{"id":8285,"date":"2019-01-30T15:28:06","date_gmt":"2019-01-30T15:28:06","guid":{"rendered":"https:\/\/citejournal.org\/\/\/"},"modified":"2019-06-05T15:44:39","modified_gmt":"2019-06-05T15:44:39","slug":"professional-learning-practices-and-beliefs-of-an-online-community-of-english-language-teachers","status":"publish","type":"post","link":"https:\/\/citejournal.org\/volume-19\/issue-1-19\/current-practice\/professional-learning-practices-and-beliefs-of-an-online-community-of-english-language-teachers","title":{"rendered":"Professional Learning Practices and Beliefs of an Online Community of English Language Teachers"},"content":{"rendered":"
Professional learning online and on social media is becoming widespread for teachers in many countries. Macia and Garcia (2016) reviewed selected studies on informal online communities and networks as a source of teacher development. The authors stated,<\/p>\n
Although informal learning and online collaboration have been largely studied, the corpus of research on teachers\u2019 online collaboration for professional development is not extensive and, in most cases, the examples of communities and networks that have been analyzed were developed for research purposes in university environments. (p. 293)<\/p>\n
Inspired by this concern, the research presented here investigated an informal community or network that developed organically. Because the field of teacher professional development in online communities is arguably at an early stage of development, this study applied the most widely used theoretical framework, Communities of Practice, to aid the process of finding commonalities across similar studies (Macia & Garcia, 2016).<\/p>\n
The study presented here focused on English language teachers (ELTs) who had a common global interest in learning from each other. Through my own professional learning practices, I had discovered many ELTs were tweeting from all over the globe united in language and professional development, providing evidence that social media can help teachers, with varying degrees of experience, find meaningful professional learning outside the boundaries of their respective institutions.<\/p>\n
The terms \u201cprofessional development\u201d and \u201cprofessional learning\u201d are often used interchangeably in the literature on teacher education (Avalos, 2011). In this paper the term \u201cprofessional learning\u201d is defined as the practice of teachers to support their pedagogical and content knowledge as well as their teaching practices for the purposes of improving student learning and relevance in the field (as also in Trust, Krutka, & Carpenter, 2016). In the case of this study, the field is English language teaching, in which \u201cpedagogical knowledge\u201d generally refers to education theories and \u201ccontent knowledge\u201d generally refers to the knowledge of applied linguistics.<\/p>\n
In a review of professional learning articles, Avalos (2011) noted that the traditional in-service teacher training model for professional learning has many limitations, a claim supported by other studies (Apple, 2009; Darling-Hammond, Wei, Andree, Richardson, and Orphanos, 2009; Duncan-Howell, 2010; Gibson & Brooks, 2013; Guskey, 2003; Kennedy, 2005; Opfer & Pedder, 2011; Trust et al., 2016). Gibson and Brooks (2013) pointed out that the traditional model often provides little applicability to the classroom, overloads teachers with content, uses the one-size-fits-all approach and, offers no modeling, practice, and follow-up. They also argued that administrators have minimal awareness if the curriculum has changed as a result of traditional professional learning practices.<\/p>\n
Duncan-Howell (2010) added that this traditional face-to-face model does not encourage the development of new skills nor does it have a lasting effect on teaching practices. For some teachers, these in-service professional development models are sometimes perceived as deskilling \u201cteachers from their intellectual work, treating them as passive recipients of mandates\u201d (Apple, 2009; Trust et al. , 2016).<\/p>\n
An alternative to the traditional in-service teacher-training model is online (or computer-mediated) professional learning. Within the past two decades, more studies and articles have described and promoted the benefits of this approach (Gibson & Brooks, 2013; Guskey, 2003; Kennedy, 2005; Macia & Garcia, 2016; Moolenaar, Sleegers, & Daly, 2012; Reich, Levinson, & Johnston, 2011; Stickler & Emke, 2015; Yoon, Duncan, Lee, Scarloss, & Shapley, 2007).<\/p>\n
