What Students Value Most: A Qualitative Examination of Learner Experiences in a Fully Online Degree Program

by Lam D. Pham, Gage F. Matthews & Xiu Cravens - 2022

Background: Enrollment in online degree programs has grown rapidly in U.S. higher education institutions, but much of the research on online learning draws from student experiences in a singular online course. Student experiences in fully online programs likely differ from the experience of taking a one-off online class, especially as students become more familiar with online learning after multiple courses. Yet, research examining student experiences in fully online programs remains sparse.

Objective: In this exploratory and theory-building study, we examine student experiences after they have taken multiple courses in a fully online degree program. Relying on the perspective of students, our goal is to better understand what elements of fully online learning programs are most valued by learners.

Setting: We examine a fully online EdD program in leadership and learning at a private university in the United States. The program includes a series of courses that all include both asynchronous (e.g., readings and lecture videos) and synchronous activities. For synchronous sessions, students log in with their computers every week using teleconferencing software that allows them to interact with the instructor and with classmates in real time.

Research Design: We qualitatively analyze student interview data. We employ the How People Learn Framework to guide our analysis and extend our understanding of two of its key learning-environment dimensions: the learner-centered and community-centered dimensions. We purposively sampled 31 students for the semistructured interviews. To analyze interview transcripts, we used a grounded theory approach that began with line-by-line codes that we aggregated into categorical tags that were used to support the emergent themes.

Results: We find that students value four learner-centered program characteristics (diversity, authenticity, safety, and individuality) and five community-centered program structures (facilitating peer-to-peer interactions, establishing norms and expectations, differentiating for learning preferences, explaining the strengths and limitations of technology, and supporting student-driven initiatives).

Conclusions: We discuss cognitive tensions in students’ self-reported perceptions of their experiences and highlight the need for future research to examine how online learning programs can be better structured to support students in diverse and inclusive learning communities.

INTRODUCTION AND CONTRIBUTION

Online education has grown rapidly over the last two decades, and the COVID-19 pandemic has further propelled online learning into an international spotlight (Martin et al., 2020). In higher education, enrollment in online courses has grown even though overall enrollment has declined (Allen & Seaman, 2013, 2017). For example, in 200304, 15.6% of degree-seeking U.S. undergraduate students enrolled in at least one online course; by 201516, that number had grown to 43.1% (Snyder et al., 2019). Likewise, the proportion of undergraduates enrolled online for their entire degree program grew from 4.9% in 200304 to 10.8% in 201516 (Snyder et al., 2019). The COVID-19 pandemic created a seismic shift for colleges to move classes online starting in spring 2020. With such a shift happening in many parts of the globe and becoming more accepted given ongoing public health concerns, some are wondering whether the adoption of online learning will persist and how such a shift would impact the worldwide education market and, more importantly, how we teach and learn.

As online learning has grown, so has the research examining online instructional strategies (Davis et al., 2018), quality (Esfijani, 2018), and student engagement in both synchronous (Martin et al., 2017) and asynchronous (Garrison et al., 1999, 2010) modalities. Yet, impact evaluations of online learning are mixed. Some researchers find that students perform worse in online compared to face-to-face courses (Bettinger et al., 2017; Figlio et al., 2013; Jaggars & Xu, 2016), but some find positive effects on postsecondary persistence and attainment (Ortagus, 2018; Shea & Bidjerano, 2014). Despite mixed evidence, advocates support online learning as a cost-effective way to increase access in higher education (Shea & Bidjerano, 2014). Therefore, a rich literature has examined the design of online environments, focusing on frameworks, teaching strategies, and instructional planning (Garrison & Vaughan, 2008; Graham et al., 2001; Martin & Bolliger, 2018; Moore, 1989). However, most of this literature focuses on student experiences in a single or short series of online courses within a face-to-face or blended degree program (e.g., Lee, 2014; Teng et al., 2012; Thormann & Fidalgo, 2014). Research examining student experiences in fully online programs remains thin but is important given the proliferation of online-only programs in higher education. Also, student experiences in singular online courses may differ from student experiences across multiple courses in a fully online program, and there is a need for research that probes these differences.

Our contribution to the online learning literature is twofold. First, we inductively examine student experiences within a fully online doctoral of education (EdD) program in leadership and learning that began in 201718 at a private research university in the United States. Targeting gaps in the literature around learner experiences in fully online programs, we ask: What program characteristics and structures do students value most from their learning experiences in a fully online program? Second, we use the learner-centered and community-centered dimensions of the How People Learn (HPL) framework (Bransford et al., 2000; Donovan et al., 1999) as an analytic lens to organize and interpret themes that emerged from the student-reported experiences. As a research-based framework capturing different dimensions of effective learning environments, HPL provides a theoretical foundation to validate our examination of a fully online learning environment. However, though widely used to inform face-to-face instruction, the theoretical application of HPL to online learning has been underresearched and its key dimensions less clearly defined. In this study, we provide a more nuanced and comprehensive understanding of two dimensions of the HPL framework that are particularly relevant to learner experiences in online environments. We ask: How well do student-valued program characteristics and structures align with and elucidate the learner-centered and community-centered dimensions of HPL in a fully online program?

Our approach to answering these research questions utilizes qualitative analysis of interview data. Our findings suggest that students highly value four learner-centered characteristics of online learning programs: diversity, authenticity, safety, and individuality. Moreover, five community-centered program structures stood out: facilitating peer-to-peer interactions, establishing norms and expectations, differentiating for learning preferences, explaining the strengths and limitations of technology, and supporting student-driven initiatives. At the intersection of these characteristics and structures, we find several enduring tensions in the way students report their experiences with the fully online program. For example, students posited that they formed relationships virtually with peers and instructors that equal their experience in face-to-face programs, but they simultaneously maintained that physical meetings are necessary for fully developing interpersonal trust. Students also commonly touted the advantages of online learning for bringing together professional and geographic diversity, but most did not recognize how some elements of the online environment detracted from inclusive conversations around racial diversity.

