Social Capital and Faculty Development in Higher Education

Social Capital and Faculty Development in Higher Education | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Social Capital and Faculty Development in Higher Education Brad Curabba This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7832545/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study examines the role of social networks in faculty development. Grounded in Social Learning Theory and Social Capital Theory, the study explores how collaborative ties provide access to resources, mentorship, and innovation, while barriers like isolation and workload constraints limit their potential. Employing a mixed-methods design at the American University of Sharjah, UAE data were collected from 41 faculty surveys and 8 in-depth interviews, representing diverse ranks, disciplines, and experiences. Quantitative analysis, including a Social Capital Index, revealed patterns of network influence on engagement, while qualitative themes illuminated mentorship's role in fostering student-centered teaching. Integrated findings highlight that robust networks align with institutional goals for teaching excellence, but systemic issues like heavy workloads undermine social capital. Faculty development social networks social capital teaching practices higher education Introduction In recent years, there has been a heightened focus on the quality of teaching within higher education, as institutions face increasing accountability from students, families, and public stakeholders. Despite this, the academic culture in many institutions continues to prioritize research productivity over teaching effectiveness, often leaving faculty members with limited resources for enhancing their instructional practices (Chronicle of Higher Education, 2024 ). When teaching is evaluated, annual reviews and the tenure and promotion processes tend to lack the rigor in differentiating between an excellent teacher and an average teacher, while student course evaluations remain unreliable in effectively evaluating a professors’ teaching performance. This makes it almost impossible to identify what is happening in the classrooms at university campuses across the United States. Additionally, a widespread movement to address this problem has never materialized, as recent studies indicate (Wright, 2023 ) only 26% of higher education institutes have a dedicated teaching center or faculty development center on campus. Furthermore, traditional, top-down faculty development programs have long been the norm among faculty development interventions. One day workshops, short sessions, or lecture-based courses are still widespread among many faculty developers. These types of interventions have been shown to have marginal influence on the quality of faculty instructional methods or performance. To add to the problem, according to a report by Cengage ( 2024 ), 70% of all faculty in higher education in the United States are adjunct instructors, who teach more than half of all college courses in the country. Adjunct instructors often receive fewer teaching resources or have less access to faculty development support services. As these forces converge on universities around the world the study of faculty development has evolved into a broad field aimed at improving teaching, research, and service responsibilities across diverse academic contexts. However, as this dissertation will argue, formal faculty development programs may overlook the critical social dynamics and peer support systems that underpin authentic professional growth. Social networks within institutions—comprising both formal and informal relationships among colleagues—offer a valuable but underutilized channel for development. The problem addressed by this study is the disconnect between faculty development practices and the social, collaborative nature of professional growth in higher education. Traditional, one-size-fits-all development programs often fail to engage faculty in meaningful ways, lacking the flexibility and social interaction needed for sustainable improvement. The study seeks to explore how social networks and informal relationships within academic departments can contribute to faculty development, providing faculty members with the peer support and social capital needed to improve teaching quality. Literature Review Social Networks and Faculty Development Research has shown the capacity of established networks to enhance teacher practice more efficiently than traditional models of faculty development. Pataraia et al. ( 2013 ) argue that personal networks equip academics with a diverse pool of knowledge and skills about teaching, offering both professional and emotional support. Van Waes et al. ( 2015 ) examined the way in which faculty networks corresponded with faculty instructional development. Buckely and Nimmon (2020) used a qualitative social network approach to explore how teaching faculty’s relationships influenced their learning about teaching. Buckely and Nimmon identified four ways social networks influenced faculty learning about teaching: (1) enabling and mobilizing knowledge acquisition, (2) contributing to professional identity formation around teaching, (3) providing opportunity for expression of vulnerability as a prerequisite for deeper sharing and (4) augmenting and scaffolding learning from multiple knowledge sources. Buckely and Nimmon argue that the use of a social network lens in this study allowed them to deepen and transform their thinking about faculty development practices. Significant Conversations To demonstrate the significance of personal networks and significant conversations, Roxå and Mårtensson ( 2009 ) explored the conversational partners that university teachers have and the nature of these conversations. The intention of their study was to identify smaller networks in relation to teaching within a larger social context, and to determine if such networks exist, and how teachers should be able to report on how they differentiate between colleagues while talking about teaching. Roxå and Mårtensson hypothesized that teachers can name rather few colleagues with whom they have sincere discussions about teaching, and that they express themselves differently while talking to colleagues not included among those few. They distributed a questionnaire to 109 academic teachers and asked them to describe who they have conversations with about teaching and learning and detail about the nature of those conversations. The results showed that university teachers rely on a limited number of individuals to test ideas or solve problems related to teaching and learning. They argue that the existence of these networks has implications for leadership and management as well as for academic development. As they state, “...by recognizing significant networks it becomes possible to further understand why policies, organizational strategies or bureaucratic requirements have such a limited impact on university teaching” (p.557). Pataraia et al. ( 2014 ) extends the work of Roxå and Mårtensson by examining a wider range of aspects of conversations about teaching within networks. Pataraia et al. applied Social Network Analysis to determine who academics talk to about their teaching, the main themes of those conversations how often those conversations take place, and the factors that motivate those conversations. In sum, findings showed that through personal networks academics acquire various kinds of resources (new ideas and teaching materials), share knowledge and experience with one another as speculated by Social Capital Theory. The interviewees appreciated these as benefits that provided incentives for networking. Overall, respondents used their personal networks for exchanging ideas, discussing teaching-related problems and obtaining professional advice (Pataraia et al. 2014 ). Cross-Disciplinary Participation In the literature reviewed on significant conversations it was shown that conversations on learning and teaching are typically encouraged when conversing teachers come from various disciplines and departments. For instance, Dorner and Belic ( 2021 ) describe how their institution invested in organizing regular lunch-time discussions about learning and teaching, which were attended over eight years by more than 500 faculty members across many departments. Locating these conversations in the Center for Teaching and Learning reinforced the importance of situated pedagogical reflections. Making these conversations interdisciplinary helped to overcome the hierarchies that often hinder teaching development within a department. Dorner and Belic also report that over time these pedagogical conversations evolved from being mostly focused on individual development, to facilitating collective learning and institutional changes. Mooney and Miller-Young ( 2021 ) engaged teachers in what they describe as the educational development interview. In their study Mooney and Miller-Young show meaningful outcomes from these interviews, illustrating the potential of structured interviews to support conversation-based cross-disciplinary academic development. Trustful Relationships Simon and Pleschová ( 2019 ) offer a definition of trust as: “a reaction to risk and uncertainty and as one actor’s (the trustor’s) psychological state that comprises of the willingness to accept vulnerability to another individual (the trustee) based upon positive expectations regarding both the intentions and the behavior of the trustee” (p.4). In their study they explored the impact of an academic development course on participants’ most significant teaching relationship at their home institutions and, indirectly through this, their teaching practice. Simon and Pleschová found that participation in an academic development program increased the trustworthiness of doctoral students by making them expert conversation partners. In some cases, program attendance also decreased participant trust in certain colleagues such as supervisors, course leaders, or other faculty members. Lack of trust was found to limit teaching conversations in general and to constrain attention to certain topics in particular, including such pivotal issues as students, the syllabus, and self-reflection on teaching. Spitzner and Meixner ( 2021 ) explored how collaborative ethnography gave form and depth to regular talk and encouragement to reconsider teaching-related assumptions, particularly related to trust and vulnerability in teachers’ pedagogy. They argue that by cultivating collaborative autoethnography faculty developers and centers of faculty development would open brave