s a symbolic importance to that, even if those credentials don’t necessarily reflect higher-quality instruction.

Frank, who also serves as the program coordinator of an online program, suggested that he would like to have more tenure-track or tenured faculty teaching online, but “nobody from the tenure-track or tenured faculty want to teach the online courses.”

Several participants noted that the reward structure of tenure-track and tenured faculty at research universities could help to explain reluctance by these faculty to commit to the development and delivery of online courses. Daryl, a tenure-track faculty member at Laminate State University, echoed those concerns:

I’m sure there is a long-term payoff for investing time on the front end [to online courses], but I’m just not looking that far down the road. My time, because I’m on the tenure track, is really important right now. Spending extra time this week that could pay off in two, three, four, or five semesters is difficult when you have to get these publications turned out in a quick fashion. . . . If I develop a course and a fixed-term [faculty member] comes in and teaches it, and I don’t get credit for that course in my [teaching] load in future semesters, then what’s the point? Why would I do that? I don’t get tenure by being a great online course developer.

Tim, who spoke about his experiences as a former university president, claimed that the growing “trend of adjunct faculty will continue,” adding that “the research university model of the lifetime contract . . . is not [financially] sustainable for most campuses in the 21st century. Those are fighting words, but I think they’re directionally correct.”


A category of data that continually appeared in interviews was the intentional focus on students’ experience and learning in online courses. Participants described the importance of student interaction with each other and faculty as fundamental to student success and retention. In addition, they noted the importance of a practical degree that both aligned with what students were looking for in a degree and also helped students easily transition into a professional setting. Finally, there was a concentration on the shift in online education from instructor-centric to student-centered pedagogies. This category offers direction regarding how to use resources most effectively to instruct online students and ultimately sustain online programs.

Student Experience

Most participants discussed the importance of student engagement to ensure a quality online course experience. One approach to achieve this is to maintain smaller class sizes in order to be able to implement high-contact activities, such as in-depth discussions and peer-review sessions. The continual integration of student-to-student discussion was a common topic outlined as one way to create a high-quality online course, as peer-to-peer engagement, which can be taken for granted in the face-to-face setting, must be designed for online students. Student engagement thereby becomes an intentional and observable component of the online course rather than a foregone conclusion of the educational process. Several administrators noted that student engagement is a strong predictor of retention among online programs and should be a critical goal in developing any online course or exclusively online program.

A Practical Education

Several instructional designers, faculty members, and administrators who participated in this study referenced the importance of leveraging online education to provide students with the knowledge and skills needed in the workplace. Bill noted the success of career-oriented online programs, such as nursing, business, and engineering, and suggested that “the activities [students] do in their courses should give a direct reflection of what they can do in their jobs, or will do in their jobs, as they move further into the field.” Administrators contended that online programs should only be developed after considering the needs and job prospects of their students. Donald suggested that “we want to get a better sense of what it is they’re looking for and we want to create the right programs,” with a particular focus on the likelihood of employment after graduation.

From Instruction Centered to Learning Centered

The participants discussed student-centered learning as a shift away from a “sage on stage” approach toward a student-centered model of instruction. Tara, who is the Director of the Teaching and Learning Center at Laminate State University, compared this pedagogical shift to “hiding the broccoli,” as instructional designers work with faculty members to prioritize active and student-centered learning without explicitly telling them to do so. This shifting dynamic is also evident in the previous two categories that display a focus on developing a high-quality and useful education for students. Tim explained that “the paradigm is moving away from what the university provides by way of faculty credentials and facilities and library materials to the questions of what are students actually learning and what are they able to do.” Christopher, a fixed-term faculty member, described his teaching method for online courses as a collaborative effort in which the faculty member is the content expert and the instructional designer is the expert in matters related to online pedagogy.

The emergent conceptual model from this study (see Figure 1) represents a dynamic process that shows how universities can navigate financial and quality concerns related to the provision of online education. Figure 1 depicts the decision-making process when offering online education, places quality concerns at the center of that process, and identifies actionable goals for institutions seeking to increase net revenue without sacrificing the quality of their academic programs.

