Unpacking Network and Discourse of Educators in Professional Learning Communities

Jemma KwonKristen DeBruler

Michigan Virtual Learning Research Institute, Michigan VirtualUnited States

jkwon@michiganvirtual.orgkdebruler@michiganvirtual.org

Abstract: This study explored the network and discourse of a group of educators, all of whose roles inhibited their participation in professional communities at either the school or district level after they joined virtual professional communities (VPCs). The two VPCs in question included one for mentors who supported online learners, and one for early literacy coaches who worked with teachers to improve literacy instruction. Using network and textual data that was created by the participants as a result of interactions, the researcher conducted social network and text-mining analysis. The findings reveal that members exchanged high quality practical knowledge and ideas about professional identity. Areas in which the VPCs could be improved are also discussed.

Keywords: Teacher Professional Development,Virtual Professional Community,Text-mining,Social Network Analysis

IntroductionStrong and productive collegial relationship among educators is important to system improvement in, and success of educational organizations (Cardno, 2012). However, creating opportunities for collegiality, collaboration, and in turn ongoing learning has been as yet a big challenge (Darling-Hammond, Wei, Andree, Richardson, & Orphanos, 2009) as teachers’ physical and social separation and consequent psychological and intellectual isolation have been documented since 1970s (Lorties, 1975). Professional learning communities (PLCs) could be an approach with potential to solving the issue of professional isolation and lack of collegiality among school teachers (Lieberman & Mace, 2010). A hallmark of PLCs is collaboration through networking to achieve the shared goal of collective knowledge development (Lieberman, Miller, Wiedrick, & von Frank, 2011).

However, the modern school system has various types of faculty positions, some groups of teachers may have difficulty creating school building-level PLCs for members with shared goals and common interests related to particular positions. For instance, unlike core subject-matter teachers, the participating members at a particular school building may be few in number for some subject areas such as music, physical education, or special education. Itinerant teachers are another example, as they travel around schools to provide specialized services as speech therapy and sometimes, individual tutoring. In that case, one of biggest challenges in creating PLCs is time and distance creating a barrier to face-to-face meetings, and thus technology, such as web-based platforms, could be a solution in the form of virtual professional communities (VPCs, Lieberman & Mace, 2010).

VPCs have the same function as PLCs do, supporting interactions of members who share common goals, interests and needs as well as providing a socio-constructive space for sharing and verifying practical knowledge and in turn, developing the new knowledge (McConnell, Parker, Eberhardt, Koehler, & Lundeberg, 2013). In Michigan, we found some unique educator groups that would be ideally suited to the VPC form, online learning on-site mentors and early literacy coaches. The state of Michigan requires any school where students take online courses to staff an on-site mentor to support the student’s online learning in their brick-and-mortar school. On-site mentors are responsible for developing relationships with students, motivating them to engage in course activities, and guiding students in terms of communication, organizational, and self-regulated learning skills (Borup & Stimson, 2017). The Statewide Early Literacy Coach grant launched by the Michigan department of education enabled grantee districts to employ coaches to work with teachers across schools. Unlike the staff of subject-matter departments, it is impossible to create school building-level PLCs (as there is often only one on-site mentor and few literacy coaches) and difficult developing school/district-wide PLCs due to the often wide geographic separation among members and the rarity of meetings between or among them. In both cases, VPCs could be an effective means of decreasing these personnels’ sense of professional isolation and promoting their professional networks.

Nevertheless, VPCs’ affordances for isolated educators cannot be realized simply by creating online platforms. Moreover, a VPC should not be seen merely as a website for archiving resources, but as a space where people come together to exchange knowledge and share feelings and concerns about their profession. So, the ultimate goals of any VPCs are collective learning, knowledge development and professional identity development as educators. Therefore, it is important to acquire reliable research evidence on why some VPCs succeed while others do not.

Conceptual FrameworkThe present study was based on Wenger’s (1998) social theory of learning – encompassing community, identity, meaning and practice – seeking to understand what the created network looked like and which topic domains were produced as a result of educators’ participation in VPCs. Based on a literature review of various PLC and CoP models (McConnell et al., 2013; Owen, 2014; Scott, Clarkson, & McDonough, 2011; Trust, Krutka, & Carpenter, 2016), the present study explored discussion forums in two VPCs from perspectives including motivation, leadership, authenticity, collegiality, collective learning, focus on student learning outcomes, technology and other related skills, as well as element of research-oriented or inquiry-based. Appendix presents the conceptual framework for the study.

