The #acadv Twitter chat is an organic, online community of higher education academic advising professionals. Using a longitudinal study, we explored the way a self-directed learning network sustains ongoing professional development and knowledge sharing by examining the archives of 203 structured online discussions. In mapping the chat topics to published core competencies, we discovered that this advising community scaffolds on-demand learning for discussion of advising approaches and strategies, distribution of resources for supporting student success, collective sharing of personal advising philosophies, and encouragement to engage in reflective assessment about advising practice. Community members are motivated to contribute to networked practice to enhance professional development activities, share open educational practices, and support advising competency development in an occupational community of practice.
As higher education institutions increase accountability efforts to include degree completion, the role of the academic advisor increases in importance for supporting students. The profession of academic advising continues to grow as campus stakeholders and student service professionals strive to meet common goals for learner success. Toward this end, academic advising creates part of the learning process. At most postsecondary institutions, a variety of academic advising professionals, including primary-role practitioners, adjunct instructors, tenure- and nontenure-track faculty members, and a variety of administrative staff members, are dedicated to student success. For the purpose of this article and to be inclusive of the various functions, roles, and institutional job titles associated with it, we refer to all advisors as either academic advising professionals or advising professionals.
Academic advising professionals not only offer scholastic advice for course selection and student retention but also communicate and provide mentoring experiences to encourage learners to persist toward graduation and to reach their professional objectives (Drake, 2011). Academic advising is not merely a transactional enterprise; advising professionals offer more than guidance about degree planning, course selection, and academic requirements. Academic advising professionals support learners and help them make meaning of their academic work, clarify their personal goals, and reflect critically on their educational experiences while considering their future career objectives.
Lowenstein (2013) outlined a vision for the future of academic advising that is closely tied to the faculty role in higher education. Specifically, he described a type of advising professionalization that embraces both an educator and a scholar role characterized by commitment to purposeful student support and shared standards for practice. The interest in scaffolding evidence-based practice with scholarly inquiry will contribute to improvements in the effectiveness of the advisor and in learner success and outcomes. Recent publications, such as Academic Advising Approaches: Strategies That Teach Students to Make the Most of College (Drake, Jordan, & Miller, 2013) and The New Advisor Guidebook (Folsom, Yoder, & Joslin, 2015), offer comprehensive guides to educate and understand the role of the postsecondary advisor and the profession of academic advising. During the past few decades, the field of academic advising has been building a theoretical base, with scholarly works that include theories, such as developmental advising (Grites, 2013; Grites & Gordon, 2000) and appreciative advising (He & Hutson, 2016; Hutson & Bloom, 2007), to inform practice.
Advising professionals also add to the teaching and learning mission of the institution by identifying clear outcomes for student learning, designing systemic and systematic processes of assessment to inform students about their academic progress, maintaining standards through professional development opportunities, and offering recognition for quality advising practices that contribute to campus and the profession as a whole (Campbell & Nutt, 2008). Advising professionals help learners to think critically about the deeper meanings that support their reason(s) for study, encourage reflection on intellectual interests and ideas, prioritize decision making that is aligned with the learner's experience, and connect academic goals to broader professional objectives to establish habits that will support lifelong learning practices (White & Schulenberg, 2012, p. 15). Academic advising can be described as individualized sense making, which requires the student's participation and involvement in the process.
The authors of Driving Towards a Degree identified a 37% growth of advising personnel in the previous 2 years and reported that 53% of institutions adopt technology for academic planning, meeting auditing programs requirements, managing caseloads, engaging with early alerts, and evaluating transfer credit (Bryant, Seaman, Java, & Martin, 2017). As the advising profession grows, so does the need to improve the models, structures, and processes for effective student support. Of currently enrolled college or university learners, 73% would have been considered “nontraditional” in the past; that is, they are single parents, caretakers, employed full-time, financially independent, or enrolled on a part-time basis (Blumenstyk, 2018). Advisors influence student success by fostering accountability, responsibility, self-efficacy, and study skills and empowering them through continual support (Young-Jones, Burt, Dixon, & Hawthorne, 2013). Nuanced advising concepts, information, and skills used in practice are now aligned with professional development for advisors. In this article, we explore the way academic advisors utilize social technologies to engage in networked practices for their professional development. Networked practices are connected activities, online interactions, and shared experiences in which individuals engage through social, digital platforms. Specifically, we examine whether topics in a Twitter chat align with the NACADA: The Global Community for Academic Advising (NACADA) professional development competencies.