This study contributes to the development of online learning by illuminating student experiences in a fully online program as distinct from the experience of taking one-off online courses. Moreover, we contribute to the theoretical development of online learning by applying and expanding the HPL framework to fully online environments.

STUDY CONTEXT

We examine the first fully online EdD degree program in leadership and learning offered at a private U.S. university, which admitted its first cohort in 201718. As designed, most students in the program are mid-career professionals who work full-time while completing two courses per trimester (fall, spring, and summer) over three years. Each course includes asynchronous and synchronous components. Asynchronous assignments include watching prerecorded lectures, completing preassigned readings, posting messages on discussion forums, and working on assignments or exams as specified by individual instructors. Synchronous components include weekly virtual sessions featuring real-time interaction with classmates and instructors. For synchronous sessions, the program used Adobe Connect for the first year, but transitioned to Zoom in following years. Students could access similar audio and visual capabilities across the two platforms and see classmates and instructors through small windows on their computer, though any individual could turn off their camera or mute their microphone. Instructors can allow students to share their screen and can place subsets of students into separate breakout rooms. The synchronous sessions also feature a chatbox that allows for written messages to the full group or private messages to individuals. Finally, students can communicate via group and one-on-one text messaging applications (e.g., Slack, GroupMe, WhatsApp, and SMS) external to the formal program features. Both the synchronous and asynchronous components comprise common practices in online learning, suggesting that student experiences in this program will likely be generalizable to other fully online learning programs across the country.

As a cohort model, the program is designed so that students can take classes with the same group of people across all three years; however, to maintain class sizes of fewer than 12 students, multiple sections of each course are offered in each semester. Thus, students may attend classes with different members of their cohort depending on their selected sections. Adding to the virtual activities, the program includes two opportunities for students to be on campus for face-to-face weekend sessions. These on-campus immersion experiences occur at the end of the first year and during the final year of students enrollment in the program. The immersion experiences are cohort-specific, so students attend on-campus sessions with all members of their cohort.   

LITERATURE REVIEW

As online learning continues to expand across higher education institutions in the United States, researchers have examined the effects of online versus face-to-face learning environments (Ary & Brune, 2011; Bettinger et al., 2017; Daymont & Blau, 2008; Driscoll et al., 2012; Figlio et al., 2013; Fischer et al., 2020; Means et al., 2013; Ortagus, 2018; Shea & Bidjerano, 2014; Xu & Jaggars, 2013); however, findings remain inconclusive. For example, Figlio and colleagues (2013) randomly assigned students to online versus face-to-face sections of the same course and found that students in the face-to-face section performed better than students in the online section. Moreover, a recent study by Bettinger and colleagues (2017) found that students who took the online section of a course performed worse both in that course and in future courses, relative to students taking a face-to-face section. However, other researchers have found positive associations between online enrollment and student outcomes, such as a higher probability of attaining a postsecondary degree (Shea & Bidjerano, 2014) and a lower probability of dropping out of college (Ortagus, 2018).

Inconclusive results from the evaluation literature suggest that design, implementation, and context are important determinants of student outcomes in online environments. Following this logic, much of the research literature has focused on strategies to improve the design of and engagement in online environments (Garrison & Vaughan, 2008; Graham et al., 2001; Martin & Bolliger, 2018). A recent review of research on online learning found that over 50% of all studies in this area examined themes related to learner engagement and characteristics that predict positive outcomes, whereas themes related to the program-level institutional support for online students and instructors accounted for only about 5% of the literature (Martin et al., 2020).

Although research examining learner experiences in fully online programs remains scarce, some themes have emerged from studies of individual online courses that are part of a larger face-to-face or blended program. These studies have found that learners in online courses benefit from interacting with peers (Comer et al., 2014), forming collaborative communities (Garrison et al., 2010; Thormann & Fidalgo, 2014) that support authentic learning (Rowe, 2016), and utilizing informal communications tools (Kent, 2013). Moreover, research has found that learners who are driven by an individual sense of self-regulation (Artino Jr. & Stephens, 2009) and self-efficacy (Cho & Shen, 2013) tend to have more interactions with peers (Delen et al., 2014), report higher levels of communication and collaboration (Barnard et al., 2009), and have more positive outcomes (Glazer & Murphy, 2015). Research on learners in individual courses has also found that students positively rate synchronous learning technologies that provide greater flexibility and convenience (Galanek et al., 2018) but become frustrated when faced with discrepancies between online and more familiar face-to-face experiences (Wuensch et al., 2009). For example, Park and Bonk (2007) examined an online graduate course and found that learners valued the technology-facilitated interaction with diverse perspectives but were also challenged by network connection problems and technological complications.

Although common themes are emerging from research on learner experiences in individual online courses, these experiences may differ in a fully online degree program. For example, students in fully online programs may have different expectations for how they will engage in a learning community. Also, frustration with technological limitations may ameliorate over time as students become more accustomed to online learning environments. Thus, potential differences between learner experiences in a fully online program relative to single online courses motivate research that specifically examines program structures and characteristics that students value in their fully online experience.

Although the literature on online learning includes research conducted within fully online degree programs, there is insufficient research examining learner experiences in these programs. Existing research at the program level has focused on program design, including pedagogical philosophies (Kumar, 2014), integration of web tools (Parenti, 2013), and academic integrity (Wagner et al., 2016). Moreover, much of the program-level research has leaned heavily on the perceptions of program designers, leaders, and instructors (Aversa & MacCall, 2013) rather than student perspectives. In this paper, we contribute novel insights into student-reported experiences. By juxtaposing our findings with the current research on individual online courses, we add nuance to the research conversation about how students experience online learning.