Figure 1. Model of quality-driven decision-making in online education



This study examines how to offer online education in higher education from the perspective of multiple levels of higher education personnel. Previous studies of online education in higher education typically examine the quality or costs of online education independently without seriously considering how one may influence the other (Bowen, 2013; Cheslock et al., 2016). We add to this growing body of literature by exploring how to navigate both quality and financial considerations pertaining to the development and delivery of online courses and exclusively online programs. In doing so, we use the concept of cost–benefit analysis (Drèze & Stern, 1987) as a lens through which to view our findings and better understand the decision-making process when pursuing efficiency and excellence in online education. Findings from this study affirm previous claims that online education “offers the promise of new student markets, increased tuition revenues, revenues from educational products, and enhanced efficiencies in the delivery of education services” (Slaughter & Rhoades, 2004, p. 317). However, this study goes beyond financial motivations to offer online courses and provides a more nuanced look at the notion of quality in online education and the mechanisms associated with balancing financial and quality considerations when offering online education in higher education.

The central finding of this study concentrates on the importance and pursuit of quality in online education. Although participants’ definitions of quality appeared to vary according to their professional role, there was a relative consensus that the commitment to quality works in conjunction, rather than in opposition, with financial motivations. Online education requires administrators to provide substantial financial investments to develop online courses and exclusively online programs; however, net revenues generated through online education may not be available until after several iterations of the online offerings. To recoup this upfront investment, administrators described some common institutional practices, such as the use of labor market research to ensure the longevity of the online program to be offered. In addition, the unbundling of the faculty role has allowed universities to leverage the expertise of various types of personnel when developing and delivering online education, with research-based faculty contributing to the content of courses, instructional designers offering expertise in online pedagogy, and teaching-oriented faculty delivering the course content.

Although the cost structure of online education is associated with economies of scale and suggests that the financial advantage of online instruction will be most prevalent at extremely large enrollment levels (Cheslock et al., 2016), high enrollment numbers may come at the expense of quality and student-centered pedagogies. Participants in this study repeatedly referenced the importance of not losing the student perspective when establishing proxies for quality in online education, noting that a highly engaging, student-centered experience can be used as a marketable commodity. In sum, our findings appear to show a strategic shift from instructor-centric to student-centered pedagogy, as a highly engaging student experience has been identified as critical to high-quality online learning (Blackmon & Major, 2012).


Many universities have developed online courses and exclusively online programs as a method to generate revenue (Cheslock et al., 2016), but the proliferation of online programs has created an increasingly competitive environment for colleges and universities to navigate (Angolia & Pagliari, 2016). The process associated with navigating quality and financial considerations when offering online education was categorized and arranged in our novel conceptual model, the Model of Quality-Driven Decision-Making in Online Education. As online enrollment numbers have shifted from for-profit institutions to not-for-profit institutions in recent years (Allen & Seaman, 2017), research universities have emerged as national leaders in online education, placing a greater focus on the quality of online instruction and online students’ academic outcomes. The Model of Quality-Driven Decision-Making in Online Education shows the transition from financial motivations to quality considerations within the left side of Figure 1.

The central component of the Model of Quality-Driven Decision-Making in Online Education concentrates on quality considerations in developing and offering online courses and exclusively online programs. For research universities seeking to enhance revenue and increase enrollment through online education, our conceptual model suggests that a high-quality experience serves as the bridge through which decisions flow. Unlike the for-profit model of online education that invests more of its revenue on marketing and profit distributions than instruction (United States Senate, 2012), research universities appear to place a greater financial and strategic emphasis on high-quality instruction. This core tenet of our emergent conceptual model, “Concern for Quality,” was reflected not only in our first and primary theme that seeks to define quality in online education, but also in our fourth theme that focuses on students’ experiences and learning outcomes in online courses and exclusively online programs. In placing that emphasis, the research universities in this study make quality-driven decisions to invest heavily in the quality of online education through elite faculty, instructional design experts, cutting-edge software, third-party assessment programs, and additional investments that may not be recouped for multiple years. As several participants noted, these initial investments in quality allow their research universities to differentiate their online courses and exclusively online programs from alternative options, leading to higher enrollment numbers and a more robust revenue stream.

By reinvesting additional revenue generated from online offerings into the quality of their online education, these research universities are able to create the virtuous cycle depicted on the right side of Figure 1. This continual reinvestment of revenue into quality runs counter to the for-profit model described earlier and provides the capital required to maintain the level of quality that allows online leaders to continue to distinguish themselves in a crowded marketplace for prospective online students. The Model of Quality-Driven Decision-Making in Online Education reflects assertions from faculty, instructional designers, and administrators suggesting that revenue and quality considerations should work in concert, and not opposition, with each other when offering online courses and exclusively online programs.