Review of Literature
An increasing number of competency frameworks are used to map professional performance and focus on practice-based training objectives for working in higher education. For example, metrics designed for student affairs and student support are generated to identify clear definitions of the skills, knowledge, and characteristics needed by professionals in the field and the graduate courses and preparation programs they must complete (Herdlein, 2004). Another example, for faculty development, is based on Scholarship Reconsidered (Boyer, 1990) and The Scholarship of Teaching and Learning Reconsidered (Hutchings, Huber, & Ciccone, 2011), which challenged those in higher education to focus on instruction as the “facilitation of student learning” to influence the way pedagogical practices support student success. Because academic advising professionals are positioned uniquely within each postsecondary institution, potentially in a staff, faculty, or hybrid role, and because these positions come with diverse expectations, the need to identify advising competencies has grown. Professional competence differs by the individual characteristics, levels of experience within the profession, various current and previous fields of practice, and intentional learning efforts of each advisor (Mulder, 2014). In addition, academic advising professionals need self-awareness about the knowledge sets and abilities required according to the expectations and responsibilities of their particular advising role. The next generation of advising professionals must obtain experience with administration skills (e.g., finance, supervision, and strategic planning), research (e.g., evidence-based outcomes and scholarly inquiry) for the institution and the students enrolled (Herdlein, 2004), and pedagogical practices (e.g., course development, instructional design, teaching, and learning assessment). These needed skills correspond with a shift in higher education toward greater accountability, standardization of performance, and requirements for student success.
A Movement Toward Professionalism and Competence in Higher Education
To ensure quality professional practice of higher education administration, governing bodies and professional organizations offer guidance according to standards within the postsecondary environment. The Council for the Advancement of Standards in Higher Education (2015) consortium “promotes the use of its professional standards for the development, assessment, and improvement of quality student learning, programs, and services” (p. v). Two professional associations for postsecondary student development and services, ACPA—College Student Educators International and NASPA—Student Affairs Administrators in Higher Education, provide “the scope and content of professional competencies required of student affairs educators in order for them to succeed within the current higher educational environment as well as projected future environments” (ACPA/NASPA, 2015, p. 7). Some of these standards govern programmatic or functional areas within an institution; others identify graduate curricula that preprofessionals should experience either in a classroom or through an internship. Following the standards and philosophy for self-regulation, evidence-based decisions for resources, accountability, and staffing must be made for all functional areas within higher education.
Movements toward academic advising professional preparation have strengthened interest in addressing a range of training, education, and credentialing within the field. The NACADA Professional Development Committee created the Academic Advising Core Competencies (AACC) model “to identify the broad range of understanding, knowledge, and skills that support academic advising, to guide professional development, and to promote the contributions of advising to student development, progress, and success” (NACADA, 2017, para. 1). The AACC model established a foundation for training and development programs by offering guidance on effective practices related to the following three academic advising components (NACADA, 2017):
The Conceptual component provides the context for the delivery of academic advising, that is, the ideas and theories advisors must understand to effectively advise students.
The Informational component provides the substance of academic advising, that is, the knowledge advisors must gain to be able to guide the students at their institution.
The Relational component provides the skills that enable academic advisors to convey the concepts and information from the other two components to their advisees. (para. 4)
The NACADA AACC model offers a framework to guide advisor learning and encourage self-awareness and consistency for professional development in relation to the academic advising skills, knowledge, applications, and inquiry that effectively support students (Farr & Cunningham, 2017). To support continuous learning of advising, the AACC model offers proficiencies for student support regardless of the institutional mission, model, or application of academic advising practice. Peer conversations create a standardized process for and common understanding of advising practice by certifying, accounting, and measuring the functions of an academic advisor in a more uniform way across higher education institutions (Aiken-Wisniewski, Johnson, Larson, & Barkemeyer, 2015). With diverse expectations and expertise, advisors can develop these competencies and the resulting insights regardless of professional role, title, or position at their institutions. In addition, specific advising components encourage intentionality when conducting academic advising such that professional preparation is supported and a more-direct career path is established for future scholars and practitioners within the field (Aiken-Wisniewski et al., 2015). This architecture undergirds a knowledge base used to offer improved student support, standardization of components of the advising professional role, and preservation of “the reputation of academic advising as a legitimate profession” (Shaffer, Zalewski, & Leveille, 2010, p. 75).
A Shift to Networked Practice: Professional Development and Knowledge Sharing
Digital and social media platforms are changing the manner and timing through which higher education professionals participate in learning and development. Social learning is defined as “joining with others to make sense of and create new ideas. [It] is augmented with social media tools that bridge distance and time, enabling people to easily interact across workplace, passion, curiosity, skill or need” (Bingham & Conner, 2015, p. 8). In higher education, emergent technologies afford postsecondary educators' tools for communication, connectivity, and feedback useful for explaining their work on various social media platforms. For example, one can easily find a Facebook post featuring recommendations for program developments, an Instagram photo sharing information about a new promotion, or a tweet posted with a question or request for advice. Social networks support creation and knowledge-sharing organization by offering the ability to transfer tacit knowledge, exchange narratives, and preserve rich information (Nahapiet & Ghoshal, 1998). Because knowledge is socially constructed and situated, social media outlets enable über connectivity, broaden capacity for professional development, and support ongoing peripheral learning online (Lave & Wenger, 1991).