THEORETICAL FRAMEWORK

The HPL framework integrates research on classroom teaching and learning using a social constructivist paradigm (Bransford et al., 2000). In academic settings, HPL posits that the development and retention of knowledge requires integrating new content with what one already knows. To gain expertise, novice learners need to adopt an organizational scheme for new information, but this organizational scheme can be idiosyncratic (i.e., applicable only in specific situations) because learners do not have the prior knowledge or know the necessary process to apply concepts to broader topics in a field. Instructors fluency in the material, on the other hand, can create challenges for learners by obscuring fundamental principles, strategies, and techniques that guide their problem solving. It is imperative, HPL states, that the thinking of both the instructor (expert) and the student (novice) are made visible during the teaching and learning experience. To effectively promote visible thinking, the HPL framework emphasizes four dimensions of effective learning environments: learner-centered, knowledge-centered, assessment-centered, and community-centered (Bransford et al., 2000; Donovan et al., 1999). Learner-centered environments highlight connecting with learners background and current knowledge; knowledge-centered environments focus on organizing new content; assessment-centered environments provide opportunities for regular feedback; and community-centered environments foster norms for learning together.

We consider the HPL framework as highly relevant to constructing effective online learning environments. Because the knowledge-centered and assessment-centered dimensions of HPL are more dependent on understanding instructors pedagogical strategies, and this study focuses on learner perceptions, we find the learner-centered and community-centered dimensions particularly instrumental in guiding our analysis of empirical findings and our interpretation of emergent themes. Furthermore, because HPL was developed from research in face-to-face settings, and assuming the process of making thinking visible in a virtual setting could be different from the process in face-to-face settings, applying this theoretical lens to a fully online environment also allows us to examine the extent to which HPL applies in a different modality.

METHODOLOGY

RECRUITMENT AND PARTICIPANT SAMPLE

We recruited students from the first three cohorts of the online Ed.D. program to participate in semistructured interviews during summer 2018 (Cohort 1), fall 2018 (Cohort 2), and spring 2019 (Cohort 3). We purposively sampled students from each cohort to maximize variation across student characteristics that we hypothesized would most likely affect students perceptions of online learning; that is, we invited a variety of students by gender, race, age, occupation, and comfort with technology to participate. Our interview sample comprised 10 students in cohort 1, 11 in cohort 2, and 10 in cohort 3.

To recruit, we invited students via email to participate in interviews during the first trimester of their second year in the program. At this point in the program, students had completed six courses and were enrolled in two more. We chose this point in the program to recruit participants because it allowed enough time for students to become familiar with typical course structures and program technology. We also chose this recruitment period because students could recall their experiences at the beginning of the program.

Table 1 shows demographic characteristics of each student in the sample. About 42% of participants identified as non-white, half were employed in the education sector, half identified as female, and 74% were older than 35. The variation in participant background characteristics suggests that we successfully recruited students with a broad range of perspectives.

Table 1. Descriptive Characteristics Interview Sample

Interview Participant	Gender	Race/Ethnicity	Age	Previous Education Level	Professional Sector
Ava	Female	White	3544 years		Higher Education
Hannah	Female	Asian/Pacific Islander	4554 years	Masters	Education
Luna	Female	Hispanic/Latinx	4554 years	Masters	Accounting
Hazel	Female	White	4554 years	Masters	Higher Education
Isaac	Male	White	3544 years	Masters	Education
Liam	Male	White	3544 years		Education
Parks	Male	Black	3544 years		Education
Owen	Male	White			Education
Lily	Female	Black	3544 years	Masters	Education
Asa	Male	White	3544 years	Masters	Education
Sarah	Male	White		Masters	Education
Drew	Male	White	3544 years	Masters	Nonprofit
Piper	Female	Black	2534 years	Masters	Education
Emma	Female	White	3544 years		Marketing
Leah	Female	White	2534 years	Masters	Education
Claire	Female	White	4554 years	Masters	Education
Clara	Female	White	3544 years	Masters	Higher Education
Milo	Male	White	2534 years	Masters	Education
Harry	Male	White	3544 years	Masters	Consulting
Ian	Male	Asian/Pacific Islander			Education
Mia	Female	Black			Education
Ella	Female	White	3544 years		Higher Education
Gray	Male	Asian/Pacific Islander	4554 years	Masters	Government
Madeline	Female	White	3544 years	Other	Education
Elliot	Male	White	4554 years	Masters	Healthcare Administration
Maya	Female	Black	3544 years	Masters
Tristan	Male	White	3544 years	Masters	Education
Anna	Female	Black	3544 years	Masters
Adam	Male	Black	3544 years	Masters
Eva	Female	Black	3544 years	Masters	Education
Luke	Male	Black		Masters

Note. Not all interview participants provided all demographic information. These cells are left blank on the table.

RESEARCHER POSITIONALITY

To better reflect on how our identities may have influenced the research process and outcomes, we identify and describe each authors positionality in relation to the subject matter, participants, and the research process (Holmes, 2020). The first author is an Asian American male who as a first-generation immigrant has had personal experience navigating higher-education environments where the customs are foreign to him. Before this project, he did not have any experience with online learning. His experience navigating higher education as an immigrant informed his thinking about how students acclimated to a new modality, and his inexperience with online learning meant that the experiences described by interviewees were novel to him. He served as a teaching assistant (TA) for one section of the online EdD program, taught by the third author, and observed classes taught by other instructors in the program. His TA role allowed him to directly observe some aspects of how students experienced the program, but his experiences were limited to the sections he observed. This meant that he met some but not all of the interview participants.

The second author is a current doctoral student who participated in all-online courses during the entirety of his first year in his current program. He is a white male from a rural area of the Midwest whose experience with graduate courses prior to his current program was entirely in person and in multiple formats; this experience served as a baseline of comparison for both his personal exposure to online learning and the novel insights of participants in this study. He was not directly involved in the EdD program centered in this study, which allowed him to view participants comments from an external perspective. However, because many instructors and students in the EdD program were white, his normative expectations of such graduate programs likely align with the dominant culture of the program. These cultural norms, along with unfamiliarity with the program, required self-monitoring and discussion with the other authors during the analysis process.

The third author is an Asian American female who came to the United States as an international graduate student; led workforce development initiatives in nonprofit and government sectors for refugees, dislocated workers, and out-of-school youth for more than a decade; and later joined academia. She was one of the faculty members who participated in the design of the online program and taught one section in each of the semesters attended by the sampled students. This study aligns well with her research interest in and advocacy for developing instructional strategies that address the needs of student populations who enter U.S. higher education institutions as outsiders, particularly international students, adult students working full time, and students from disadvantaged backgrounds.   