The Model of Quality-Driven Decision-Making in Online Education offers insight to researchers and practitioners seeking to better understand how to navigate financial and quality considerations related to the provision of online education in higher education. As noted previously, research failing to account for both financial and quality considerations offers limited value to administrators aiming to generate additional revenue through online education without unduly harming the quality of teaching and learning (Cheslock et al., 2016). Our novel conceptual model suggests that harmony between financial and quality considerations can only be achieved when administrators are willing to invest (and reinvest) in the development and delivery of online education. The initial decision regarding whether to develop an online course or exclusively online program should be rooted in the understanding that high-quality online education is a long-term investment and not merely a short-term mechanism to cut costs or increase revenues. Because the business model of online education only makes financial sense after the individual online course has been offered numerous times, the Model of Quality-Driven Decision-Making in Online Education provides the order of operations for ensuring the longevity and financial viability of online courses and exclusively online programs.

Another practical implication drawn from this study relates to the need to prioritize student-centered learning in online education. The importance of a positive student experience was repeatedly identified by our participants as an important criterion for achieving a high retention rate. Administrators, in particular, noted that retention is not only important for ensuring students’ academic success, but also the financial stability of their online offerings, as the reputation (and potentially the performance-based funding) of the university is tied to its ability to retain and graduate students. To prioritize the student experience, online courses can integrate frequent contact points between students and the instructor to give students a sense of belonging and academic support. Our findings suggest that online courses and exclusively online programs should not enroll extremely large numbers of students to achieve economies of scale to the extent that students have very little communication or interactions with the instructor. Every level of personnel included in this study referenced the need for enrollment caps in online education to ensure that faculty can guide online students in a more personable manner, leading to a high-quality and interactive student experience.

Further research can examine financial and quality considerations related to the provision of online education across additional institutional contexts, including those outside of the United States. Although this qualitative study is not generalizable and focuses solely on practices of highly regarded online programs at research universities, several institution types may be able to gain insight from the core takeaways of the identified strategies. Further study can also examine whether instructor type impacts the quality of online courses, as several participants noted that tenure-track and tenured faculty were less likely to serve as instructors for online courses than their fixed-term peers. Finally, future researchers can empirically test the novel conceptual model depicted in Figure 1 by examining whether these investments and reinvestments in online education actually improve the quality of online courses and exclusively online programs.


Allen, E., & Seaman, J. (2014). Grade change: Tracking online education in the United States. Newburyport, MA: The Sloan Consortium.

Allen, E., & Seaman, J. (2017). Digital learning compass: Distance education enrollment report 2017. Babson Park, MA: Babson Survey Research Group.

Allen, E., Seaman, J., Lederman, D., & Jaschik, S. (2012). Conflicted: Faculty and online education. Inside Higher Ed, Babson Survey Research Group, and Quahog Research Group, LLC.

Angolia, M. G., & Pagliari, L. R. (2016). Factors for successful evolution and sustainability of quality distance education. Online Journal of Distance Learning Administration, 19(3), n3.

Ary, E., & Brune, C. (2011). A comparison of student learning outcomes in traditional and online personal finance courses. MERLOT Journal of Online Learning and Teaching, 7(4), 465–474.

Blackmon, S. J., & Major, C. (2012). Student experiences in online courses: A qualitative research synthesis. Quarterly Review of Distance Education, 13(2), 77–85.

Belkin, D. (2013). US private colleges face enrollment decline. The Wall Street Journal, 11(11).

Bowen, W. (2013). Higher education in the digital age. Princeton, NJ: Princeton University Press.

Bowen, W. G., Chingos, M. M., Lack, K. A., & Nygren, T. I. (2012). Interactive learning online at public universities: Evidence from randomized trials. Ithaka S+R, 22.

Carter, N., Bryant-Lukosius, D., DiCenso, A., Blythe, J., & Neville, A. J. (2014). The use of triangulation in qualitative research. Oncology Nursing Forum, 41(5), 545–547.