A growing number of online communities of practice distribute opportunities and offer a collective history of engagement, shared creativity, and a cooperative repertoire of experiences (Wenger, 1998). By participating in communities of practice, individuals share activities, construct identities, exercise sense making, and socially interact with one another (Wenger, 1998). Evidence shows that communities of practice offer effective mechanisms for promoting knowledge transfer both among members and within broader organizations (Retna & Ng, 2011), and in an interesting finding, the entire community benefits from the voluntary contributions of the members' collective knowledge, effort, and time (Wasko & Faraj, 2005). With access to collaborative platforms, many occupation-based communities of practice steward technology to help the community share work and connect with others to offer support and share ideas, tips, and innovations (Wenger, White, & Smith, 2009).
The integration of technological tools enables communities of practice to integrate experiences within networks designed outside the boundaries of physical space and time. These innovations nurture and contribute to networked practice among higher education professionals who participate in spontaneous, self-organizing, and fluid communities of practice that encourage members to make meaning of their occupational experiences (Wenger, 1998). The autonomy and access that social media tools afford contribute to the growth of these networks that attract “groups of people who share concerns or a passion for something they do and learn how to do it better as they interact regularly” (Wenger-Trayner & Wenger-Trayner, 2015). Contributors to online communities of practice may seek self-directed learning and want to connect with like-minded peers who share similar interests in professional development. The nature of these digital communities of practice encourages members to connect and contribute to learning, beyond designated roles, formal organizations, and geographic locations, according to their professional interests. With the emergence of connected technologies and accessibility to collaborative platforms, individuals find value for professional development that is neither cost nor time restrictive; that is, many online resources are found on demand.
Higher education practitioners are drawn to networked professional learning because it offers intentionality, experiential learning, peer review, consultation, accountability, and community (Carpenter & Stimpson, 2007). Social networks not only preserve collegial connections and professional affiliations but also provide space to build community around shared work experiences, interests, and values. Postsecondary educators choose to use interactive methods, such as consulting with colleagues and mentoring, to learn skills and access knowledge, and they often seek a variety of learning methods that comport with their professional objectives (Roberts, 2007). These networked practices offer opportunities and access for self-directed professional learning and ongoing development with peers that complement and augment traditional training (e.g., conferences, webinars, and workshops). They provide a space for practitioners and administrators to distribute information and news, introduce or explain resources, and discuss emerging trends.
For this study, we examined archived chat transcripts that revealed the constructed and distributed resources, ideas, and knowledge bases that the Twitter #acadv community has created in the physical world. These archived transcripts and other digital artifacts (e.g., the hashtag archive, blog, Twitter account) serve as a form of reflection for the members of a community of practice, as a whole, that is based on the values expressed. These artifacts contribute to a process of reification (Wenger, 1998) as the #acadv community engages in meaning making and participant ideas congeal through the production of objects (instances of chat on Twitter) in the physical world (transcripts of the chat). Wenger (1998) described this “thingness” and the reification process within the community as the “negotiation of meaning … the interplay of participation and reification that makes people and things what they are” (p. 72). The members of this community of practice negotiate meaning by chatting and thereby asking questions, offering responses, sharing links to resources, and perceiving meanings as true for the group (Wenger, 1998; Wenger & Snyder, 2000). As the archive of #acadv chats increases, the reification of the processing and sharing of knowledge about practice for this community will determine both meaning and understanding for participants.
Professional Networked Practices on Twitter
Twitter, an important social media outlet for working professionals, offers a platform to host conversations, share news, and make direct connections to relevant experts and knowledge sources. Twitter is viewed as a “third place” (Oldenburg & Brisset, 1982) for professionals to gather online (McArthur & White, 2016) because users can post as many as 280 characters and a variety of content (e.g., text, images, videos, and URLs). Communication on this platform has shifted gradually from broadcast to interactive to form a “hybrid network” community (Quan-Haase, Martin, & McCay-Peet, 2015, p. 9) that is both informational and social. Tweets can mention users (@ symbol) or tag topics of specific interests using hashtags (#), which leads to aggregation of ideas. Hashtags enable users to distribute information, curate resources, and connect (thread) dialogues on any subject. Unless an account is set to private, tweets are open for all to search, read, and respond to in aggregate by event, topic, and trend to reach beyond a user's social network (Lewis & Rush, 2013).
The hashtag creates a digital signal that professionals, colleagues, and peers use to teach, learn, and interact with one another. Therefore, professionals use Twitter to share knowledge and resources (Davis, 2015) when they connect to exchange information (Gilbert, 2016), develop meaningful interpersonal relationships (Visser, Evering, & Barrett, 2014), foster ownership of ideas in an occupational group (Moorley & Chinn, 2014), and cultivate a sense of belonging in a specialized learning community (Krutka & Carpenter, 2016). The professionals who optimize Twitter for knowledge sharing include nurses (Richardson, Grose, Nelmes, Parra, & Linares, 2016; Schnitzler, Davies, Ross, & Harris, 2016) and other health care professionals who also communicate with hashtags to offer motivation (Gilbert, 2016). In addition, K–12 teachers access Twitter for self-directed learning and professional development (Davis, 2015; Visser et al., 2014), and staff of government agencies use Twitter to explain their organizational roles and communicate transparency (Wang, 2016). Occupational communities are initiating conversations, dialogue, and knowledge distribution on Twitter.