spaces for civil dialogue, mentoring, intergroup dialogue, story circles, and communities among same and diverse peers. Boschman et al. (2021) explores efforts to stimulate significant conversations through a Scholarship of Teaching and Learning (SoTL) Community of Practice (CoP) amongst a diverse group of professors and professional staff in a College of Applied Arts and Technology in Ontario, Canada. Participants shared their reflections on the formation of significant networks and the start of significant conversations through the founding of a Community of Practice. Conducive Spaces Thomson and Barrie ( 2021 ) explore how academics use informal conversations to overcome unsupportive teaching contexts. They find that proximity, similarity, and camaraderie help academics to have significant conversations about teaching. In their study, a frequently mentioned positive factor is a conducive space for academics to talk about teaching – a corridor, meeting room, coffee machine, or other place that fosters informal discussion. Thomson and Barrie argue that space alone is not sufficient for meaningful talk and that trustful relationships, often friendships, also play a crucial role in enabling significant conversations about teaching in an institutional environment that privileges research. Ndlovu et al. (2021) created a space, Room32, for themselves at the outskirts of their campus where they refurbished an old, forgotten room. They explain how conversations in Room32 contrasted with the much less helpful frontstage conversations that dominated other university settings. Ndlovu et al. argue that the liminality in Room32 sparked meaningful conversations and change that were not possible elsewhere on campus. Gachago et al. ( 2021 ) analyze a convenient space they found for academic development and pedagogical conversations during the disruption of COVID-19: WhatsApp. The authors describe how this group retreated to a ‘third place’ after they could not continue their usual ways of working together. They used this virtual space to build courage and support for each other, and to exchange ideas about effective practices in new conditions. The authors conclude by sharing their understanding of the mission of educational developers: to transform institutions into caring places of teaching and learning. Research Questions Research Q1: What institutional conditions contribute to the enhancement or hindrance of social capital of faculty members? Research Q2: What effect does social capital have on faculty development (significant conversations, teaching and learning interventions) Research Q3: What effect do personal characteristics (age, gender, experience level, discipline) have on one’s social network ties? Methodology Design Convergent Parallel Mixed Methods This study adopted a convergent parallel mixed-method design (Creswell & Clark, 2018) to answer the research questions. The quantitative component involved Social Network Analysis to visualize and measure the structure of faculty networks, while the qualitative component involves semi-structured interviews and focus groups to understand faculty members’ experiences and perceptions. The rationale for using a mixed-method design was to integrate network-level data with rich qualitative insights, providing a more comprehensive picture of the factors influencing social networks within the academic context. Implementation of the Study Study Site This study took place at The American University of Sharjah, a private, non-profit, liberal arts university in Sharjah, United Arab Emirates. The university is one of only a handful of American style liberal arts colleges in the MENA region. The study site was chosen out of convenience; the researcher has been employed by the university since 2015. According to AUS’s internal research group, as of Fall 2023 there were 5,876 students enrolled. 5,233 of those students were enrolled in a four-year bachelor’s program, 412 in a master’s program, 119 Ph.D. students and 112 were enrolled in the universities Achievement Academy, which specializes in English language preparation. The American University of Sharjah is one of the most diverse universities in the world, with over 97 nationalities represented among the student body. The makeup of the faculty community is also very diverse with faculty coming from 47 different countries, 43.5% of whom are US or Canadian citizens. The Population of the Participants The participants were selected from the existing community of faculty members at the American University of Sharjah. Currently there are 337 full-time faculty teaching in four colleges and various departments. The College of Arts and Sciences has the most faculty with 147, the College of Engineering has a total of 87 faculty, the School of Business Administration has 65 faculty and the College of Architecture, Art and Design has a total of 38 faculty members. Sample Selection Method This study utilized a convenience sampling approach to select participants from the American University of Sharjah (AUS). Convenience sampling was chosen due to the practical considerations of participant accessibility and the exploratory nature of the research. As Etikan et al. ( 2016 ) explain, convenience sampling allows researchers to gather data quickly and efficiently, especially in settings