Online professional learning is reported by some as more coherent and better connected to the school\u2019s goals and to teachers\u2019 needs (Gibson & Brooks, 2012; Stickler & Emke, 2015). Some teachers have thus claimed that this online learning has resulted in an increase in student learning and achievement (Moolenaar, Sleegers, & Day, 2012; Stickler & Emke, 2015) and a greater sense of teacher satisfaction with the collaboration process (Reich, Levinson, & Johnson, 2011; Stickler & Emke, 2015). Gibson and Brooks (2012) claimed that online professional learning can be ongoing and intensive; it can be more focused on content and curriculum, and it is delivered in more meaningful and relevant ways that provide opportunities for practice and feedback. Finally, online professional learning is usually less expensive, especially for freelance or part-time instructors who may not be supported with district funding for professional development (Stickler & Emke, 2015).<\/p>\n
Concerns teachers have about online professional learning include privacy (Akcayir, 2017; Seaman & Tinti-Kane, 2013), defining professional boundaries (Veletsianos & Kimmons, 2013), and institutional constraints (Manca & Ranieri, 2016; Walster, 2017).<\/p>\n
In 2010, Duncan-Howell referred to online communities as a new source of professional learning. Online communities can be formal or informal. A formal community has specific goals for the community, and the success of a formal online community is defined by how well it meets these goals and how well it cultivates sharing and trust (Booth, 2012; Bourhis & Dube, 2010). An informal online community creates a learning ecology (Hill, Wilson, & Watson, 2004), which encompasses informal collaborative learning environments. In this sense, the main difference is that a formal community has a shared goal or objective, whereas members each have their own individual goals in an informal community.<\/p>\n
Social media, such as Twitter and Facebook, have helped teachers create online communities for professional learning (Booth, 2012; Brass & Mecoli, 2011; Brown & Munger, 2010; Chen, Chen, & Tsai, 2009; Davis, 2015; Duncan-Howell, 2010; Holmes, 2013; Hur & Brush, 2009; Schlager, Faroq, Fusco, Schank, & Dwyer, 2009; Tsai, 2012; Tsai, Laffey, & Hanuscin, 2010; Vavasseur & MacGregor, 2008; Wesely, 2013; Zuidema, 2012). Social media helps online community members gain access to professional learning resources that might have been previously difficult to find (Booth, 2012; Dede, Ketelhut, Whitehouse, Breit, & McCloskey, 2009; Loucks-Horsley, Stiles, Mundry, Love, & Hewson, 2010; Nochumson, 2018; Schlager et al., 2009). These communities \u201ccan allow teachers to diversify their networks and to gain access to human and content resources not available locally\u201d and \u201cgive teachers agency in co-constructing their own personalized programs of professional learning\u201d (Reich et al., 2011, p. 384).<\/p>\n
Online communities are social learning structures and the term can be used interchangeably with online networks. A commonly used term for online networks for professional learning is professional learning networks (PLNs). Wenger, Trayner, and de Laat (2011) distinguished between the two stating that communities are \u201cthe development of a shared identity around a topic or set of challenges,\u201d whereas networks are \u201cthe set of relationships, personal interactions, and connections among participants who have personal reasons to connect\u201d (p. 9). In this paper, PLNs refer to online communities for professional learning.<\/p>\n
Several studies have described and analyzed PLNs through the theoretical framework of Communities of Practice (Booth, 2012; Cranefield & Yoong, 2009; Davis, 2015; El-Hani & Greca, 2013; Hur & Brush, 2009; Ranieri, Manca, & Fini, 2012; Tsai, 2012; Wesely, 2013). Booth (2012) described communities of practice as \u201cgroups of people who share a concern, a set of problems, or a passion about a topic, and who deepen their knowledge and expertise in this are by interacting on an ongoing basis\u201d (p. 4). The Communities of Practice framework (Wenger, 1998; Wenger-Trayner & Wenger-Trayner, 2015) is grounded on a social theory of learning, postulating that learning is the product of a community and its interactions.<\/p>\n
In her qualitative study of world language teachers on Twitter, Wesely (2013) posited that PLNs can serve as communities of practice. She analyzed her participants using Wenger\u2019s (Wenger-Trayner & Wenger-Trayner, 2015) themes of domain, community, and practice. Put simply, the domain refers to the shared interests of the group, in this case the PLN, the community refers directly to the members of the PLN, and the practice refers to the discussions and texts produced by members of the PLN online and offline. Two of these themes, domain and practice, are central to this study.<\/p>\n