Similarly, higher education colleagues are finding like-minded peers and the potential for connection with other professionals through Twitter networks organized with community hashtags. We built upon previous empirical work to examine the way structured Twitter chats provide online professional development within a community. Guidry and Pasquini (2013) shared the #sachat case study of student affairs educators using a hashtag for nonformal learning during weekly moderated chats and nonscheduled chat time to discuss trends, issues, and ideas for campus support services. Ford, Veletsianos, and Resta (2014) investigated an emergent social network, #PhDChat, and found that this organic community offers social and emotional advice, support, and resources for doctoral scholars. The learning and teaching in higher education chat (#LTHEchat) refers to synchronized Twitter discussions, facilitated by a guest moderator, that involve a variety of pedagogical topics and instructional themes each week (Beckingham, Nerantzi, Reed, & Walker, 2015). Gao and Li (2017) discovered that #edchat offered structured conversations for K–12 teachers and preservice educators to build connections, share resources, and gain perspectives from peers. Finally, Veletsianos (2017) identified hashtags for massive open online courses (MOOCs), such as #EdTechMOOC and #NutritionMOOC, and organic communities, such as #PhDChat, that offer professional development in digital learning environments where participants share and signal to others about their related learning experiences and common interests.
Similar to researchers of previous studies (Beckingham et al., 2015; Ford et al., 2014; Gao & Li, 2017; Guidry & Pasquini, 2013; Veletsianos, 2017), we focused on the way academic advising professionals use a hashtag to conduct a synchronous Twitter chat and support a distributed network, that is, an interconnected group designed to share resources and accomplish a common goal, typically structured through Internet-based computing, for professional development. To better understand knowledge sharing and professional development activities of postsecondary educators on social media, we needed to see the way platforms are embedded into work-life experiences and practices over time. This longitudinal investigation involving digital artifacts (e.g., archived Twitter chat transcripts, Google docs, blog) offers insights into the way higher education professionals utilize social media for self-directed learning and occupational support in an online community of practice. For this study, we analyzed digital artifacts and socially constructed components of meaning that revealed spontaneous creation, structuration, and articulation among members of the #acadv community of practice. By reviewing the #acadv hashtag and the corpus of chat transcripts from this community, we can offer insight about how networked practice scaffolds informal, self-directed professional development within a digital environment.
For this study, we sought to understand the way an online community of peers supports professional development on Twitter. Specifically, we reviewed the digital artifacts shared and the archived transcripts (Twitter chat) produced by and from members of the #acadv community. To understand the characteristics, knowledge, and skills shared within this online professional network, this investigation asked the following research questions:
What are the general patterns of participation in the #acadv community during a sustained period of time?
Which topics or issues are frequently discussed during the structured #acadv Twitter chats that directly relate to the three components of the NACADA AACC model; that is, which artifacts or transcripts align with conceptual, informational, and relational core competency areas?
Based on mapping the NACADA AACC components to the #acadv chat archive, which gaps are visualized between the discussions of professional development and the professional development competencies for academic advising?
For this qualitative investigation, we used a combination of Web and social media recovery methods to collect data, an approach called netnography, which is a type of digital ethnographic research that is designed for investigating digital spaces and artifacts and that involves participation within an online community (Kozinets, 2015). To ensure efficacy and to meet ethical standards, we followed the common practices of netnography, which include immersive involvement within the group, prolonged engagement over time, identification of our research participation, and persistent and ongoing conversations with members of the community (Kurikko & Tuominen, 2012). We included both observational and archival data created by and for the community. Following data retrieval, we employed basic descriptive statistics and in-depth qualitative analysis to examine each of the research questions.
The #acadv Community on Twitter
The @acadvchat Twitter account has been active since October 2010, and participants use the associated #acadv hashtag to share information about academic advising practices in higher education and moderate a weekly and, more recently, a biweekly 60-minute conversation. The #acadv hashtag and the Twitter chat offer a space for academic advising professionals to congregate and exchange ideas, discuss issues, distribute resources, and learn more about academic advising practices. The #acadv community members include full-time and part-time professionals, graduate students, administrators, instructors, and faculty members who work within postsecondary education. The majority of participants work at American or Canadian institutions. To ensure the privacy and confidentiality of the #acadv community members, individual demographic information is not included in this netnographic study because the social media platform (Twitter) and this research data set (the Twitter chat archives) are both publically accessible and searchable online (Kozinets, 2015, pp. 131–134). General membership and participation in the #acadv chats are dynamic, so the focus for this investigation was on the archived transcripts and collected data that reflect the use of the #acadv hashtag for structured conversations and use of the same hashtag during off-schedule chat times.