where participants are readily available and willing to engage. The sample comprises an interdisciplinary group of faculty members at AUS, drawn from various departments to ensure diversity in the social network structures being analyzed. Results Participant Demographics Table 1 presents demographics for 41 survey respondents and 8 interviewees (a subset of survey participants) at the American University of Sharjah. The sample was diverse across academic discipline, gender and years of teaching experience. For the interviews, the Colleges of Engineering and the School of Business Administration were underrepresented. Table 1 Participant Demographics (N = 41 Surveys, N = 8 Interviews) Demographic Category Survey (n, %) Interview (n, %) Gender Female 15 (39.5%) 3 (37.5%) Male 26 (60.5%) 5 (62.5%) Rank Assistant Professor 9 (20.9%) 2 (25.0%) Associate Professor 14 (32.6%) 3 (37.5%) Instructor 1 (2.3%) 0 (0.0%) Professor 9 (20.9%) 2 (25.0%) Senior Instructor 5 (11.6%) 1 (12.5%) Visiting Professor (any rank) 4 (9.3%) 0 (0.0%) College (Discipline) College of Art, Architecture and Design 6 (15%) 2 (25%) College of Arts and Sciences 16 (39.5%) 4 (50%) College of Engineering 9 (20.9%) 1 (12.5%) School of Business Administration 11 (25.6%) 1 (12.5%) Years of Teaching Experience 1–3 Years 2 (4.7%) 1 (12.5%) 4–7 years 2 (4%) 0 (0%) 8–10 years 4 (9.3%) 1 (12.5) More than 10 years 34 (81.4%) 6 (75%) Social Capital Index To better understand the social structures that shape faculty development at the American University of Sharjah (AUS), this study employed a Social Capital Index (SCI) to provide a quantifiable measure of each participant’s access to and engagement with professional networks, as well as the institutional conditions that affect access to social capital. The Social Capital Index was calculated as the mean of survey items assessing network size and diversity, frequency of conversations, trust and reliance on colleague feedback, and shared pedagogical goals. SCI ranges from 1 (low) to 5 (high). Higher SCI scores indicate conditions fostering social capital (e.g., supportive departments, supportive administration, access to colleagues and trust in receiving and giving feedback on teaching), while lower scores suggest barriers (e.g., limited collaboration opportunities, lack of shared space, workload). Table 2 presents the Social Capital Index (SCI) of each of the survey respondents. The overall mean of 3.40 (SD = 1.50) indicates moderate to high social capital throughout the university. The college of Art Architecture and Design (mean 3.54) enhanced their faculty’s social capital through classroom design, collaboration and studio classes. The College of Arts and Sciences (mean 3.51) also had a moderate to high level of social capital mostly fostered by department level collaboration and supportive department heads. The School of Business Administration and the College of Engineering had lower levels of social capital with workload and lack of institutional support mentioned as barriers. Table 2 Social Capital Index (SCI) Scores by Faculty Characteristics (n = 42) Group N Mean SCI (1–5) SD Notes Overall 41 3.40 1.05 Moderate social capital enhanced by supportive conditions but hindered by barriers like workload. Assistant Professor 9 3.53 0.62 Moderate enhancement through collaboration. Associate Professor 13 3.35 0.60 Varied; enhanced by department support but hindered for some. Instructor 1 2.33 N/A Low, indicating potential hindrances like limited resources. Professor 9 3.27 0.66 Consistent; enhanced by experience but hindered by time constraints. Senior Instructor 5 3.67 1.00 Moderate-to-high, supported by institutional structures. Visiting Professor (any rank) 4 3.42 0.54 Varied by department culture. CAAD 6 3.54 0.66 Enhanced by collaborative studio environments. CAS 16 3.51 0.70 Moderate-to-high, fostered by departmental interactions. CEN 9 3.12 0.58 Lower; hindered by workload or limited support. SBA 11 3.39 0.67 Moderate; barriers like heavy loads may hinder social capital. Institutional Conditions RQ1: Research Q1: What institutional conditions contribute to the enhancement or hindrance of social capital of faculty members? Table 3 below synthesizes the quantitative survey data (N = 41, including means, SDs, and percentages from selected survey responses) and network outcomes with qualitative themes and quotes from interviews and open-ended survey responses. As discussed above, this integration reveals how institutional conditions—such as leadership, PD programs through the CITL, workload, and structural support—shape faculty social capital, addressing RQ1: "What institutional conditions contribute to the enhancement or hindrance of social capital of faculty members?" The analysis highlights convergences (e.g., aligned data on workload hindrances) and divergences (e.g., quantitative showing moderate support but qualitative emphasizing burnout), drawing on Social Capital Theory to interpret network strength (e.g., trust, diversity) as influenced by these conditions. The data converges strongly on enhancements through supportive leadership and professional development programs. Quantitatively, high selection of supportive HODs (63.4%) and department value for peer talk (41.5% high) correlate with robust trust in colleagues (76.0% high) and moderate network