Methods

Two study sites in Michigan provided us with network and discourse data: (a) the Mentor Network for educators whose primary role is academically advising students who take online courses at the school building (b) the Early Literacy Coach Network for educators who were employed to work with teachers throughout Michigan. The two VPCs began in last two months of 2016 year, respectively. The EL Coach Network members met regularly face-to-face, and the online community provided an ongoing communication channel to bolster their interactions in between meetings. The Mentor Network was originally a website hosted resources and general information to understand the role of this unique position and extended to the function as a social constructivist space under the VPC framework.

There were 242 enrolled members in the Mentor Network and 1,147 in the EL Coach Network at the time of data collection (September 30th, 2018), each of which included 186 and 694 members that posted on either introduction or discussion boards. Yet, the study sample was limited to threads to discuss about specific educational topics and excluded data from introduction boards, returning the study sample of 19 of Mentor Network and 78 EL Coach Network.

Archives of the discussion forum formulated by members for approximately two years were processed as two types of data: network and discourse data. The network data refers to as the relations between actors, namely connections among members who posted and who responded to previous postings. We used 2-mode network data by adding one more dimension--the thread, so the network data of study represents how members are connected by communication ties around particular communication topics. Social network analysis (SNA) was performed using UCINET (Borgatti, Everett, & Freeman, 2002).

The discourse data means texts resultant from participating in discussions forums and two types of text mining techniques were used for the study: (a) style word analysis with Linguistic Inquiry and Word Count (LIWC: Pennebaker, Boyd, Jordan & Blackburn, 2015) and (b) content word analysis with data visualization by the use of word cloud. The former focused on function words such as pronouns, prepositions, and conjunctions so we could produce a snapshot of social and psychological characteristics in the discourse. On the other hand, the content word analysis was to draw an inference of communication topics through a weighted set of related words (Tausczik and Pennebaker, 2010). As such, for the content word analysis process, we treated function words as “stopwords” and thus removed them from all documents to be analyzed. Finally, the author conducted a qualitative thematic analysis of the discourses in the resultant word list (Ignatow & Mihalcea, 2017).

Results and DiscussionThe Mentor Network participants discussed six topics in 42 threads, containing a total of 183 postings. Six topic strands included: (a) General ideas and questions, (b) Starting a new term strongly, (c) Annual mentoring calendar, (d) Public knowledge base, (e) Credit recovery, and (f) Fully online programs. The individual threads contained an average of 4.4 responses to the initial post, with a minimum of zero and a maximum of 22. Of 42 total threads, 13 threads did not receive responses from colleagues and those threads are more likely to focus on particular program

formats of online learning (e.g., credit recovery and full-time online learning) rather than on the mentor role or teaching practices in general. The average time that elapsed from the initiation of a thread to its last post was 79 days, with the longest such period (as of the data-collection date) being 605 days for the topic surrounding specific resources for students while waiting for new semester and student enrollments.

A key difference between EL Coach Network and the Mentor Network was providing a structure to curate predetermined contents for professional learning, titled Essentials. As a result, the number of topics was greater than the Mentor Network’s as the platform was designed for participants to initiate each thread under individual categories of Essentials. General topic areas included: (a) Free Discussion, (b) Interacting with Administrators, (c) 3rd Grade Reading Law and Assessment, (d) Grant Opportunity; (e) A Place for New Coach to Share. Examples of Essentials discussion topics are (a) Deliberate research-informed efforts to foster literacy motivation and engagement within and across lessons, (b) Small groups and Individual instruction, using a variety grouping strategies, most often with flexible groups formed and instruction targeted to children’s observed and assessed needs in specific aspects of literacy development, and (c) An ambitious summer reading initiative supports reading growth.