Davis (2015), Hur and Brush (2009), and Wesely (2013) implemented the framework on their investigations of PLNs already existing outside the control of the researchers or specific institutions. Davis (2015) and Wesely (2013) investigated Twitter as the primary platform for PLN interactions. Five main themes or reasons for using Twitter (Davis, 2015) and other online communities (Hur & Brush, 2009) emerged, many of which overlapped in meaning.<\/p>\n
Hur and Brush (2009) found teachers wanted to participate in online communities to experience a sense of camaraderie while Davis\u2019 (2015) participants found Twitter promoted a sense of belonging. Teachers also found the technical benefits of Twitter (Davis, 2015) and the advantages of online environments (Hur & Brush, 2009) helped ease facilitation of their professional learning.<\/p>\n
Wesely (2013) sought to understand how the characteristics of her participants\u2019 community of practice related to teacher learning. Community was the characteristic that overlapped the most with the aforementioned studies, in that she found many of her participants \u201chad a profound feeling of professional isolation in their school environment\u201d (p. 312), and Twitter helped them find this community in their PLN. The difference between the Davis (2015) and Hur and Brush (2009) <\/strong>studies and Wesely\u2019s study is that her participants\u2019 community was explicitly a site of teacher learning.<\/p>\n Similar to Wesely\u2019s study, the current study also investigated preexisting PLNs outside the control of the researchers and sought to examine how PLNs for English language teachers compared and contrasted with PLNs for teachers in general (Davis, 2015; Hur & Brush, 2009) and PLNs for world language teachers (Wesely, 2013) using the communities of practice framework.<\/p>\n This study sought to investigate similar issues with the following research questions:<\/p>\n To answer these questions using the Communities of Practice framework, professional learning was the specific type of practice under investigation within the domain that included other interests in that framework (Wenger, 1998; Wenger-Trayner & Wenger-Trayner, 2015).<\/p>\n This case study was an investigation of a PLN and the professional learning practices and perspectives of its members. It was a holistic or single-case study with the PLN as the unit of analysis, studied in the online contexts of social media, primarily Twitter and the blogs written and shared by members of the PLN (Yin, 2009). It was largely a descriptive case study because it presented a detailed account of the domain and practice of the PLN as a community of practice. However, it was also an evaluative case study, as the second research question evaluated the PLN\u2019s online professional learning in comparison with more traditional methods of professional learning. For both descriptive and evaluative purposes, the case study is an ideal research method for this research because it provides rich, thick descriptions ideal for a Communities of Practice framework (Macia & Garcia, 2016; Merriam, 1998).<\/p>\n All participants of this study were members of my PLN, most identifying as English language teachers at the time of data collection. Some also identified as researchers in English language teaching. For the purpose of this paper, members of the PLN will be referred to as English language teaching professionals.<\/p>\n Convenience sampling was used to recruit participants who were already members of the existing PLN. Each participant in the sample already met the following criteria:<\/p>\n Out of the hundreds of English language teachers I followed on Twitter, 20 agreed to participate in the study. Recruitment began on March 15, 2017, and ended on April 10, 2017. All participants signed consent forms approved by my institutional review board. To protect the privacy of the participants, I use pseudonyms in this paper in place of their real names.<\/p>\n At the time of data collection, the participants lived in many parts of the world (see Table 1), with a quarter of them (five of 20) living in Japan. Four of the 20 participants speak English as their second language. Their first languages are Russian (Grace and Rebecca), French (Mira), and Czech (Eve).