size (57.0% high), suggesting these conditions build relational and structural social capital. Qualitatively, this aligns with the "Supportive Leadership/HOD" theme (6/8 interviews, 8/30 surveys), where faculty describe HODs as catalysts for collaboration, as in "Our department head is amazing at promoting collaboration... [but] our workload is so extreme" (Interview - SNA Study Interview). This convergence indicates that institutional leadership enhances social capital by enabling trust and informal networks, though workload moderates the effect. Workshops and CITL programs demonstrate moderate convergence as enhancers. Quantitative data shows 39.0% selection for teaching workshops and 31.7% for peer mentoring, linking to moderate network diversity (mean 3.2, 50.0% high) and strategy adoption (mean 3.8, 62% high). Qualitatively, the "Workshops/CITL/PD Programs" theme (5/8 interviews, 12/30 surveys) reinforces this, with faculty praising CITL for innovation, for example, "CITL workshops have been much better about introducing us to more innovative teaching methods". A slight divergence appears in qualitative accounts of time barriers, such as "faculty are just too busy", which underscores how institutional professional development boosts cognitive social capital through shared pedagogical goals but faces practical limitations, such as workload and a formal incentive structure. Hindrances reveal strong convergence, particularly for heavy workload and time constraints. Quantitatively, low workload allowance (73.2% low) and ~ 60% citing workload in barriers correlate with lower network diversity (20.0% low) and size (14.0% low), indicating reduced structural social capital. Qualitatively, the "Heavy Workload/Time Constraints" theme (8/8 interviews, 18/30 surveys) echoes this, with consistent reports of burnout, e.g., "Reduce the teaching load... The current trend at AUS is not realistic and will only result in reducing the quality of teaching " and " Workload and time constraints limit networking ". Both sets of data converge on this idea as a major impediment to the development of faculty social networks and professional development opportunities. Additionally, the lack of formal structures and incentives shows convergence with some nuance. Quantitative data highlights low formal structures (61.0% low) and low selections for retreats (7.3%) and shared spaces (, 4.9%), linking to moderate trust (10.0% low). Qualitatively, the "Lack of Formal Structures/Incentives" theme (6/8 interviews, 14/30 surveys) aligns, with calls for incentives, e.g., "No incentives for teaching... many colleagues do not even care about teaching" and "No formal structures for teaching/practice conferences ". “ I don't, I don't think we're formally encouraged in any way to learn from one another. I think we're kind of put in our like, in our little box, and we're told this is what you do. And so if you are personally interested to learn from one another. You need to go out of your way to do this .” Convergence is evident in both datasets where emphasis was placed on policy gaps hindering relational capital, but qualitative data provides more depth on research-teaching imbalance. Siloed departments and isolation also converge as a hindrance. Quantitatively, low interdisciplinary opportunities (58.5% low) correlate with lower diversity (20.0% low). Qualitatively, the "Siloed Departments/Isolation" theme (5/8 interviews, 9/30 surveys) supports this, e.g., "We are pretty insular... engineers for sure" and "AUS doesn't do anything. Outside of faculty meetings or committee work, you don't see faculty at all" . This convergence highlights institutional silos reducing structural social capital, with no major divergence—both types stress departmental independence. Table 3 Integrated Quantitative and Qualitative Findings for Institutional Conditions and Social Capital Aspect Quantitative Support Qualitative Support Integration Notes Enhancement: Supportive Leadership/HOD 63.4% selected 41.5% high. Supportive HOD theme (6/8 interviews, 8/30 surveys): "Our department head is amazing at promoting collaboration". Converges: High HOD selection enhances trust/networks ;(qual. shows HODs fostering collaboration, but limited by workload (e.g., "extreme workload") Enhancement: Workshops/CITL/PD Programs 39.0% selected; (Workshops): 31.7%. selected (Peer Mentoring) Linked to moderate network diversity). Workshops/CITL theme (5/8 interviews, 12/30 surveys): "CITL workshops have been much better about introducing us to more innovative teaching methods”. Converges: Moderate selection for workshops enhances innovation/networks; qual. praises CITL but notes time barriers Hindrance: Heavy Workload/Time Constraints 73.2% low, ~ 60% cite workload. Linked to lower network size Heavy Workload theme (8/8 interviews, 18/30 surveys): "Reduce the teaching load... The current trend at AUS is not realistic". Converges: Low workload allowance hinders networks qual. emphasizes burnout Hindrance: Lack of Formal Structures/Incentives 61.0% low; (Shared Office Space): 4.9%; (Retreats): 7.3%. Lack of Structures theme (6/8 interviews, 14/30 surveys): "No formal structures for teaching/practice conferences". Converges: Low selection for structures hinders collaboration; qual. calls for incentives (e.g., "No incentives for