Throughout both discussion forums, the EL Coach Network members created 84 threads with 304 postings. Among them, 26 threads’ initial communication did not obtain other members’ replies. Of note were those threads that explicitly sought for resources (“Any info would be appreciated”), recommendation/advice (“Any advice?”), feedback (“Your feedback will be appreciated”), other districts’ experience to share (“Any of your districts using…”) regarding particular model, assessment tools, and interventions. In Essentials’ discussion forums, one thread reflecting given learning materials and another thread sharing out additional resources were not extended by appreciation, feedback, or question by colleagues. The thread with the maximum number of replies (31) was about a conference the majority of members planned to attend. Aside from that, two lengthy conversations occurred to share ideas and district specific information surrounding procedures of 3rd grade reading assessment and law with 11 postings and ready-to-use resources for coaching practices (e.g., forms for meeting and planning) with 11 postings. The average time from the initiation of thread to its last post was 32 days, with the two longest threads having run for 439 and 369 days at the time of data collection. Note that the pre-curated material, Essentials’ discussion boards included both threads that were revisited and extended by other members more than one year after.

To explore networks formulated by members and communications, SNA was undertaken and network diagrams (Figure 1) illustrate the results on core members and threads of crucial topics for both VPCs. Circles in red denotes member nodes and square in blue indicate thread nodes and ties are connections among members as well as threads. Note that we used the valued network data (the number of connections among members and threads), not the binary data (whether to exist a connection), so the network diagram presents weighted nodes, which means that the bigger nodes, the greater frequency of interactions. The results suggest a variety of facilitating behaviors in the discussion.

Figure1. Two-Mode Social Network Diagram

In the core area of Mentor Network, we found three members as power users and their connectedness appeared to be anchored in the following conversation topics: (a) sharing school specific information and ideas in terms of how to support students in AP courses; (c) sharing orientation activities and resources for the new semester preparation; and (c) sharing “Annual Mentoring Calendar” each school had for mentors’ key roles by time of the semester. We found three ways for power users (i.e., the biggest circle node in the network diagram) to engage in discourse: (a) a long posting sharing out their own contexts or ideas to initiate a thread, (b) a long posting to extend the existing thread in the midst, and (3) frequent short postings to express agreements or appreciation. However, there was no power user’s questioning behavior, such as probing questions to elaborate given information.

In the EL Coach Network, the power user’s facilitating behaviors include posing questions (“Are you aware of…?”), encouraging members’ participation (“Have you considered doing a one hour presentation on an aspect of the Essentials?” or “I am wondering if anyone has crafted a parent letter they may be willing to share that explains the Law and/or the individualized  reading plan”), actively sharing resources (“Two  excellent website resources that were sited from…” ) and expressing positive feedback on colleagues’ activities (“Excellent question…” or “Excellent selections…”). Notably, we found the new type of facilitating behavior from threads though which the power user is connected to peripheral nodes (i.e., participants who are distant from the core area where power users and related threads locate). As shown following examples, “This video has been shared under the Essential #3 discussions” and “The first email bounced back”, a new type of facilitating behavior was to direct members to existing resources related to the question or request and provide logistical supports for the community management. In addition to active engagement with burning topics (i.e., long-running threads), the power users’ involvements were found in short threads, in which their communications appear to be related to the pre-curated materials, Essentials, or special events held in the community, for instance sharing discussions in a special synchronous discussion specifically for the new coach members for the entire community (e.g., “The portion of the conversation that took place in the Chat feature has been saved, and you can access it here …”).

Following the analyses of power users’ behaviors and focal topics for the conversation through which they were connected to other members, exploring textual data by LIWC enabled understanding of another aspect of discourse. LIWC developed by Pennebaker’s team is a computerized text analysis program to summarize corpora in terms of word usage and its psychological characteristics. The key feature is the dictionary that is composed of almost 6,400 texts that identify various categories of linguistic or psychological aspects of language usage. Then, all entries are assigned to one or more categories, resulting in a summary with approximately 90 variables (Pennebaker, Boyd, Jordan, & Blackburn, 2015).

The present paper reports part of those summary variables. Some foundational variables include simple word count in each unit text file (hereafter WCPS), and three general descriptor categories such as words per sentence (WC), percent of target words capture by the dictionary (Dictionary), and percent of words that greater than six letters in length (WC>6 letters). Besides, variables produced by the LIWC2015 include ones tapping linguistic dimensions (e.g., percentage of words that are auxiliary verbs), psychological constructs (cognition), personal concern categories (e.g., leisure activities), and informal language markers (e.g., netspeak) and punctuation categories (e.g., period).