Cellini, S. R., & Kee, J. E. (2010). Cost-effectiveness and cost–benefit analysis. In J. S. Wholey, H. P. Hatry, & K. E. Newcomer (Eds.), Handbook of Practical Program Evaluation (3rd ed., 493–530). San Francisco, CA: Jossey-Bass.

Charmaz, K. (2006). Constructing grounded theory: A practical guide through qualitative analysis. London, UK: Sage.

Cheslock, J., & Gianneschi, M. (2008). Replacing state appropriations with alternative revenue sources: The case of voluntary support. Journal of Higher Education, 79(2), 208–229.

Cheslock, J., Ortagus, J., Umbricht, M., & Wymore, J. (2016). The cost of producing higher education: An exploration of theory, evidence, and institutional policy. In J. Smart (Ed.), Higher Education: Handbook of Theory and Research (Vol. 31, 349-392). Dordrecht, Netherlands: Springer.

Creswell, J. W. (2012). Qualitative inquiry and research design: Choosing among five approaches. Thousand Oaks, CA: Sage.

Crotty, M. (1998). The foundations of social research: Meaning and perspective in the research process. Thousand Oaks, CA: Sage.

Drèze, J., & Stern, N. (1987). The theory of cost-benefit analysis. In A. Auerbach & M. Feldstein (Eds.), Handbook of public economics (Vol. 2, 909–989). Amsterdam, Netherlands: Elsevier.

Daymont, T., & Blau, G. (2008). Student performance in online and traditional sections of an undergraduate management course. Journal of Behavioral and Applied Management, 9(3), 275.

Driscoll, A., Jicha, K., Hunt, A., Tichavsky, L., & Thompson, G. (2012). Can online courses deliver in-class results? A comparison of student performance and satisfaction in an online versus a face-to-face introductory sociology course. Teaching Sociology, 40(4), 312–331.

Figlio, D., Rush, M., & Lu, Y. (2013). Is it live or is it internet? Experimental estimates of the effects of online instruction on student learning. Journal of Labor Economics, 31(4), 763–784.

Golafshani, N. (2003). Understanding reliability and validity in qualitative research. The Qualitative Report8(4), 597–606.

Guba, E. G., & Lincoln, Y. S. (1989). Fourth generation evaluation. Newbury Park, CA: Sage.

Immerwahr, J., Johnson, J., & Gasbarra, P. (2008). The iron triangle: College presidents talk about costs, access, and quality. San Jose, CA: The National Center for Public Policy and Higher Education.

Jaquette, O., & Curs, B. (2015). Creating the out-of-state university: Do public universities increase nonresident freshman enrollment in response to declining state appropriations? Research in Higher Education, 56(6), 535–565.

Lack, K. (2013). Current status of research on online learning in postsecondary education. New York, NY: Ithaka S-R.

Lewis, J., & Harrison, M. (2012). Online delivery as a course adjunct promotes active learning and student success. Teaching of Psychology, 39(1), 72–76.

Lincoln, Y. S., & Guba, E. G. (1986). But is it rigorous? Trustworthiness and authenticity in naturalistic evaluation. New Directions for Program Evaluation, 30, 73–84.

McPherson, M. S., & Bacow, L. S. (2015). Online higher education: Beyond the hype cycle. The Journal of Economic Perspectives, 29(4), 135–153.

Means, B., Toyama, Y., Murphy, R., & Baki, M. (2013). The effectiveness of online and blended learning: A meta-analysis of the empirical literature. Teachers College Record, 115, 1–47.

Mentzer, G., Cryan, J., & Teclehaimanot, B. (2007). Two peas in a pod? A comparison of face-to-face and web-based classrooms. Journal of Technology and Teacher Education, 15(2), 233–246.

Merriam, S. B. (1998). Qualitative research and case study applications in education: Revised and expanded from case study research in education. San Francisco, CA: Jossey-Bass.

Merriam, S. B., & Tisdell, E. J. (2016). Qualitative research: A guide to design and implementation. San Francisco, CA: Jossey-Bass.

Meyer, K. A. (2006). Cost-efficiencies of online learning. ASHE Higher Education Report Series, 32(1), 1-123.


Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook. Thousand Oaks, CA: Sage.

Miller, B. (2010). The course of innovation: Using technology to transform higher education. Education Sector Reports. Retrieved from http://www.educationsector.org/usr_doc/NCAT-Report_RELEASE.pdf

Morris, D. (2008). Economies of scale and scope in e-learning. Studies in Higher Education, 33(3), 331–343.