Two researchers positionality as instructors in the program produced both strengths and limitations for our research design. Because two of us were instructors in the program, we directly interacted with many of the interviewees, both online and in-person, over an extended time. These roles enriched our contextual understanding of the students perceptions and experiences. However, our position as instructors likely also influenced student responses during the interviews. Only the first author conducted the interviews, and as part of the interview process he was intentional about describing the project objectives and maintaining confidentiality. Some interview participants knew the authors from class, and those students appeared comfortable sharing their perspectives. Other interview participants did not personally know any of the authors but did know of our position as instructors in the program. Overall, we acknowledge that student responses were likely moderated by our positionality as instructors, but we also believe our relationships with students and in-depth familiarity with the program facilitated a richer understanding of student experiences.

DATA COLLECTION PROCEDURES AND MEASURES

A semistructured interview protocol was developed to collect students perceptions (Creswell & Poth, 2016). We developed the interview protocol based on our review of the literature on student experiences in online learning, as relevant to our project aims (see Appendix C). After writing initial questions, we tested multiple iterations of the interview protocol based on suggestions from a methods expert and cognitive interviews with a pilot sample of four students (Desimone & Le Floch, 2004). The protocol was designed to probe for students (1) experience with online learning, (2) expectations for online learning, (3) interactions and relationships with classmates, (4) methods of communication with cohort mates, and (5) general strengths and weaknesses of the online program. Although the protocol included probes to guide the discussion, we intentionally allowed student perspectives to drive the conversation and varied follow-up questions according to students responses. All interviews were conducted one-on-one, lasted between 30 and 75 minutes, and were audio-recorded. Field notes were taken during and immediately after each interview, and short memos were written throughout data collection to document emerging concepts, observations, and adjustments to the methodology. Audio recordings were transcribed verbatim and analyzed in MAXQDA18.

DATA ANALYSIS

We used constant comparative analysis within a grounded theory framework to analyze the interview data (Charmaz, 2014; Corbin & Strauss, 2014). Using constant comparative analysis meant that, with each additional interview, we simultaneously updated coding definitions and applied new codes to all previously coded transcripts as new themes emerged. We began with line-by-line codes in 9 of the 31 interview transcripts. This initial open coding approach allowed us to identify broad categories, concepts, and themes grounded in the data. Two coders simultaneously coded each of the initial nine interviews, meeting frequently to compare interpretations, discuss emergent themes, identify categorical tags for themes, and update the coding scheme and categorical tags based on evolving insights from each additional interview. As coders met to discuss categories that repeatedly emerged within the data, we also wrote analytic memos that noted discrepancies and decisions on how to resolve differences between coder interpretations.

After developing a coding scheme using nine interviews, two coders independently coded a second set of four interviews to determine interrater reliability. Through several additional iterations and discussions between coders, we reached an 87% agreement and k = 0.83 (Cohen, 1960). Then, having established a sufficiently high interrater reliability, two coders independently coded each of the remaining interviews. After coding all interviews, we cross checked our coding to identify any remaining disagreements for resolution through discussion among the three authors. Once discrepancies were resolved, we again reviewed our codes to summarize and synthesize them into categories and subcategories that were then used to identify themes across interviews. See Appendix A for our full coding scheme. Finally, we shared our emergent findings with interview participants as a member check to inform how well we captured and interpreted the perspectives of participating students. We incorporated participant comments into a final round of analysis. Guided by the HPL framework with a focus on student experiences, we then developed a two-dimensional analytical structure to sort the emergent themes and codes into learner-centered program characteristics and community-centered program structures.

RESULTS

In this section, we present findings organized under the two dimensions of interest within HPL: learner-centered environment and community-centered environment. For clarity, we use the term program characteristics for coding categories relevant to the learner-centered dimension and program structures for categories relevant to the community-centered dimension. Tags for the characteristics and structures are selected first from words directly used by the respondents and subsequently updated to fully capture each theme. Our qualitative results include detailed summaries of key themes and coding categories and are accompanied with quotes labeled with pseudonyms for each individual.

LEARNER-CENTERED PROGRAM CHARACTERISTICS

Four categories of codes consistently emerged as highly valued characteristics of a learner-centered online program: diversity, authenticity, safety, and individuality. These four characteristics align well with the HPL notion that learner-centered environments pay careful attention to the knowledge, skills, attitudes, and beliefs that learners bring to the educational setting (Bransford et al., 2000, p. 133). Note that these characteristics emerged from our empirical analysis and are not explicitly defined in the HPL framework.  

Diversity

This category refers to opportunities to regularly interact with classmates from different backgrounds with a wide range of professional experiences. Students highlighted access to geographically and professionally diverse viewpoints as a major benefit of the fully online program that would not be as rich in face-to-face or blended programs requiring students to be local. Lily described a sentiment shared by most interview participants by saying the program is helpful because I get to interact withyou know, we have a senator in the program; we have a city manager; we have a vice president of an organization. And you get to see the dynamics across other sectors, so I think that thats a huge benefit. Like Lily, multiple students repeatedly highlighted diverse perspectives as important to expanding their professional network and welcomed learning from cohort mates as much as they valued course content. Mia noted that learning occurs when Im afforded the opportunities based on being part of a learning community to view things or to analyze things in a different lens. Eva agreed, stating that youre acquiring new knowledge you did not have before, and some of that comes through the classroom space you share and some of it comes from outside and then being able to come together and collaborate and flesh out some of those ideas.

Although most students refer to diversity in terms of professional backgrounds and geography, a few discussed racial diversity. Sentiments around racial diversity primarily centered on a desire for instructors to address racially insensitive comments and to create a safe space for people from racially minoritized backgrounds to share their thoughts. For instance, Maya noted [t]he fact that we are in a white school, a predominantly white school, the program is predominantly white, taught by predominantly white people that have no clue about what its like to be a minority in learning or in anything. Although our data are limited to only some comments about racial diversity from a small number of participants, we believe these themes are noteworthy and discuss them to the extent that our data allow under the safety category, while also noting this as an important avenue for further investigation.