Table 1 presents part of results by which we could better understand the nature of discourse in which the participants of the two VPCs were involved. To get a sense of the degree to which the outstanding characteristics are in terms of particular linguistic or psychological aspects, the table includes parts of Pennebaker et al (2015)’s results from analyzing text samples used by a variety of studies. We chose Blog, Twitter, and NY Times for purpose of comparison with texts in the present study.

Table 1. LIWC2015 ResultsStudy Sample Pennebaker et al (2015) Corpus Samples

Mentor (Obs. 19)Mean (Min ~ Max)

EL Coach (Obs. 78)Mean (Min ~Max)

Blog Twitter NY Times

WC 730.26 (11~ 1800) 209.27 (2 ~ 2196) 3206.45 660.24 744.62

WCPS 15.79 (5.5 ~ 20.29) 12.95 (1 ~ 23.13) 18.4 12.1 21.94

Dictionary 87.81 (76.19 ~ 91.44) 83.94 (57.14 ~ 100) 85.79 82.6 74.62

WC>6 letters 20.71 (10.68 ~ 25) 24.99 (0 ~ 57.14) 14.38 15.31 23.58

Articles 6.57 (0 ~ 9.62) 6.01 (0~14.29) 6 5.58 9.08

Preposition 14.36 (9.62 ~ 19.05) 12.36 (0 ~ 21.74) 12.6 11.88 14.27

Conjunction 5.12 (0~ 7.77) 4.76 (0 ~ 14.29) 6.43 4.19 4.85

? mark 0.61 (0~ 2.5) 1.01 (0 ~ 8.33) 0.59 1.4 0.15

Assent 0.15 (0 ~ 0.65) 0.44 (0 ~ 6.82) 0.33 1.82 0.05

I 4.07 (0 ~ 9.09) 3.54 (0 ~ 14.29) 6.26 4.75 0.63

We 1.67 (0 ~ 9.09) 1.91 (0 ~ 10) 0.91 0.74 0.38

The Mentor Network’s corpora from 19 members appear to be relatively small: Word counts per person averaged 730.26 and ranged from 11 to 1800 while word counts per sentence for each person have the average of 15.79 and the range from 5.5 to 20.29. The EL Coach Network with 78 participants who contributed to discourse has smaller overall WC and WCPS than the Mentor Network. Given that both text samples came from discussion forums for approximately two years participation, the results of smaller corpora than two of Pennebaker et al (2015)’s three comparison samples in length and in sentence length deserves special attention in program improvement.

This is unsurprising given the expectation of “authoring” in VPCs’ discussion forums. Blog posts and news articles are to be authored by an individual who has a motivation to disseminate something he/she would like others to read, whereas discussion forums are collectively authored as a result of social interactions by exchanging questions and responses or opinions relatively in a short length of unit posting. Nevertheless, we may very safely assert that improvement needs in a design feature by which we intend to scaffold richer social and intellectual participation

(Grossman, Wineburg, & Woolworth, 2000), which will end up with lengthy corpora. For that purpose, the collaboration and participation norm may be changed to incorporating the blogging function into the discussion forum, in other words, the VPC could grant a special authorship role to members for the topic they have a good knowledge about.

According to Tausczik and Pennebaker’s LIWC validation study (2010), proportions of prepositions (e.g., to, with) or conjunctions (e.g., and, also) could reveal a depth of thinking. In this vein, the present study text samples show a complexity at a similar degree to either of Blog or NY Times sample. Additionally, EL Coach sample shows greater proportions of question marks or assent-related words (e.g., agree, OK, yes) than NY Time and Blog samples, which would illustrate the VPC context where social coordination behaviors and group process occur as a socio-constructive space.