<\/p>\n Table 1<\/strong> Three sets of data were collected for this study: interviews, blog posts, and tweets. The primary data set was from the interviews, which were recorded between March 17, 2017, and June 8, 2017. Participants had an option of being interviewed either through synchronous online text using Google documents or through Zoom, an online video conferencing product. Interviews were semistructured; participants were each asked the same set of questions, allowing for follow-up questions depending on the quality and quantity of responses to each question.<\/p>\n All video interviews were transcribed. Both video and text interviews were coded using open and axial coding techniques (as in Mogdhaddam, 2006). Open coding was used to identify general categories of information, which were labeled in the margins with summaries. Axial coding disaggregated the open codes and organized interview data into four major categories.<\/p>\n Three of these categories answered research questions for this paper. These three categories were identity, network, and professional learning. Each category followed additional levels of axial coding and analysis. For the identity category, two responses to interview questions were coded into themes. For example, the responses to the question, \u201cWhy do you use social media for professional learning?\u201d were coded into 22 themes.<\/p>\n For the network category, general comments about social media represented one category, whereas the names of individuals and blogs that each participant followed represented the other. These general comments were further divided into general comments about Twitter and general comments about blogs and blogging.<\/p>\n Of the three major axial codes, the professional learning category yielded the most information. This code addressed statements in the interviews comparing professional learning on social media to three more traditional means of professional learning: textbooks, scholarly articles, and conferences. Face-to-face school or district-based means of professional learning were not included because most of the participants were not in public school systems where these are commonly offered.<\/p>\n Three three-column tables were designed for this analysis. Each table represented the comparison between professional learning on social media and one of the more traditional means of professional learning. For each table, the left column listed codes addressing social media, whereas the right column listed codes addressing one of the more traditional means, and the middle column listed codes listed items that addressed them equally. See Tables 2, 3, and 4 for abridged examples of each type.<\/p>\n Table 2<\/strong> Table 3<\/strong> Table 4<\/strong> <\/em><\/p>\n Publicly accessible online document data were also collected and coded from two types of sources, Twitter and blogs. Because several of the participants had tweeted more than 10,000 times, data collection was limited to 12 months (June 30, 2016, to June 30, 2017) or the most recent 1,000 tweets. For example, Trevor tweeted the most frequently, 1,000 times from late June 2017, to April 24, 2017. Therefore, the maximum number of tweets coded per participant was 1,000. Eleven participants tweeted 1,000 times within a year.<\/p>\n Sixteen participants had publicly accessible blogs that had at least one post addressing English language teaching issues. Similar to Twitter data, data collection was limited to the 12 months, June 30, 2016, to June 30, 2017. Fifteen of the 16 blogged within that time frame, and the number of posts ranged from two (Esther) to 73 (Max). Table 1 shows the online document data collected from each participant.<\/p>\n Each participant\u2019s Twitter data was scanned for content related to ELT issues only. All other content on Twitter was not collected. Because of the high volume of Twitter data, the coding process analyzed tweets by month, coding ELT-related topics or issues that arose more than twice each month. The same process was applied to ELT-related hashtags, such as #eltchat, referring to a semistructured tweet chat, and #TESOL17, referring to the International TESOL Association\u2019s 2017 Convention and Expo.<\/p>\n After the topics and hashtags were coded, they were analyzed for frequency by each participant and by the PLN as a whole to identify what they tweeted about in descending order, not including topics or hashtags used once a month. The topics were also themed if and when they were found to have similar content or content that greatly overlapped. For example, the codes for webinars, websites, online courses, and online resources were eventually grouped under one theme: online resources.