The Twitter chat transcripts are open and accessible for all to view, and democratic measures are used to engage participants in decision making about the chat topics and the direction of the communication for the members of the community. In addition, we have historical knowledge of the community: One author currently maintains the data collection for this community and has supported the leadership of this group since its inception. Other digital artifacts available for analysis include the community blog, a Facebook page, the Twitter account archive, and Google planning documents created and contributed to by the team that moderates the structured chat conversations.
For each weekly or biweekly #acadv chat, a topic is selected, or a vote is taken in the community to focus the conversation on a particular element of academic advising and student support in higher education. The @acadvchat Twitter account moderates the dialogue by posting reminders in advance to promote the topic and schedules and encourages participation by inviting higher education colleagues to join the open chat. Fourteen volunteers have helped with planning, organizing, and moderating this Twitter chat community. During the scheduled chats, one moderator posts five to seven questions or prompts to facilitate the discussion. These cues are released during the designated chat hour to guide the conversation according to the topic selected. Chat participants answer the questions with texts, URLs to online content (e.g., images, videos), and the designated hashtag. Although the #acadv hashtag is used in circumstances other than the structured, synchronous conversations, the participants in the official #acadv chat are self-directed in their contributions to the topic and interest in supporting the community. During the #acadv Twitter chat hour, this hashtag helps to thread the conversation and enables other participants to read and review responses to the #acadv prompts or questions.
To understand the characteristics of the #acadv community with regard to professional competencies, we mapped the chat topics discussed using the NACADA AACC model framework. The findings provide descriptive information obtained through the chat archives, blogs, and other digital platforms used to organize the community chats.
Data Collection: The #acadv Chat Archive
The chat transcript archives were collected from a WordPress blog and a Storify account, and we used a Twitter Archiving Google Sheet (TAGS) method. From 203 completed chats, we recovered 133 complete chat transcripts and the associated Google docs (n = 203) that outlined each discussion with questions and prompts. These chats were held between October 26, 2010, and May 22, 2018. Between the dates of November 25, 2014, and November 8, 2016, no transcripts were collected or available for review. The volunteer moderators responsible for the chat during this time period did not have the technical capability and/or resources (e.g., funding or personnel) to aggregate these data. The transcripts recovered (n = 133) comprised a corpus of 21,320 tweets, including 1,299 shared URLs, from 2,203 Twitter participants who contributed to these conversations. For the purpose of this investigation, we did not analyze or identify demographic information of the participants who contributed to the organized #acadv chat. Instead, we analyzed the way the #acadv hashtag was utilized on Twitter and sought to understand the contents and knowledge shared within the digitally archived conversations further; that is, we looked at the corpus of #acadv chat transcripts that served to document the community's activities over time.
To evaluate the topics discussed during the time in which transcripts were unavailable, we reviewed the 70 Google docs that had been used for planning the chats because they contained information about chat topics, including the titles of the chats, prompts and resources for the themes, and 413 questions used to guide the chat topic discussions. These documents offered sufficient comprehensive detail about the foci and issues (e.g., for each chat) that we could use the information for mapping to the professional development competencies. Since November 22, 2016, we have used an archive to collect conversations with the #acadv hashtag by using the TAGS open-source tool. TAGS helped capture the final 27 chats included in this study, including the complete conversations (posts and topics, etc.) and informational data about the community (e.g., geographic location and user interactions). To minimize potential risks to users in the community, we did not include any personal identifiers, geographic locations, or nonrelevant URLs that might reveal information about the individual users. By cataloging all of the chat topics, we identified the moderator who led the chat, counted the number of participants, counted the number of tweets, and determined the content and resources (e.g., URLs and images) shared during each chat event. All of the available Twitter chat archives were converted to CSV (comma-separated values) files for transfer to Excel for evaluation and analysis.
To examine the #acadv Twitter community like other researchers who had studied online groups for professional development (Beckingham et al., 2015; Richardson et al., 2016), we analyzed the textual data from the digital archive through a constant comparative method. Using the NACADA (2017) AACC framework to guide the coding of the data, we implemented an inductive approach based on grounded theory (Corbin & Strauss, 1990), following the work of other researchers who had mapped professional competencies (e.g., Neiworth, Allan, D'Ambrosio, & Coplen-Abrahamson, 2014). This process included independent coding of the corpus (e.g., topics, questions, prompts, responses, and planning documents) to identify the professional development core areas as denoted by the major AACC framework (e.g., conceptual [C], informational [I], and relational [R]). Each code referred to subcompetencies of the AACC framework given as statements numbered by content area; for example, a code of C3 refers to the third AACC framework statement under the conceptual area “theory relevant to advising” (see Table 1). Each chat was reviewed, and passages that aligned with the AACC competencies were denoted with 1 (or more) of the 18 possible codes. Through a review and discussion of each chat topic, we reached agreement as a means to check the validity of coding. Any discrepancies on the identification of subcomponents were resolved by consensus.
The academic advising Twitter community is an informal learning network that developed organically. Members use the #acadv hashtag to support dialogue and ongoing professional development as a way to support student success in higher education.