teaching" in S9), tying to RQ1 institutional gaps. Hindrance: Siloed Departments/Isolation 58.5% low; Linked to lower diversity (20% low). Siloed Departments theme (5/8 interviews, 9/30 surveys): "We are pretty insular... engineers for sure". Converges: Low interdisciplinary opportunities hinder diversity; qual. notes isolation (e.g., "Outside of faculty meetings, you don't see faculty". Social Capital and Faculty Development RQ2: What effect does social capital have on faculty development? Integrated Findings for Research Question 2 Drawing on Social Capital Theory to interpret how networks influence development through knowledge exchange and practical application, the analysis reveals strong convergences. The findings, shown below in Table 4 , converge on social capital's positive effect through enhanced significant conversations. For example, quantitatively, high reliance on colleagues (mean 3.9, SD 0.9, 68% high) and ease of finding discussion partners (mean 3.8, SD 1.0, 65% high) correlate with moderate conversation frequency (mean 3.0, SD 1.1, 45% monthly or more), indicating networks facilitate insightful exchanges. Qualitatively, this aligns with the "Enhanced Significant Conversations" theme (7/8 interviews, 10/30 surveys), where faculty describe discussions leading to shared insights, for example, "Informal discussions on curriculum and psychosocial aspects of teaching” . This convergence suggests social capital fosters relational ties that enable conversations, promoting development, though qualitative data highlights time limitations (e.g., "No time for extra activities” more than the moderate standard deviations in quantitative results. Additionally, adoption of new teaching interventions shows strong convergence as a key effect. Quantitative data reveals high strategy adoption from colleagues (mean 3.8, SD 1.0, 62% high), linked to access to valuable resources (mean 3.9, SD 0.9, 70% high) and trust (mean 4.0, SD 0.8, 76% high). Qualitatively, the "Adoption of New Teaching Interventions" theme (6/8 interviews, 8/30 surveys) reinforces this, with faculty noting practical applications, such as "A colleague suggested mind maps... It worked" (P3). This data illustrates the potential of how increased social capital can positively impact collaboration among colleagues, especially peer recommendations for teaching activities and curriculum ideas. Another theme that emerged with moderate convergence was building trust and reciprocity with colleagues effects sustained faculty development. Quantitative evidence includes high reciprocal support (mean 4.0, SD 0.8, 74% high) and trust (mean 4.0, SD 0.8, 76% high), correlating with strategy adoption (62% high). Qualitatively, the "Building Trust and Reciprocity" theme (5/8 interviews, 7/30 surveys) supports this, for instance, "Peer mentoring and shared learning from colleagues". This convergence while high in the interviews, was not well supported by a vast majority of the faculty who responded to the survey. Some of the barriers where convergence could potentially limit faculty development were between conversation frequency (25% low), linking to lower reliance in some groups (12% low). Qualitatively, the "Barriers Limiting Effects" theme (6/8 interviews, 12/30 surveys) aligns, emphasizing constraints like workload, such as "Workload prevents me from attending workshops, hindering collaboration" (P2). This supports the idea of how barriers moderate social capital's positive effects. A majority of the barriers noted in both data sets were related to workload and the fact that a focus on teaching is not incentivized. In summary, the integration affirms that social capital positively affects faculty development by enabling significant conversations and interventions through trust, reciprocity, and resource sharing. These convergences dominate, with divergences mainly in qualitative depth on barriers. The findings suggest that strengthening networks could amplify faculty development and highlights the importance of focusing on building ground up, department level collaboration in order to increase social networks. Table 4 Integrated Quantitative and Qualitative Findings for Effects of Social Capital on Faculty Development Aspect Quantitative Support Qualitative Support Integration Notes Enhanced Significant Conversations High reliance on colleagues (mean 3.9, SD 0.9, 68% high) and ease of finding partners (mean 3.8, SD 1.0, 65% high); moderate conversation frequency (mean 3.0, SD 1.1, 45% high). Enhanced Conversations theme (7/8 interviews, 10/30 surveys): "Informal discussions on curriculum and psychosocial aspects of teaching" (S21). Converges: Networks enable exchanges; qual. adds depth to insights (e.g., "psychosocial aspects"), beyond quant's frequency. Adoption of New Teaching Interventions High strategy adoption (mean 3.8, SD 1.0, 62% high); linked to resources (mean 3.9, SD 0.9, 70% high). Adoption theme (6/8 interviews, 8/30 surveys): "A colleague suggested mind maps... It worked". Converges: Social capital drives practical application; both show peer influence, with qual. providing examples (e.g., mind maps). Building Trust and Reciprocity High reciprocal support (mean 4.0, SD 0.8, 74% high) and trust (mean 4.0, SD 0.8, 76% high). Trust theme (5/8 interviews, 7/30 surveys): "Peer mentoring and shared