<\/p>\n Only 15 of the 20 participants had blogs with posts between June 30, 2016, and June 30, 2017. Table 1 shows the number of blog posts per blog. Just like collection and analysis process for the Twitter data, only blog posts about ELT issues were included. Each post as a whole, as opposed to the contents of each post, was coded using a spreadsheet that listed at least one code per post.<\/p>\n After coding all ELT-relevant blog posts, 124 different codes were identified. These open codes were then themed into 16 themes and a 17th \u201cother\u201d axial code for single codes that did not fit the other themes. These axial codes were then listed in order of frequency by the PLN as a whole.<\/p>\n An outside researcher coded the raw data independently to identify any codes that may have been overlooked or mislabeled. After analysis was completed and the first draft of this article was completed, the participants were invited to check the results to verify if they were represented accurately in the paper. This member checking helped to increase the accuracy of the findings and improve the validity of this study (Creswell, 2014).<\/p>\n The purpose of this study was to investigate the domain, practice, and beliefs of a Community of Practice, specifically a PLN of ELTs on Twitter. The first research question asked about the domain, uncovering the \u201cshared competence that distinguishes members from other people\u201d (Wenger-Trayner & Wenger-Trayner, 2015): What aspects of English language teaching did the participants discuss, tweet, and blog about? The second research question exploreed one specific aspect of the PLN\u2019s practice, sharing professional learning online: How do members of this PLN compare professional learning through social media with professional learning through more traditional means: reading textbooks on ELT, reading scholarly articles on ELT, and participating in professional teaching conferences?<\/p>\n This section identifies the extent to which professional learning is discussed among ELT topics on Twitter and the participants\u2019 blogs over the course of 1 year. The Twitter data results are divided into tweets and hashtags, as some participants used hashtags more frequently or habitually than others.<\/p>\n The most common practice was sharing blog posts written by other ELT professionals. One specific blog that many participants shared is ELT Research Bites<\/em>, created by Dustin with several collaborators from this PLN, including Aurora and Trevor. Other members of this PLN who did not collaborate on writing posts helped to share and promote the blog and specific posts of interest. Sharing blog posts exposes members of the PLN to literature they might otherwise not see and, therefore, contributes to their general awareness of current issues.<\/p>\n Beyond sharing blogs and blog posts, this study found 14 other common themes and issues that make up this PLN\u2019s domain. Listed in descending order of frequency, these issues are as follows: conferences, students, online resources other than blogs, teacher equity (primarily for nonnative English speakers), technology for teachers, research, blog and research writing, professional learning, teachers\u2019 wellbeing, teacher education, grammar, promoting a global online teacher development institute, pronunciation\/phonology, and the politics of work. These 15 common themes demonstrate that sharing professional learning is the major overarching theme of this PLN. Of these themes, seven can be categorized as tools for professional learning: conferences, online resources, instructional technology, research, writing, teacher education, and promoting a global online teacher development institute.<\/p>\n In addition to analyzing the ELT topics or issues that PLN members tweeted, this study also analyzed the hashtags frequently used on Twitter. According to Twitter (2017), \u201cA hashtag\u2014written with a # symbol\u2014is used to index keywords or topics on Twitter. This function was created on Twitter, and allows people to easily follow topics they are interested in\u201d (np).<\/p>\n This study identified 81 hashtags that were used more than once a month over the course of a year, with 29 of them used more than 1 month or more than one person. Ten of these 29 hashtags were about professional teaching conferences. Among the other 19 hashtags used, #ELTchat denotes an overlapping community of practice of ELTs. #ELTchat is usually a synchronous tweet chat organized by CELTA trainers with an ELT-related prompt once a week (ELTchat, 2017). Five participants were involved in #ELTchat more than once a month.