The LIWC’s four summary variables could shed insight into underlying psycho-linguistic characteristics of discourse--analytical thinking (Analytic), clout (Clout), authenticity (Authentic), and emotional tone (Tone) in the language usage. Unlike other summary variables, the calculation of those four variables is not transparent (i.e., there is no examples of words or word stems to define individual variables), but instead derived from the process of standardization against the large comparison sample in the development team’s corpus archive (Pennebaker et al., 2015). The present study also observed the nature of discourse focused on its cognitive process by the use of such variables as Insight (e.g., think, know), Causation (e.g., because, effect), Discrepancy (e.g., should, would), Tentative (e.g. maybe, perhaps), Certainty (e.g., always, never), Differentiation n (e.g., hasn’t, but, else).

Figure 2 displays the results in graphical form with box and whisker diagram and red dots for outliers. The two plots on the left are for Mentor Network and the others are for the EL Coach Network. Per network, the first box and whisker plot (top panel) displays results of the four linguistic process summary categories on a scale from 0 to 100, while the plot in the bottom panel of figure shows frequencies of words defining six categories of cognitive processes.

Figure 2. Linguistic Processes Summary and Cognitive Processes Mentor Network EL Coach Network

In linguistic processes summary, the greatest estimate on emotional tone category stands out given that the median, the upper quartile, and the upper extreme appear to be higher (closer to 100) than other categories’ in both networks. This is related to overall emotional positivity with on average, participant’ greater use of positive words (4.37% of individual text data sets in Mentor and 5.13% in EL Coach) than those of negative words (0.34% in Mentor and 0.26% in EL Coach). This emotional positivity appears to come from communications to appreciate shared resources and to celebrate collegiality.

The second greatest averages were found in the variable of Analytic for the Mentor Network and the Clout for the EL Coach Network. Unlike other variables that are calculated by the frequency of particular words, the calculation of the four linguistics process estimates are based on an algorithm that is unknown to LIWC users, but two studies

using LIWC will help us interpret those results. In Pennebaker and colleagues’ study (2014), the study team used relatively more use of articles and prepositions and less use of such function words as pronoun, auxiliary verb, conjunction, adverb, and negation as a proxy of analytic process of cognition in college admission essays. Using those function words, we found that Mentor Network sample was characterized as greater than Blog and Twitter samples in terms of the average proportion of article and similar to NY Times sample for the preposition (see Table 1), which of characteristic would feed into the great rate in the Analytic variable.

The Clot variable is related to hierarchy in the group of people, leadership regardless of formal hierarchical positions, and/or collectively-orientedness. Relatively less use of first-person singular (I in Table 2) and more use of first-person plural (We in Table 2) are some of factors to gauge the type of psychological process behind language use (Kacewicz, Pennebaker, Davis, Jeon, & Graesser, 2014). Both datasets in the present study indicated greater rates of “We” words than any of three LIWC samples. Additionally, the EL Network showed a slightly greater estimate than the Mentor Network, suggesting that it successfully functioned as a socio-constructive space through being more collectively oriented rather than being personally oriented. This could be evidence of shared leadership among EL Network members, at least by power users, based on their psycho-linguistic characteristics.

The authenticity component appears to fall behind the other linguistic process components. The authenticity is used to capture language use that is associative with sharing real experiences. Pennebaker et al’s Blog sample indicated the authenticity as the greatest linguistic process (Authentic 60.93 > Tone 54.5 > Analytics 49.89 > Clout 47.87). By contrast, the present study samples’ authenticity estimates are relatively low in comparison with other linguistic process variables (i.e., the median, the lower quartile, and the lower extreme closer to zero in both networks). This could be construed as psycho-linguistic characteristics of greater distance individual members from the discourse per se when they share professional topics than personal stories. Nonetheless, this results indicates an area for program improvements. In the PLC context, according to the study’s conceptual framework, authenticity means practical, authentic, and situated conversations using actual practices, samples, student work, and/or recordings. Therefore, authenticity may be improved by including relevant topics (e.g., discussing about an actual student progress chart to get practical solutions) or design features to promote this type of conversation (e.g., Member blogging) deserves consideration.