Authenticity

In contrast to professional and geographic diversity, which was seen as a natural strength of the online program, nearly all interview participants described authenticity as particularly difficult to establish, even with regular synchronous classes. By authenticity, we mean a learning context that supports honest and open communication. Students repeatedly emphasized a desire for conversations with classmates that would naturally occur before, after, and during breaks in a physical environment. Milo described his sentiments, I wish I could have the social experiences with them that werent about learning. I wish I could have more of the sidebar conversations. Those are the interactions I crave. Importantly, students did not express a desire for social meetings to become part of the official programming because it would no longer feel authentic. Some students believed planned social meetings would take away from time for coursework; some emphasized that the virtual format does not allow for small groups and pairs to organically form (i.e., mingling); and some felt that additional time in front of their computer would be an extra assignment rather than an opportunity for authentic connections.

Students also pointed out authenticity as a salient limitation of the program because the audio-video conferencing technology limits their ability to read nonverbal cues and presents a barrier to naturally taking turns in a discussion. Harry described this limitation:

Lets say the teacher asks a really thought-provoking kind of question that everybody wants to answer. Its kind of hard to manage that because everyones going to start talking at the same time, and thats kind of weird or awkward. So, that is one drawback. Whereas, I think if we were face-to-face, you could kind of read the nonverbals or youd see someones hand go up or youd see someone take a deep breath to start to speak, or something like that.

Part of the limited authenticity in the online environment is due to technology, which we describe below, but several students directly said that they felt less authenticity because they prefer in-person interaction, no matter how smoothly the technology could facilitate conversations.

Safety

The safety category refers to the value students placed on an inclusive culture that made them feel safe to share their thoughts. Although many students discussed a general desire for safe learning environments, a few (all of whom were people of color) also expressed the specific need to feel safe sharing racially minoritized perspectives and lived experiences. For example, Maya described her experience,

We talk a lot about learning and because were talking about learning, theres discussion about inequity. And it makes me feel uneasy because I dont feel that we all understand fully what inequities mean to each community. So, I dont feel safe in that community at all.

Maya was describing how she does not trust that her white classmates understand how racial inequities have affected her and others who share her racial background. For students like Maya, explicitly and inclusively discussing race was important to developing a sense of safety and trust in their classmates. Eva summed up this idea: Make sure all voices are heard. As a person of color, I want to know what my white peers are thinking and how they digest the information were reading.

Overall, students described safety as intrinsically related to authenticity because they felt they could not fully trust each other without authentically interacting. Furthermore, most students brought up the in-person immersion as crucial to increasing trust. For example, Drew said:

Meeting them in person, I got to know them on a more personal level that you cant really, even in the private chat, you cant really get to know somebody until youre in front of them and see their mannerisms and how tall they are, and you know. It is still different, I feel like.

Although students had interacted virtually for a year before the in-person immersion, they still highlighted the opportunity to have embodied interactions as a major leap forward in building trust and safety. A couple of students presented an alternative perspective, describing feeling more comfortable in the fully online program relative to physical spaces. Leah provided an example:

If I walk into a room and people are already sitting in groups, Im not one to just break into a group often. Even if its people that I know, if theyre already sitting in groups, and I dont know I belong to a group, I tend to sit by myself. That might be my lens looking at all this, but just the fact that I dont have to worry about that with online, that I just sign in and theres literally no order at all that the cameras are shown; its eliminating a huge social barrier for me.

Though this perspective was voiced by fewer students, their viewpoints suggest that there are ways to leverage the online environment in support of a more inclusive and safe learning environment.

Individuality

This category captures students desire for instructors and program coordinators to recognize that they have individual preferences and familiarity with learning online. Students consistently noted wanting instructors to appreciate that they are learning about virtual learning while also learning content. For example, Madeline described her experience by saying, I will say I had a little bit of a learning curve with the camera. Im not very comfortable on camera. Ive gotten better. That was definitely an adjustment. The HPL framework already emphasizes building on what students already know, but our finding suggests that this component of HPL should be expanded beyond content knowledge to include building on students pre-existing comfort with navigating virtual learning. Learning in an online program at a university primarily offering in-person classes also pushed students to highly value individualized support. Hazel articulated how she values individual attention from instructors, I keep thinking this is worth it because of this quality and this level of expertise and how they really did make me feel that I was just as important as one of their students on campus.

Additionally, students valued content that was applicable to their individual professional context. Claire, a college instructor, provided an example:

So some of this is not new to me, but the way Im thinking about it and experiencing it in this program is definitely impacting me in ways that I work with my students, in ways that Ive worked with committees, and in the ways I observe the culture at my institution. Its definitely providing me different lenses to think about whats going on here.

For Claire, the program provided new tools to approach her daily work. This element within individuality is related to students desire to expand their professional network as part of diversity. Within diversity, students valued new viewpoints from classmates that can help expand their professional horizons, whereas within individuality, students valued course content that applies to their specific professional setting.

COMMUNITY-CENTERED PROGRAM STRUCTURES

Five categories of codes emerged as salient program structures that support community-centered learning environments: facilitating peer-to-peer interactions, establishing norms, differentiating for learning preferences, explaining the strengths and limitations of technology, and supporting student-driven initiatives. The structures identified here are consistent with how HPL envisions community-centered environments that involve norms that encourage collaboration and learning (Bransford et al., 2000, p. 197). Although the need for such program structures is mentioned, note that the HPL framework does not currently describe how these structures help build community-centered learning environments for adult learners.