Morse, J. M. (2010). Sampling in grounded theory. In A. Bryant & K. Charman (Eds.), The SAGE handbook of grounded theory (pp. 229–244). Thousand Oaks, CA: Sage.

Ortagus, J. (2017). From the periphery to prominence: An examination of the changing profile of

online students in American higher education. The Internet and Higher Education, 32, 47–57.

Ortagus, J. (2018). National evidence of the impact of first-year online enrollment on postsecondary students’ long-term academic outcomes. Research in Higher Education, 59(4), 1035–1058.

Ortagus, J., & Yang, L. (2017). An examination of the influence of decreases in state appropriations on online enrollment at public universities. Research in Higher Education, 59(7), 847–865.

Poirier, C., & Feldman, R. (2004). Teaching in cyberspace: Online versus traditional instruction using a waiting-list experimental design. Teaching of Psychology, 31(1), 59–62.

Sener, J. (2012). The seven futures of American education: Improving learning and teaching in a screen-captured world. North Charleston, SC: CreateSpace.

Shea, P., & Bidjerano, T. (2014). Does online learning impede degree completion? A national study of community college students. Computers & Education, 75, 103–111.

Shenton, A. K. (2004). Strategies for ensuring trustworthiness in qualitative research projects. Education for Information, 22(2), 63–75.

Slaughter, S., & Leslie, L. L. (1997). Academic capitalism: Politics, policies, and the entrepreneurial university. Baltimore, MD: Johns Hopkins University Press.

Slaughter, S., & Rhoades, G. (2004). Academic capitalism and the new economy: Markets, state, and higher education. Baltimore, MD: The Johns Hopkins University Press.

Stake, R. E. (2010). Qualitative research: Studying how things work. New York, NY: Guilford Press. United States Senate. (2012). For-profit higher education: The failure to safeguard the federal investment and ensure student success. U.S. Senate, Health, Education, Labor and Pensions Committee.

Wagner, S. C., Garippo, S. J., & Lovaas, P. (2011). A longitudinal comparison of online versus traditional instruction. MERLOT Journal of Online Learning and Teaching, 7(1), 68-73.

Xu, D., & Jaggars, S. (2011). Does course delivery format matter? Evaluating the effects of online learning in a state community college system using instrumental variable approach. New York, NY: Community College Research Center, Teachers College, Columbia University.

Xu, D., & Jaggars, S. (2013). Adaptability to online learning: Differences across types of students and academic subject areas. New York, NY: Community College Research Center, Teachers College, Columbia University.



Sample Interview Questions

1. How did you become so involved with online education? What was your career pathway?

2. What would you say are the most important characteristics of a high-quality online course?

3. What are some actionable ways to cut costs or boost revenue when offering online courses?

4. How can universities balance quality and financial considerations when offering online education?

Sample Follow-Up Questions

1. Can you talk further about why faculty buy-in is so critical to offering high-quality online courses?

2. How do you respond to the critics you referenced who may view online courses as inferior to face-to-face courses? What can you do to change that narrative?

3. You mentioned that [your institution] operates like a business at times. Can you explain what you mean by that?

4. I want to go back to what you said about your desire to deliver a “profitable” online program without sacrificing quality. What does this look like in practice? Can you offer a few examples?



Raw Interview Data:

We operate within the parameters of the university. Our [online] programs are the same programs as on campus. They go through the same approval process through faculty senate or the graduate school; however, our orientation to how we pick programs to develop is totally different. We start with a focus on the adult learner and market data to determine which programs the adult learner would want and what would prepare him or her for sustainable careers in the future. We’re interested in programs that will lead our students to good jobs. We’re very careful to pick degree programs that are in growth areas. We look very closely at the Bureau of Labor Statistics before we agree to put a degree online. We’re looking at the potential for a person who earns this degree to get a job and move up the career ladder.