The box and whisker plot in the bottom panel of figure 2 summarizes results for categories representing the cognitive process behind language use. In both networks, most of the words used are those are associated with variables of Insight, Tentative, and Differentiation. The Insight category consists of 259 words including “think” and “know”, the Tentative is composed of 178 words including “maybe” and “perhaps”, and the Differentiation is defined by 81 words such as “but” and “else”. It is not surprising that members often use Insight words in sharing various ideas on given topics, but the use of cautious words gives a detailed insight into the linguistic characteristics of VPCs’ discourse: that is, members put forth an idea as a claim, rather than as a definite answer. Thus, what is known could change as new discoveries were made, ideas should be open to various interpretations, and thus discussion becomes a space for collective intelligence. Lastly, the variable of Differentiation that may signal psycho-linguistic process focused on meaning shifts to correspond to situation shifts stood out as the third top variable among six cognitive process, however not to the extent used in Pennebaker et al’s Blog sample (Mentor = 2.67, EL Coach = 2.13, Blog = 3.31, Twitter = 2.62, and NY Times = 2.03) .

As the final stage of text-mining, the study explored discourse focused on content words, specifically content being conveyed through the communication behavior. Word clouds provided a useful tool to visually summarize big words that indicate focal points around which members communicated. Figure 3 is the word cloud presenting the keywords most frequently encountered in discussion forums. In the case of EL Coach Network, two separate word clouds were generated for general topics and curated contents. Note that all word clouds were created after the text stemming process for such texts as numbers, English common stopwords, and punctuations and in this process functional words were eliminated from the content word analysis, which enabled minimized redundancy of two stages of text-mining.

Figure 3. Word Cloud Mentor Network EL Coach Network--General Topics EL Coach Network--Curated Contents

The Mentor Network members most often uttered “student”, in proximity to “online” and “course.” Accordingly themes related to student learning and/or change appear to dominate the discourse. More specifically, focal topics included (a) powerful avenues to success in the online-learning environment and (b) effective ways to intervene if a student fell behind in a course. Observations of corpora containing those keywords however revealed that the community lacked in-depth conversations that engaged members with student work samples, artifacts collected from the classrooms, or specific examples of strategies for monitoring students’ progress, which might have led to a discourse of specific pedagogical change.

Another keyword, “mentor” serves to indicate that the VPC enabled members to have an opportunity to share reflections on online education and their professional identities within that context. It can be justified by the keyword’s highly correlated words (i.e., word correlation indicating which pairs of words co-appear within sections in relative to the extent to which they appear separately). Those are “amount,” “golden,” and “maximum” and conversations with them shaped the content of discourse regarding mentors’ caseloads, duties, and commitments. Talks were not simply to seek “a golden number,” but instead extended to reflecting upon various school contexts.

In the EL Coach, the textual data was organized in two ways: one for general discussion forums, and the other for threads prompted by content curated, Essentials. The community’s most frequently uttered word was “coach” which was prominent in discussions about effective coaching practices. Relevant conversations covered focal topics regarding student learning and/or change. Also in-depth conversations focused on pedagogical change stood out such as mentionings about data-collection practices for student achievement and teacher instructional practices. Other key words, “will” and “thank”, appear to justify collegiality and supportive and shared leadership exhibited by the EL Coach community. The word of “thank” was for the appreciation expression and threads contained such remarks as “I could send you what that looked like if you would like an example,” or “I would like to see examples of the surveys you sent out to staff.” The word “will” and its closely related terms such as “share,” “collaborate,” “ reach out to,” and “willing to” reiterated that this VPC’s members devoted a great deal of their discourse to sharing resources and expertise and to collaborating as a team.

The third word cloud is for forums about pre-determined contents. In it, new key words such as “read,” “book,” and “word” stand out, suggesting that curated learning materials could help members redirect their focus of discourse, scaffold in-depth collective learning, and in turn enhance cognitive outcomes in PLCs. In corpora containing the keyword “read” most noticeable are such phrases as “one way to think about,” “I would love to chat about,” and “does anyone have any other”. It suggests that predetermined contents could serve as an anchor that enables members to acquire new information, connect it to their existing practical knowledge, bounce ideas off each other, seek feedback from others’ perspectives, and in turn, re-create knowledge.