Facilitating peer-to-peer interactions

As the most commonly referenced category within community-centered program structures, students felt that the online program facilitated peer relationships because of its structure as a cohort model where they could take multiple classes with the same group of people. In fact, numerous students chose specific course sections so that they could be in class with the same members of their cohort every semester. Hannah described how she connected with specific people in the cohort:

Because you find the people, as we break up in discussion groups, and as you have the same people in your classes, class after class. I dont want to say you establish your clique, but you establish the people that you gravitate towards or that are interesting to you and you form these friendships. Of course, we might all collectively get along, but you see these groups forming of people that are a little bit closer than the rest.

The strength of peer relationships built within this cohort model even surprised several students. Emma, for example, said:

Were sort of surprisingly close considering that weve never met each other face to face. Like just today, Ive had three different people from my cohort, just today, have messaged to see how my kid was. I mean like theyre my friends, like theyve met my kid, and they never have.

Most students also brought up the on-campus immersion experience as an important way to encourage peer relationships. In addition to interacting physically and seeing body language, participants described the immersion as a social opportunity. Though it lasted only two days, students consistently pointed to social interactions over that weekend as a major strengthening of their relationship with peers. Asa described this experience:

The relationships became more personal, because even though, being on the phone call, and even seeing the video, you know those people, but it wasnt until after we all went to [campus], and we ate together. I hate to be so traditional, but the idea of fellowship, we sort of really became a cohort, so now were generally concerned about each other, but we also are more in-tuned to the particulars of each others experience.

Beyond the cohort model and immersion, some students expressed the importance of instructors and advisors motivating them to deliberately find learning partners. Drew described how he liked having an instructor who intentionally connected him with classmates, saying:

He partnered us up with a buddy to talk through our project. And I think creating opportunities to have a thought partner in those first few classes was really important because thats where I ended up bonding with people the most.

For these students, working with learning partners stood out as a way to form strong relationships, even without sharing a physical space. Forming partnerships across multiple courses also stood out as a way the learning experience in a fully online program differs from the experience in a singular online course.

Establishing norms

Another notable category of program structures is establishing norms. Norms were especially referenced when students described online features that were atypical or unavailable in face-to-face environments (e.g., chatboxes, private messaging during class, microphone and video control, and placement into virtual breakout rooms). Students used the same software in all classes, so they described developing a culture around how they used the technology, repeatedly noting that norms for using these online features could be set by instructors but often were not. They believed that instructors who were less familiar with teaching online were unsure of how they wanted students to use the various online features or unaware that they wanted to set certain norms. In the latter case, these instructors would reactively announce preferences along the way instead of clearly communicating norms at the beginning of class. For example, students often mentioned the class chatbox as a useful feature, but when norms were unclear, students usage of the chatbox sometimes became distracting and even inappropriate. The impact of unclear norms was especially important when students discussed how inappropriate comments in the chatbox made the online learning environment feel unsafe for people of color. Eva describes these experiences:

Sometimes Ive seen a student will just make jokes about something that I think is inappropriate. And a professor doesnt address it. And again, sometimes its those professors who just dont see it, because they dont keep up with the chat or professors who just kind of will chuckle at it or just ignore it. And that makes me feel very uncomfortable because I feel like if somebody were to say that thing out loud in an in-person class, then I wonder, if we were on campus, would that professor still ignore itact like that wasnt just said. Because sometimes people just carry out conversations in the chat that have nothing to do with class.

For Eva, unclear norms made her uncomfortable because her classmates could make inappropriate comments without any pushback from the instructor or other classmates.

Students also described wanting clear expectations for breakout activities and whole group discussions. Norms for breakout rooms were important as students progressed through the program because they were more distracted when given unclear tasks. Madeline described this issue when she said,

When I have sat in front of the computer for three hours solid, that last 30 minutes, Im not going to talk as much in a breakout and apply it without getting lost or sidetracked or someone else starting up a, What are you doing this weekend? conversation.

Whole group discussions could also benefit from clear expectations around how to take turns during the conversation. Though not all students wanted explicit turn-taking protocols, many felt that discussions were less natural in the virtual environment because the technology (i.e., clicking to unmute and difficulty getting the speakers attention) impeded an organic, back-and-forth exchange. Thus, some students believed a discussion protocol would help them prepare for who should speak next and keep exchanges moving forward without requiring the instructor to speak between each person to identify the next speaker.

Differentiating for learning preferences

Differentiating links directly with individuality and refers to efforts from program staff to meet the differing needs of individual learners. In contrast to traditional pedagogical approaches to differentiation in face-to-face environments, this category refers to students wanting differentiated support in navigating virtual learning environments. Lily described her experience, saying:

For digital natives, I dont think they would have even noticed any different. And I noticed that with the younger people in our cohort, they are able to interact in this digital world where these programs are almost like oxygen. Its just what they use, where I have to make an adjustment because Im a little older, I need a bridge to this learning.

Differentiating to meet individual levels of comfort with technology was commonly mentioned, especially by people who were unfamiliar with online learning.

Differentiation was also important as students adapted to multiple methods of communication that do not involve physically meeting. Differences in personal preferences for technology created a wide array of potential communication modalities, and students often described wanting flexibility around communicating with peers when completing assignments or studying together. Hannah, for example, discussed how she interacted with cohort mates:

Theres not a particular way. Some people like to text, so then I just text back and forth. Some people would just do emails. Some people, we do the group chats. And then, I guess, through the apps. And then some people, we dothey like the face-to-face more. And then some people, I actually just physically talk to them, on the phone.

Students also emphasized a desire for different ways of structuring synchronous sessions. For example, students wanted variation in breakout room assignments (e.g., sometimes grouping people with similar ability levels together and sometimes grouping people in similar occupations together) based on intended learning goals and individual affinity for small group work.

Explaining the strengths and limitations of technology

Students described myriad aspects of the technology that played a role in supporting or impeding their learning experience. The synchronous video platform placed all students on one visual plane and allowed students to see each others facial expressions, which helped with reading reactions, but the direct, constant video on everyones face also made some students self-conscious. The chatbox allowed students to participate without feeling forced to speak, but as described above, it also could be distracting, irrelevant, or inappropriate. Asynchronous forums were convenient ways to dialogue over an extended time but could also become busy work if the forum conversations were not integrated into synchronous discussions.