General Patterns of Participation in the #acadv Community
As of June 28, 2018, the @acadvchat Twitter account had logged 7,111 tweets, was following 434 other Twitter users, was followed by 2,395 Twitter users, and had been liked 557 times. The @acadvchat account had been active since October 2010, and at the time of publication, four moderators used the @acadvchat account to facilitate the biweekly Tuesday chat (12–1 p.m. Central time) during the academic calendar year (from September through May). They schedule no chats during the Summer (June through August). They infrequently share schedule-related posts to the blog and a dedicated Facebook page. Most activity transpires on the @acadvchat Twitter account by messages to followers or through use of the #acadv hashtag.
In reviewing the available chat archives (n = 133) to address RQ1, we documented an average of 17 participants, 161 posted tweets, and 11 posted URLs for each structured conversation. During the first 7 years of @acadvchat facilitations, 13 moderators have individually facilitated 3 to 48 Twitter chats. In this shared leadership structure, 4 moderators have organized the community logistics (e.g., scheduling, assigning topics, and promoting the chat). Over time, an average of 5 members of the #acadv community had participated in the original chats in 2010 and had continued to engage with the community through Twitter in 2018 (the last time of our data collection). Involvement in the #acadv community has been dynamic, with an average of 12 members who join the scheduled Twitter chats on a regular basis each year. From previous research on this #acadv community (Eaton & Pasquini, 2019), we learned that the common topics discussed involve supporting student needs, academic orientation, advising approaches and structures, advisor role expectations, and career development and advancement within the field of academic advising.
We examined the #acadv archive from November 2016 through June 2018 to determine the general patterns of hashtag use during a 20-month period. This archive contained 11,463 unique tweets, 2,878 retweets, and 6,233 links. In the #acadv archive, we found that 213 users had included tweets with the #acadv hashtag at least five or more times, and 144 users who had replied to others (i.e., used the @ symbol) had included the #acadv hashtag in their tweets. Most of the tweets originated from users within the United States; however, other geographic locations represented in this data set include Canada, the United Kingdom, Columbia, Pakistan, Egypt, and Singapore. In addition to #acadv, six of the most-popular hashtags used in this archive were #highered, #sachat, #nacada17, #sapro, #nacada, and #sagrad. These secondary hashtags signal to users in higher education, those who work in student affairs, attendees of the 2017 NACADA Annual Conference, members of NACADA, and graduate students currently in student affairs programs.
For the biweekly Twitter chats during this 20-month period, we calculated averages of 15 users, 147 tweets, and 31 posted URLs for each conversation. Overall, during this time, 92 unique users participated in the #acadv Twitter chats (n = 27). As a proportion of the entire corpus of documentation, 35% of the tweets (n = 3,966) and 13.5% (n = 827) of the shared URLs came from the 20-month #acadv hashtag archive. Active chat users (tweeting at least five times with the #acadv hashtag) comprised 43% of this archive. Most nonscheduled tweets identified with the hashtag referred to job postings, conference events, news, and solicitations for advice on or resources for academic advising practice.
Issues Discussed During the #acadv Chat Related to the AACC Model
To address RQ2, we evaluated the overall data from the community and found that all three competency areas—conceptual, informational, and relationship—were addressed. Furthermore, all 20 subcategories within the NACADA AACC model had been discussed (see Table 1). The data showed that the relational core competency was represented at the highest frequency, as shown in Table 2. Because members of the #acadv Twitter community often discussed skill development and reflected on their practices in the #acadv chat, the code R7, “engage in ongoing assessment and development of advising practice,” was the most frequent (n = 125) competency found for this mapping study.
The AACC conceptual competency area features three areas of competence (i.e., conceptual, informational, and relational) with 18 subcompetencies that identify ideas that advisors must understand and apply in practice. When coding the archive of chats, we identified 184 conceptual components. The most frequently discussed conceptual components were C4, “academic advising approaches and strategies” (n = 55), and C5, “expected outcomes of academic advising” (n = 47); “NACADA's core values of academic advising” (C2) followed with 40 mentions.
The informational competency area features seven components that cover the knowledge and information that academic advisors must master. We found 278 informational components included in the chat data, with I6, “campus community resources that support student success” (n = 55), and I3, “institution-specific policies, procedures, rules, and regulations” (n = 50), discussed most frequently. Chats often included specific information related to either an academic institution, such as “the history, mission, vision, values and culture” (I1), or specific student population “characteristics, needs, or experiences” (I6); both were discussed 48 times.
The relational competency area includes seven components that outline the skills and abilities that academic advisors must demonstrate in their professional practice. We identified 329 relational components within the chat archive. Beyond overwhelming engagement with R7, “engage in ongoing assessment and development of self and the advising practice” (n = 125), the data indicated two prominent areas of discussion: R1, “articulate a personal philosophy of academic advising” (n = 55), and R6, “facilitate problem solving, decision making, meaning making, planning, and goal setting” (n = 37). All three most-cited relational components require critical thinking, deep reflection, and understanding of application of advising for postsecondary student success. More instances of relational competency than instances from the conceptual and informational areas were mapped from chat data.