<\/p>\n In addition to Twitter data, blog data were analyzed to learn more about the PLN domain; however, blog data is considered secondary to the Twitter data because many of the participants stated that they did not follow their peers\u2019 blogs as closely as their peers\u2019 tweets. For example, Julian admitted he \u201ckind of stopped reading them\u201d (Network, March 30, 2017), and Andrew stated, \u201cThese days I don\u2019t even really follow blogs that much\u201d (Network, April 6, 2017). Furthermore Dustin, Grace, and Ellen claimed they did not follow any blogs specifically.<\/p>\n Most of the participants said they would read a blog if it was posted on Twitter and they found the topic interesting. Of the blog data, 16 themes and a 17th \u201cother\u201d theme emerged after the 124 codes were categorized. Figure 1 shows the number of blog posts per theme.<\/p>\nResearch Questions<\/h3>\n
\n
Method<\/h2>\n
Participants<\/h3>\n
\n
\nParticipants and Their Collected Publicly Accessible Online Data<\/p>\n\n\n
\n Twitter ID<\/strong><\/td>\n Type of Interview<\/strong><\/td>\n Country of Residence<\/strong><\/td>\n English <\/strong><\/td>\n Most Recent Twitter Data Collected <\/strong><\/td>\n No. Blog Posts in 12 Mos.<\/strong><\/td>\n<\/tr>\n \n Aaron<\/td>\n Video<\/td>\n UK<\/td>\n L1<\/td>\n Full 12 months<\/td>\n N\/A<\/td>\n<\/tr>\n \n Andrew<\/td>\n Video<\/td>\n Japan<\/td>\n L1<\/td>\n Until March 1, 2017<\/td>\n N\/A<\/td>\n<\/tr>\n \n Aurora<\/td>\n Text<\/td>\n Germany<\/td>\n L1<\/td>\n Until July 16, 2016<\/td>\n 33<\/td>\n<\/tr>\n \n Dustin<\/td>\n Video<\/td>\n USA<\/td>\n L1<\/td>\n Until August 2, 2016<\/td>\n 36<\/td>\n<\/tr>\n \n Ellen<\/td>\n Video<\/td>\n Italy<\/td>\n L1<\/td>\n Full 12 months<\/td>\n N\/A<\/td>\n<\/tr>\n \n Erica<\/td>\n Video<\/td>\n Canada<\/td>\n L1<\/td>\n Until March 14, 2017<\/td>\n 41<\/td>\n<\/tr>\n \n Esther<\/td>\n Video<\/td>\n Japan<\/td>\n L1<\/td>\n Until October 6, 2016<\/td>\n 2<\/td>\n<\/tr>\n \n Eve<\/td>\n Text<\/td>\n Czech Republic<\/td>\n L2<\/td>\n Full 12 months<\/td>\n 46<\/td>\n<\/tr>\n \n Felix<\/td>\n Text<\/td>\n Japan<\/td>\n L1<\/td>\n Full 12 months<\/td>\n N\/A<\/td>\n<\/tr>\n \n Grace<\/td>\n Video<\/td>\n Canada<\/td>\n L2<\/td>\n Until October 24, 2016<\/td>\n 8<\/td>\n<\/tr>\n \n Harvey<\/td>\n Text<\/td>\n UK<\/td>\n L1<\/td>\n Full 12 months<\/td>\n 7<\/td>\n<\/tr>\n \n Jesse<\/td>\n Text<\/td>\n USA<\/td>\n L1<\/td>\n Until February 22, 2017<\/td>\n 40<\/td>\n<\/tr>\n \n Julian<\/td>\n Video<\/td>\n UK<\/td>\n L1<\/td>\n Until August 19, 2016<\/td>\n 39<\/td>\n<\/tr>\n \n Max<\/td>\n Text<\/td>\n USA<\/td>\n L1<\/td>\n Full 12 months<\/td>\n 73<\/td>\n<\/tr>\n \n Mira<\/td>\n Text<\/td>\n Saudi Arabia<\/td>\n L2<\/td>\n Full 12 months<\/td>\n 0 (last post in April 2016)<\/em><\/td>\n<\/tr>\n \n Raphael<\/td>\n Video<\/td>\n South Korea<\/td>\n L1<\/td>\n Full 12 months<\/td>\n 18<\/td>\n<\/tr>\n \n Rebecca<\/td>\n Text<\/td>\n Japan<\/td>\n L2<\/td>\n Full 12 months<\/td>\n 13<\/td>\n<\/tr>\n \n Stewart<\/td>\n Video<\/td>\n Canada<\/td>\n L1<\/td>\n Until February 6, 2017<\/td>\n 4<\/td>\n<\/tr>\n \n Sylvester<\/td>\n Video<\/td>\n Japan<\/td>\n L1<\/td>\n Until March 29, 2017<\/td>\n 44<\/td>\n<\/tr>\n \n Trevor<\/td>\n Text<\/td>\n France<\/td>\n L1<\/td>\n Until April 24, 2017<\/td>\n 19<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n Data Collection and Analysis<\/h3>\n
\nSocial Media vs. Textbooks<\/p>\n\n\n
\n Social Media<\/strong><\/td>\n Both<\/strong><\/td>\n Textbooks<\/strong><\/td>\n<\/tr>\n \n Quicker (4)
\nMore accessible (4)
\nMultiple perspectives (3)<\/td>\nEnables authors to expand (2)
\nEnables readers to question (2)<\/td>\nFoundations we have and need (2)
\nDon\u2019t have the time to read full books (2)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
\nSocial Media vs. Scholarly Articles<\/p>\n\n\n
\n Social Media<\/strong><\/td>\n Both<\/strong><\/td>\n Articles<\/strong><\/td>\n<\/tr>\n \n Free (2)
\nHelp more with the practical aspect (2)
\nShorter (2)<\/td>\nAccess (4)
\nDiscuss articles on social media (2)
\nBridge (2)<\/td>\nNot necessarily written with teachers in mind (2)
\nMeaty and hard to digest (2)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
\nSocial Media vs. Conferences<\/p>\n\n\n
\n Social Media <\/strong><\/td>\n Both<\/strong><\/td>\n Conferences<\/strong><\/td>\n<\/tr>\n \n Cheaper (3)
\nAccess every day (2)
\nYou can always close the window\/walk away (2)<\/td>\nLearn about conferences through social media (3)
\nSocial media shares videos of\/from conferences (4)<\/td>\nHappen once in a while (2)
\nImmediacy of various forms of communication (2)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\nResults<\/h2>\n
PLN Domain: How Important Is Professional Learning to the PLN?<\/h3>\n