learning from colleagues". Converges: Ties support sustained growth; qual. emphasizes reciprocity (e.g., "shared learning") not fully captured in quant SDs. Barriers Limiting Effects Moderate frequency (25% low); lower reliance in some groups (12% low). Barriers theme (6/8 interviews, 12/30 surveys): "Workload prevents me from attending workshops". Converges: Barriers moderate effects; qual. adds context (e.g., workload) to quant's variability. Personal Characteristics and Social Network Ties Research Q3: What effect do personal characteristics (gender, experience level, discipline) have on one’s social network ties? Integrated Findings for Research Question 3 The findings converge on discipline shaping network insularity. As Table 5 displays, Quantitatively, the SCI varies by discipline, with CAAD (mean 3.54, SD 0.67), CAS (mean 3.50, SD 0.66), CEN (mean 3.48, SD 0.48), and SBA (mean 3.46, SD 0.70) showing moderate-to-high ties, but lower diversity (overall 20% low) suggests silos. The qualitative data reinforces the theme of department and college level silos and lack of cross-departmental or cross-disciplinary collaboration. The data suggests that CAS faculty tend to have more department level collaboration and lesson sharing than other colleges. Additionally, this convergence indicates that discipline affiliation, particularly in STEM or design fields, restricts cross-departmental ties, reducing network diversity, with quantitative variability (SD 0.48–0.70) reflecting qualitative nuances on departmental independence. Another theme which emerged from the data analysis was the fact that experience and mentorship and network strength shows moderate convergence. Quantitatively, faculty with more than 10 years of experience have a mean SCI of 3.48 (SD 0.62), slightly higher than mid-career (8–10 years, mean 3.26, SD 0.65), suggesting accumulated ties. Qualitatively, the "Experience Enabling Mentorship and Network Stability" theme (5/8 interviews) supports this, with senior faculty leveraging tenure. The convergence suggests that experience fosters mentorship and stable ties, though quantitative data shows less variation (SD 0.62) than qualitative accounts of novice reliance on diverse connections. This would suggest that longer tenure tends to restrict the adoption of new network ties, whereas newer faculty possibly seek out older faculty for guidance and advice. Interviews with more senior level faculty with 10 or more years of teaching experience reinforce this analysis. Many noted that in the beginning of their careers they were more active in both department level collaboration and cross-disciplinary collaboration. Often the theme of institutional changes or policy directions were noted as indicators for barriers, as noted in the analysis of RQ1. Gender influencing network access and dynamics reveals convergence with some divergence. Quantitatively, females have a mean SCI of 3.37 (SD 0.65) compared to males at 3.56 (SD 0.59), a slight negative effect possibly due to barriers. There as little qualitative data on the effect of gender on faculty social ties, one faculty member mentioned being the only “western woman” in her department and that she felt “isolated”. However, these themes were not explored in greater depth in the survey or interviews. Experience level moderating network diversity and growth shows moderate convergence. Quantitatively, mid-career faculty (8–10 years) have a higher mean SCI (3.26, SD 0.65) than novices (1–3 years, mean 3.78, SD N/A), suggesting diverse tie growth. Qualitatively, the "Experience Level Moderating Network Diversity and Growth" theme (4/8 interviews) supports this, with mid-career faculty building broader ties, however the most experienced faculty have a less diverse network and rely on colleague for support less often than new or mid-career faculty. Table 5 Integrated Quantitative and Qualitative Findings for Effects of Personal Characteristics on Social Network Ties Aspect Quantitative Support Qualitative Support Integration Notes Discipline Shaping Network Insularity SCI varies by discipline: CAAD (3.54, SD 0.67), CAS (3.50, SD 0.66), CEN (3.48, SD 0.48), SBA (3.46, SD 0.70); 20% low diversity. Discipline Insularity theme (6/8): (P6). Converges: Discipline creates silos, reducing diversity; quant SDs reflect qualitative emphasis on independence. Experience Enabling Mentorship SCI for > 10 years (3.48, SD 0.62) vs. 8–10 years (3.26, SD 0.65); higher stability with experience. Experience Mentorship theme (5/8): Converges: Experience builds mentorship ties; quant shows stability, qual. adds depth to senior roles. Gender Influencing Network Access SCI females (3.37, SD 0.65) vs. males (3.56, SD 0.59); slight negative effect for females. Gender Dynamics theme (3/8 Converges with divergence: Gender impacts access; qual. highlights barriers more than quant’s modest difference. Experience Level Moderating Diversity SCI 8–10 years (3.26, SD 0.65) vs. 1–3 years (3.78, SD N/A); mid-career shows moderate diversity. Experience Diversity theme (4/8): "I just finished my first year at a US" (P3). Converges: Experience moderates diversity; quant variability aligns with qual. shifts in network growth. DISCUSSION Implications The research findings from this study have many implications for faculty development in higher education. As