Professional Learning and Development Gaps Found in the #acadv Chat
Although the mapped data showed that many Twitter chat topics featured components of the NACADA AACC competency model, not all competency areas or subdomains received the same level of attention in the #acadv conversations. In our analysis to address RQ3, we found that four subcompetencies of the AACC had received the least attention in #acadv chats: I4, “legal guidelines of advising practice, including privacy regulations and confidentiality” (n = 7); C6, “how equitable and inclusive environments are created and maintained” (n = 8); C1, “the history and role of academic advising in higher education” (n = 15); and C3, “theory relevant to academic advising” (n = 19). AACC subcompetencies I4 and C6 describe the required critical facilitation skills for nuanced academic advising topics such as those discussed the least.
Ongoing participation in and sustained activity of the #acadv Twitter chat community suggests that, for a segment of postsecondary educators, this networked practice enables professionals to connect, contribute, and seek support related to their own learning and development. In building an online occupational community of practice, the relationships and regular sharing of experiences offers a self-directed way to gather information, acquire resources, and engage in dialogue with professional peers with minimal restrictions for participation (e.g., financial cost, geographic boundaries, and travel disruption). The #acadv community offers a means to contribute across institutional types, functional roles, and professional affiliations. These networked practices fill a larger gap in professional competency development among postsecondary educators. Unlike the student affairs chats (#sachat) that are organized as an informal learning resource (Guidry & Pasquini, 2013), the academic advising (#acadv) chat features specifics about the occupational role and designated responsibilities of academic advising, creating a niched, distinct community of regular contributors.
With this form of open educational practice, participants engage in peripheral learning about a profession (Cronin, 2017) and acquire a greater understanding of the academic advising role in higher education. They express interest in openly contributing and sharing knowledge with other academic advising professionals. This type of open dialogue welcomes new higher education colleagues and helps current community members develop rapport during such introductions (e.g., “@acadv MOD: Welcome to the #acadv chat. Please take a minute to introduce yourself, your role, and institution”), which builds trust before a conversation related to an occupation is initiated. The openness of the Twitter platform and access to read or contribute to the #acadv hashtag inspire conversations around academic advising to extend beyond topics related to a discipline, institution, or professional boundary.
Similar to research results from Sun, Rau, and Ma (2014), our findings showed that members of the #acadv community participate actively or passively in the discussions, and some lurk on the periphery of this online community. The hashtag allows for temporal participation and training on demand for advising professionals. When community members miss a scheduled chat, they can search the hashtag on Twitter, review the archives, and access the advising resources shared on Twitter or archived on the web site. Efforts to post upcoming scheduled conversations have led to creation of a dedicated Web space linked to the @acadvchat Twitter account. In addition, the use of this hashtag, other than solely during the scheduled Twitter chats, demonstrates participants' affinity and interest to continue the conversation about academic advising and student support with a broader audience (RQ1). Advising professionals and practitioners promote events, share information from conferences, post articles, seek out support, and ask questions frequently using the #acadv hashtag. The evidence suggests that these professionals are seeking modes to improve their advising approaches, outline their work philosophy, problem solve on the job, engage in ongoing assessment, and critically reflect upon their role and practice to better support college and university learners (RQ2).
In contrast, the mapping of the data to the NACADA AACC model subcompetencies revealed that some professional development competencies seldom transpired (RQ3). Specifically, the data show a lack of conversation about topics related to legal issues, privacy concerns, equity, and inclusion. To navigate the subject matter and guide conversation online about such topics may require specific expertise. The competency subdomains of C1 (historical) and C3 (theoretical) are connected to the historical underpinnings of the advising role and the way expectations for it have evolved in postsecondary education such that the in-depth discussions are based on understanding the various theories of learning, student development, and educational frameworks. Therefore, because of the limitations of the platform or logistics of a synchronous Twitter chat, the four topics receiving the least attention may not be easily addressed in the #acadv community chat space, a main shortfall for this networked community. Complicated topics cannot be adroitly handled through the Twitter platform because of the character limitations, text-only format, and public nature of the communication. These discussions can be better undertaken in a smaller discussion forum or using an alternative medium (e.g., Web conference, longer form discussion, private chat, or offline face-to-face conversation).
Whatever the difficulty with the platform, community members did not vote to address these topics, which may mean that members lack understanding or knowledge of them. However, because these conceptual and theoretical areas affect practice, perhaps the #acadv community should invite those with this advanced knowledge to facilitate a chat.
With no explicit or formal partnership with NACADA, the #acadv chat community cannot effectively expand the dialogue about the background and evolution of advising in higher education as they relate to educational or learner development frameworks. Hence, affiliation with a professional organization might bring new voices and subject matter expertise into the Twitter conversation. In this way, the expansion of nuanced and complicated topics, such as legal issues related to privacy and confidentiality guidelines (I4) and design and provision of inclusive advising settings (C6), might be discussed. However, limitations of the platform and the openness of the network may create barriers that discourage potential contributors.