ConclusionsThis study has attempted to sketch out the characteristics of network and discourse of educators when they become networked through VPCs. First, this research shows the three ways of researching participations in VPC activities. Discussion forums were useful data sources regarding how members were connected in the community, what topics were crucial in their process of collective knowledge development, and what psycho-linguistic characteristics stood

out behind educators’ discourse in VPC contexts. Overall, the study identified the strong potential of VPCs – and their discussion forums in particular – as hubs for the social constructivism approach to isolated educators’ professional needs (Booth, 2012, Ostovar-Nameghi & Sheikhahmadi, 2016).

Results from social network analysis highlight a variety of communication behaviors that are related with roles in which the facilitator or the moderator would play to lead meaningful and goal-oriented dialogues. Two types of text-mining technique were useful to unveil the nature of discourse. Content analysis using word cloud revealed crucial topics for the two types of educators: for on-site mentors, the student was the main focus in discourse focused on how to best serve them in particular situations, whereas for EL coaches, the position per se and resource share were key words resulting in dialogues focused on how to best perform their specialized roles. The study also found that predetermined learning materials could prompt members to develop specific goal-oriented dialogues, in this case, reading instructions. The LIWC analysis indicated a variety of social and psychological processes by which members shaped the discourse, participated in collective learning, and came to bolster professional identity as educators.

The results also suggest that several aspects of these two VPCs were ripe for improvement. In addition to noticeable numerical imbalances between these communities’ total enrollees and their active participants, some promising initial postings were followed by less thought-provoking feedback or questions. Also, both VPCs were marked by a relative lack of inquiry-based interactions by which the community is more likely to tap into knowledge and cognitive processes related to the authenticity component. To cultivate and sustain more meaningful and goal-oriented conversations, these communities’ design components and day-to-day practices need to be improved.

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Appendix. Conceptual frameworkMotivation Participants’ reasons for participation

Joint or Shared values and vision Common needs and interests

Leadership Supportive leadership: external leadership supports Shared leadership: opportunity for distributed leadership within communities

Authenticity Practical, authentic, and situated activities and/or tasks Identifying  individual focal point for action research or  specific aspects of practice that

should be improved. Bringing evidence collected from the classrooms (i.e., actual practices, e.g., samples, student

work, recordings) to lead the discourse and to analyze the data collectively Hearing practical solutions

Collegiality Describing people and working together on a regular basis (i.e., collaborating) Responsibility for other team members and accountability to the group Developing professional friendship and networking Binding long term members and newcomers into a social entity: new comers with new ideas

gradually move towards the center of it from the periphery A sense of community (e.g., meaningful discussion)

Collective learning

Knowledge being created, shared, organized, revised, and passed on within and among the communities

Bouncing ideas off of and share feedback from others’ perspective Communal resources (e.g., routines, articles, sensibilities, artifacts, vocabulary, style) are

developed and archived in the community Involving outside experts, funded conferences, study program to continue to bring in new

ideas Being research-oriented and experiencing Inquiry approach for the purposes of improving

practices: a greater linking of theory with practice Learning new process and having a new perspective

Focused on student outcome

Professional change leading to student change in academic achievement, engagement and academic interest, participation, deep learning, problem-solving, creativity and more

Focused on specifically targeted groups (e.g., struggling learners, student with special needs or from low SES background)

Affective outcomes: becoming passionate about their learning, change in learning disposition (e.g., mindset), self-confident growth, responsibility for learning, learning more purposefully, etc

Social outcomes: connectedness and collaboration, collaboration, peer supporting, and more Other outcomes: skills of research, personal management (e.g., well-organized),

independence, using resources more effectively, and moreLearning Outcomes

Cognitive outcomes: professional knowledge that is useful to their professional role but not directly related to daily job activities, educational philosophy, technologies in the classroom, efficiency (e.g., making their work more efficient or streamlined), and more

Affective outcomes: Emotion, disposition, habits, mindsets, attitudes toward professional learning, confidence (e.g., willingness to take risks and try new things), and more

Social outcomes: the value of having a community of educators and being more likely or willing to work collaboratively

Professional identity: becoming a more reflective practitioner and reinvigorated about profession

Pedagogical change: examination of student work process and product, use of assessments, practice of progress-monitoring, using new strategies and more integrated approach, and more

Format Singular component vs. multifaceted nature Blended format Real time collaboration

Technology & Skills

Use of and challenges with technology for participation and engagement Learning strategies to actively engaged with PLCs