Several students discussed frustration with technological glitches, especially if they occur repeatedly and are the result of instructors who had not learned to use the technology. They emphasized training for both students and instructors on using the technology early in the program and particularly appreciated training from support staff. Hannah described her experience learning to use the technology: I was really nervous, and I tried to really inform myself, read the directions over and over, and had practice sessions with my support specialiststudent support. But once I learned that, I mean, it was really simple. For those who do not feel comfortable with the technology, students suggested that differentiated sessions early in the program to address their individual technology learning needs could quickly alleviate concerns and familiarize them with the operating procedures.

Another aspect of the technology that stood out as relevant to a community-centered learning environment involved helping students learn to use different methods of communication. Although many students emphasized the immersion, an equally large majority of students also felt that connecting with classmates through text messaging, phone calls, and synchronous meetings were important ways of building and maintaining relationships. In fact, some students felt that they communicated more regularly with classmates because the online program motivated them to intentionally connect using technology. Luna described this sentiment:

I think, in a physical class, it would be more like I was saying, youre done with class, and its early enough, Oh, let's go to the library and continue our discussion, or Lets go have some coffee and continue the discussion. So, I think that texting and reaching out takes the place of that in a way.

Supporting student-driven initiatives

Within this category, students described individual efforts to initiate and sustain relationships with their classmates. Some of these student-driven efforts include starting group chats, setting up weekly study sessions, and even organizing travel to meet in person. Importantly, these efforts created spaces where students could interact informally, without an instructor present. Supporting students efforts to create these spaces (rather than planning them as part of the program) meant they became more authentic. Leah described a common experience of reaching out to cohort mates via text, saying:

Were all in this together. Thats all you can see on the screen, and you probably dont even know if people are texting individually outside. I know I text people individually, and I have other group texts with classmates that arent in the same classes or arent all in that group text in my class. So, there is a sense you can form your own community, and everybody kind of has a chance because you can reach out to anyone.

Although many students shared Leahs feeling that student-initiated groups are generally open, a few students also noted that these groups tend to become cliques that some people were not invited to join. A few students also said that student-initiated efforts seem useful, especially synchronous study sessions, but that these groups were a challenge to join given existing personal responsibilities and the demands of coursework.

CONNECTING LEARNER-CENTERED CHARACTERISTICS AND COMMUNITY-CENTERED STRUCTURES

As we aggregated codes into the four learner-centered program characteristics and five community-centered program structures, we identified multiple ways that these structures and characteristics overlapped; that is, beyond generally supporting a community-centered environment, each of the five program structures were also associated with one or more of the learner-centered program characteristics. For example, Harry described how technology can support authentic interactions by saying, Ive still made a connection with a couple of individuals, and just text and email as opposed to seeing each other at the coffee shop. HPL predicts that the learner-centered and community-centered dimensions will overlap in the physical learning environment, so we explored how they overlap in our fully online setting by examining the number of instances, within the same unbroken segment of speech, where participants would simultaneously mention a learner-centered characteristic and a community-centered structure. Figure 1 shows the proportion of segments within each characteristic-by-structure cell where there is overlap, with darker colors representing more overlap and lighter colors representing less. We also include examples of segments with overlaps in Appendix B. Note that the overlaps in Figure 1 do not account for a positive or negative valence; for example, participants can describe instances where establishing norms can either support or hinder authentic interactions. Because we did not specifically ask learners about whether specific structures supported or impeded specific characteristics, we felt assigning valence to students comments would stretch our discussion beyond what our data would support, so we leave this question for future research.

Figure 1. Proportion Overlap Between Learner-Centered Program Characteristics and Community-Centered Program Structures

Note. Overlapping segments do not capture a negative or positive valence for how program structures supported or impeded valued characteristics.

Figure 1 depicts several areas where characteristics and structures showed particular overlap. Program structures that encourage greater differentiation overlapped most with diversity. Authenticity overlapped most with establishing peer-to-peer interactions, explaining technology, and supporting student-driven initiatives. Both safety and individuality overlapped most with establishing peer-to-peer relationships. Overall, our participants most often emphasized supporting peer-to-peer interactions as highly relevant to all the learner-centered characteristics they valued in an online learning environment. The multiple ways for program structures to either positively or negatively influence authentic interactions also suggest a strong desire for the online program to find ways of supporting authenticity. Areas where we see the lowest levels of overlap include supporting student-driven initiatives and access to diverse viewpoints. This low level of overlap could suggest that students valued diverse experiences and perspectives more in class sessions than in external communication. Somewhat surprisingly, establishing norms tended to have a low level of overlap with diversity and safety. That students are not connecting norms with these desired characteristics suggests the program, as currently designed, is not clearly communicating norms that directly target diversity and safety.

DISCUSSION

This paper contributes to the literature on online learning by focusing on student perspectives in a fully online program, which is distinct from previous work examining only single courses or relying only on the perspective of program leaders (Martin et al., 2020). We also make theoretical and empirical contributions by extending the application of HPL to online learning and identifying specific program characteristics and structures that are valued by adult learners. In the last chapter of Bransford and colleagues text (2000), the authors state that HPL urges future research to address how learning environments can be organized in ways that counteract societal stereotypes and tap diversity as a positive resource for learning (p. 277). This, however, is the only time that diversity is directly used in HPL to describe learners and their backgrounds. By delving into student perspectives and identifying diversity as a highly valued characteristic of a learner-centered program, we practice what HPL preaches and recognize the importance of building on the conceptual and cultural knowledge that students bring with them to the classroom (p. 134). In addition to diversity, we examined why and how adult students in online learning environments value authenticity, safety, and individuality. By identifying these specific program characteristics, we expand on HPLs original application, which looked more broadly at children and their need to connect with real-life experiences and cultural practices (p. 135). Further, by describing specific program structuresfacilitating peer-to-peer relationships, establishing norms, differentiating, explaining the strengths and limitations of technology, and supporting student-driven initiativesthat are valued within a community-centered environment, our findings validate HPLs prediction, written 20 years ago, that new technologies provide opportunities for communication and online learning and can connect teachers and students with others who share their interests and needs (p. 194). Later in this section, we also discuss how these student-valued program structures point to actionable instructional strategies that aim to develop communities of practice, an approach that involves collaborative peer relationships and teachers participation in educational research and practice (p. 197), which HPL advocates.