Finally, these results suggest important implications for both the occupational future of advisors and the knowledge sharing among them. Twitter chats and similar media provide opportunities to enhance and develop the professional competencies outlined by NACADA through networking. The use of the Internet to acquire knowledge and develop skills complements traditional training curricula (e.g., institutes, conferences, and webinars) and provides accessible outlets for open, occupational learning. However, a need for experienced practitioners, early career professionals, and leading experts was identified for ongoing professional conversations about academic advising and student support. Professionals who are not yet part of this online community or who are involved in other types of networked practice might appreciate the opportunity to address the #acadv community as guest moderators to facilitate conversations about specific topics. In addition, community members may need to seek out additional media as spaces for discussing complicated issues. In any case, we suggest that the community extend invitations to advising professionals who can use their experience and expertise to fill the professional competency gaps through ongoing knowledge sharing using #acadv.
This research study featured a few limitations and necessary delimitations. First, we identified the aggregated transcript data to determine the topics discussed and used related digital artifacts from the community that had not been consistently collected (i.e., transcripts missing for chats between November 25, 2014, and November 8, 2016) because of limited technical capacities and resources. This gap in the data may mean that important information from these discussions is missing; however, the Google documents used for planning provided the topics, prompts, and questions used in each chat, which allowed us to map the professional development competencies for the missing chat transcript archives.
Second, the Twitter application programming interface (API) limits the retrieval of #acadv hashtag contributions for Twitter accounts that feature privacy restrictions. The API is a set of programming instructions and standards for accessing a Web-based software application or online tool, like Twitter. These standards and protocols can be released to allow computer developers a roadmap to build or design products powered by a particular service. Therefore, the aggregation of tweets may not include posts from Twitter users who protect their tweets or restrict access to their accounts, so these posts may not be accessible or accounted for with regard to individual settings and the API allowances.
Future investigations might address some of these limitations and clarify or extend our findings. We recommend comparisons of specific Twitter accounts of members within the community, reviews of individual Twitter data archives, and a review of #acadv hashtag use on other platforms. Use of the #acadv hashtag or activity related to the #acadv community on other social, digital platforms was not included in this study.
Implications for Practice and Future Research
Self-awareness and self-directed learning for professional growth are critical for advisors facing a variety of issues in supporting students, including changing demographic trends, in higher education (Farr & Cunningham, 2017). College and university staff, faculty members, and administrators seek ways to gain knowledge for effective academic success; however, completion of their quest requires ongoing training and use of innovative approaches to share evidence-based practice. To meet the diverse expectations of their role on campus, postsecondary educators need to utilize networked practices for on-demand professional development opportunities, just-in-time knowledge sharing, and continuous skills training.
The analysis of the digital artifacts from the #acadv chat community does not provide a complete picture of ways Twitter or other social media platforms might be utilized for professional development and ongoing knowledge sharing; however, it offers some key insights and points to issues that could be further analyzed and developed for professional advising practice. Although we focused the research on academic advising, we recognize that networked practices influence other higher education stakeholders and move beyond to affect other sectors of industry and professional life. With the opportunities that social digital technologies afford to augment and enhance professional development, we hope future research in this area will explore informational fluency and digital literacy in educational programs—challenges that career practitioners encounter early in their careers with networked practices. We also anticipate that further studies that examine networked practices will reveal other ways occupational, online communities shape job performance and long-term advancement in other career fields, disciplines, or industries.
Professional development experiences can be enhanced by networked practices. In analyzing the corpus of the #acadv chat, we presented insights on the way one Twitter community supports academic advising professional development through a social media platform. A peer-to-peer professional development network offers ways to mentor, model, and meet the needs of professionals who are seeking just-in-time solutions and on-demand training. The lessons learned from this organic, grassroots community include the development of new pathways for career engagement, innovative training designs, new pathways for accessing knowledge, and identification of gaps in talent and skill development within an occupation. Professional development can be self-directed, social, and organized digitally to meet the needs within any industry. Emerging digital environments and distributed networks have the power to advance training and professional development in the workplace. The ability to collaborate, share, engage, and inquire with networked practice nurtures individual career growth while also creating a ripple effect to influence organizations, professional associations, and occupational fields.
The authors thank Lisa Endersby for the research assistance she provided in preparation for data extraction and analysis.
Laura A. Pasquini, PhD, is a senior lecturer in the Department of Learning Technologies in the College of Information at the University of North Texas. Her scholarly work examines digital and open practices, specifically how sociotechnical systems and connected technologies influence mentoring experiences, professional identity development, and collaborative learning environments for workplace learning and performance. She can be reached at Laura.Pasquini@unt.edu.
Paul William Eaton, PhD, is an assistant professor of educational leadership at Sam Houston State University. Eaton's research interests include inquiries into digital technologies in education and human identity–subjectification–becoming; complexity, postqualitative, and posthumanist inquiry; and curriculum theorizing–philosophy in the realms of postsecondary education and student affairs.