Open Codes:

Market-driven, learner-focused, comparison to face-to-face, data-driven decisions, student demand, labor market outcomes

Raw Interview Data:

The definition of quality varies quite a bit from context to context. It’s hard to even agree upon what we mean conceptually when we say quality. Once you come to that conceptual agreement, you end up having no trouble in terms of measurement. Is it in terms of getting your money’s worth because you’ve realized these learning objectives or because you felt or perceived it to be good or because you’ve reached outcomes in terms of professional advancement? Those are three very different things. That’s where prestige and brand come in. Prestige helps number three even if number one or two aren’t really there. That’s how higher education has historically operated. If you have the brand, that can cover up deficiencies on the instructional side.

What do I mean by quality? To be honest, in the short run, there’s a focus on making sure students perceive that they’re getting their money’s worth. If you get negative feedback, it’s based on students’ perceptions.

Open Codes:

Varying definitions of quality, metrics for quality, perceptions of quality, power of prestige, student-centered decision-making



Open Codes

Axial Codes

Selective Codes

Accreditation as quality definition

Quality control

Rankings as quality

Data metrics for a quality standard/standardizing quality

External measurements of quality

Quality Matters as quality metric

Outside metrics

Quality comparison and metrics

Quality established through research and data

Data on student learning—pathway to quality

Quantitative data factor into branding

Data metrics for a quality standard/standardizing quality

Extra quality control measures for online education

Metrics for quality

Data-driven definition

Quality Matters as quality metric

Data-driven metrics

Equality of programs

Equality of rigor standards

Modeling face-to-face experience

Brand/equality of brand

Learning outcomes as quality/comparison to face-to-face

Equality of skills

More rigorous than face-to-face

Comparison to face-to-face model

Fundamentals of teaching and quality remain the same—equitable

Quality could be façade in face-to-face

Quality comparison

Less clear definition in face-to-face

Comparison of online and face-to-face education

Small class size as quality measure

Student interaction as quality measure

Large class sizes harm quality of  curriculum

Student–instructor interaction

More activity equated to harder course

Learning “experience” is true quality of course

Student-centered decision making

Student engagement as quality

Student experience

Measuring quality indicators

Faculty as quality

Faculty/instructor as quality

Tenure-track as quality

Tenure-track as quality control

Experts required for quality control

Academic department equals quality control

Quality comes with instructor experience


Student outcomes as quality

Learning outcomes as quality/comparison to face-to-face


Data on student learning—pathway to quality

Student interaction as quality measure

Quality focused on product of course and student learning, not on faculty title

Rigor of expectations as quality

Online as more rigorous

Student learning

Planning is key

Quality rests in design

Pedagogy fundamentals as quality measures

Pedagogy/theory basis of quality

Quality needs good material and instructor



Importance of brand/power of prestige

Institutional brand

Brand perception equals quality, especially when definition is unclear

Quantitative data factor into branding

Lean on brand and quality of institution

Perceptions of quality

Institutional brand equals quality perception

Institutional brand in place of quality

Brand in place of understanding quality

Brand vs. quality

Brand vs. quality perception vs. reality


Intangible factor of quality

Quality that can’t be measured

Rankings don’t adequately reflect quality

Online courses create limitations on quality—regardless of class size

Student perspective of quality

Faculty view of quality

Departmental view of quality—data driven

Quality is variable

Quality remains undefined in full

Quality defined through perspective

Comparison of quality not appropriate

Still in search of quality

Varying definitions of quality

Tenure-track doesn’t necessarily mean quality

Brand perception equals quality, especially when definition is unclear

Perspective determines quality

Possible metrics of quality

Perception over reality

Symbolic value relates to perception of quality

Ambiguous/undefined quality

Perspective-bound quality

Cite This Article as: Teachers College Record Volume 122 Number 2, 2020, p. 1-32
https://www.tcrecord.org ID Number: 23025, Date Accessed: 5/19/2022 5:30:55 AM

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About the Author
  • Justin Ortagus
    University of Florida
    E-mail Author
    JUSTIN C. ORTAGUS is an Assistant Professor of Higher Education Administration & Policy and Director of the Institute of Higher Education at the University of Florida. His research typically examines the growing impact of online education and technology, the role and influence of community colleges, and the effects of various state policies on the opportunities and outcomes of historically underrepresented students.
  • R. Tyler Derreth
    John Hopkins University
    E-mail Author
    R. TYLER DERRETH is the Associate Director of SOURCE at Johns Hopkins University and a faculty member at The Johns Hopkins Bloomberg School of Public Health. His research examines critical teaching and learning practices, university–community partnerships, and educational equity.
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