Looking across these categories, several themes emerged that highlight unresolved tensions in students perception of their learning experience. We believe these tensions deserve greater attention in the development of more effective online degree programs. First, participants commonly cited professional and geographic diversity as a strength of the online program, but this contrasted with the limited ways in which the program supported racial diversity. The synchronous conferencing technology allowed students to enroll in the program from all over the world, which is an important feature of fully online programs that differ from one-off courses in primarily in-person programs (Galanek et al., 2018; Park & Bonk, 2007). However, unclear norms around relatively novel features of the software (like the chatbox) also created an opportunity for some students to make racially insensitive comments. Part of this tension stems from the difficulty instructors had with managing both the spoken discussion and written discussions in the chatbox. Although the two conversational streams gave more students an opportunity to contribute, they also meant that potentially harmful comments could go unnoticed or unaddressed by instructors. Given data from a small number of participants, we did not have sufficient evidence to further examine this issue, but this tension suggests a greater need for online programs to develop explicit norms for using technology in ways that support a safe learning environment for racially minoritized students. HPLs community-centered dimension underscores norms not only for people learning from one another, but also for efforts to continually improve. Such norms should create safe and nurturing spaces that encourage students to be active, constructive participants and learn from their individual mistakes, regardless of their backgrounds. Potential ways to support this effort include designating specific people to monitor the chatbox and consistently communicating program-wide norms that address diversity and safety. Relative to single online classes, we believe these norms could potentially be even more powerful in fully online programs that implement them consistently from course to course.

Second, many participants described the effectiveness of virtual communication tools in supporting a community-centered learning environment while simultaneously emphasizing the in-person immersion as crucial to building relationships and describing noticeable changes to the sense of community after the immersion. This tension appears to be driven by an increase in trust and sense of familiarity that students developed after physically seeing their classmates and spending concentrated time in social settings conversing on topics unrelated to course content. Yet, our interviews with participants who had not attended an immersion experience suggest that many felt strong connections with cohort mates even if they had never met in person. These tensions suggest that students felt adequately connected to each other when using online communication tools but realized even deeper connections (that some did not consciously recognize as missing) during and after the immersion. Many students also suggested scheduling the immersion earlier, when they began their first classes, to make the benefits to community-building even greater. We conclude that, although an in-person experience may not be necessary to support a community-centered learning environment, the experience can be quite powerful for students. Additionally, in-person meetings may be more powerful in fully online programs where students take more classes together than in single online classes that bring students together only for a short time. We also note that no students mentioned wanting the immersion to last longer or wanting more in-person meetings, suggesting that the combination of rich virtual communication tools and the short experience of sharing a physical space was perceived as sufficient to support a community-centered online learning environment. Also, these perspectives highlight the importance of more studies examining the student perspective on online programs, relative to only the perspective of program designers or leaders (Kumar, 2014; Parenti, 2013; Wagner et al., 2016).

Another related tension appears in students perception of how well they could read each others nonverbal cues. Numerous students noted that the virtual synchronous sessions put everyone under a spotlight because everyones face was visible to everyone else (assuming cameras were turned on). The intensity of attention from the whole class on each persons face, along with potential recordings of the synchronous session, made many students feel that classmates were keenly aware of their reactions. However, many students also felt like seeing facial reactions through a small, on-screen window made it difficult for them to read others reactions because body language was not visible and facial reactions were easy to miss. Part of this tension could be explained when we further interrogated the codes under individuality. Most students who felt the virtual environment focused more attention on their body language tended to have more experience with online learning, and students who felt like body language was missing tended to be less familiar with online learning. This tension suggests that programs, as part of supporting a learner-centered environment, should differentiate how they support students adjustment to reading nonverbal cues in online-only interactions. This finding also highlights a need for longitudinal research examining how students comfort with technology changes as they take more classes in a fully online programresearch that will further explain differences between the experience of online programs versus single online classes.

Overall, our results suggest that the HPL framework provides a cogent conceptual lens to capture online learning communities. Although the elements of a learner-centered and community-centered learning environment differ in fully online versus face-to-face or blended degree programs, the HPL framework remains a useful guide for maximizing students learning experience. For example, we found that although the HPL framework already emphasizes building students existing content knowledge, it should be further extended to also recognize and build on students existing familiarity with the online environment. Moreover, community-centered components of HPL tend to focus on learning from in-person conversations, but this component of the framework can be extended to include text-based discussions (e.g., asynchronous forums and text messaging applications). Given the student-focused nature of our inquiry, a limitation of our work is our examination of only two HPL dimensions, keeping us from examining all four dimensions in comparison to each other. Future research should expand our analysis by examining and integrating the assessment-centered and knowledge-centered dimensions of HPL.

Future work should also look beyond the HPL framework to examine noncognitivist phenomena that may also influence student experiences in fully online learning programs. Finally, it is important to keep in mind our positionality because two authors in this study were instructors in the program. Our perspectives are likely colored by our own experiences in this online environment, and future work should probe the intersection of instructor and student experiences in online learning.

Given the limitations in this paper, there is more work to be done to understand how different programmatic structures (e.g., when and how often to schedule immersions) can either support or detract from each of the four dimensions of effective learning environments within HPL. Our interview protocol allowed only limited opportunities to probe students perception of racial diversity and inclusion in their online experience. More research is especially needed to illuminate how the different dimensions of HPL can help us design instructional strategies that support more racially diverse and inclusive online learning environments. Other facets of diversity (e.g., gender, age, sexual orientation) are similarly critical avenues for future research that we did not pursue here. Overall, this work illuminates complex cognitive tensions around how students assess their learning experience in a fully online program and paves the way for the future design of these programs to better address student needs.  

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