mentioned at the outset, universities are facing many headwinds which have a negative impact on the way that teaching is valued and practiced at higher education institutions around the world. With the advent of Artificial Intelligence and Large Language Learning Models, the challenges have become even larger. The basic relevance of higher education and teaching in particular has become a common theme in media outlets and, I believe in the minds of undergraduate students. Finding relevance through social learning, building community and advancing social networks may help universities navigate these uncertain times. Implication 1: Enhance social network with institutional policy reforms Aligning with the research in the field, the findings in this study recommend for a policy shift such as reducing teaching loads from 3–3 to 2–2, supported by Gibbs and Coffey’s ( 2004 ) evidence that time availability boosts network engagement. The high percentage of faculty responses indicated that workload was a barrier to the creation of teaching related social networks (mean 1.38, 73.2% low) suggests a critical need for policy reform in this area. This is exacerbated by the fact that institutional incentives are primarily focused on research output, specifically journal articles published in the top percentile of Scopus ranked journals. These incentives are a part of end of year reviews and ‘rolling contract’ and promotion decisions. Additionally, while this study supports the idea that social network strength is essential to faculty development, the creation of formal structures, like interdisciplinary grants or teaching retreats, could mitigate silos, consistent with Trowler’s ( 2008 ) call for cross-departmental initiatives. While this study contends that the strongest social networks are those which are created from the bottom up, without clear direction and buy-in from the institution there would be very little incentive for faculty to develop new department level or inter-departmental networks. One example of this would be at AUS, where research pressure overshadows teaching, rebalancing evaluation criteria to include network-building efforts—such as crediting teaching collaborations in year-end reviews—could shift priorities, echoing Fairweather’s ( 2002 ) advocacy for holistic assessment. Implication 2: Focus on creation of shared physical spaces Implementing shared physical spaces, such as offices, lounge areas, or collaboration hubs, could significantly enhance faculty ties, addressing the low 4.9% selection rate for shared spaces (Q17_4) and the pervasive lack of conducive environments (mean agreement ~ 1.2–1.5). Defined in the literature as "conducive spaces" that foster informal interaction and trust (Thomson & Barrie, 2021 ), AUS currently offers few venues for academics to discuss teaching, a gap echoed in qualitative insights like "Outside of faculty meetings or committee work, you don’t see faculty at all" (S22). The weak correlation between lack of shared space and low trust (e.g., 12.2% overall, 16.7% in CAAD) suggests physical isolation undermines social capital, particularly in siloed colleges like CAAD (mean SCI 3.02). A pilot project converting underutilized areas into shared spaces, monitored with pre/post SCI surveys, could boost network formation. Complementing this, virtual spaces—such as Microsoft Teams channels or a dedicated Slack workspace—could extend access, aligning with Gachago et al.’s ( 2021 ) findings on mobile communities of practice in the Global South, where WhatsApp fostered collaboration despite barriers. At AUS, a virtual "teaching lounge" for asynchronous discussions could leverage the 21.9% online tool uptake, enhancing trust and breaking isolation, especially for CEN/SBA faculty, while accommodating the 3–3 teaching load constraints (mean 1.38, 73.2% low). Implication 3: Enhance social capital through structured conversations about teaching and learning An additional implication would be to leverage social capital through structured conversations (e.g., monthly teaching rounds facilitated by HODs) and interventions (e.g., peer observation programs or co-teaching initiatives) could enhance development, resonating with Wenger’s ( 1998 ) communities of practice model. The moderate conversation frequency (mean 3.0, 45% high) suggests institutional incentives, such as PD credits, small stipends, or time off, could amplify effects, supported by Quinlan’s ( 2016 ) findings on peer influence. Qualitative barriers like "Workload prevents me from attending workshops" (P2) indicate a need for flexible scheduling, aligning with global trends in faculty support (Gibbs & Coffey, 2004 ). Integrating technology, such as virtual collaboration platforms (e.g., Microsoft Teams or Blackboard Collaborate), could overcome time barriers, building on Henderson et al.’s (2011) work, especially given AUS’s hybrid teaching model post-COVID. A specific intervention could involve a semester-long virtual teaching seminar series, tracking participation and development outcomes to assess impact. These strategies could be piloted in high-SCI departments like CAS to model success for others, with evaluations using pre/post SCI surveys to measure changes in conversation frequency and strategy adoption over a 12-month period. Implication 4: Discipline specific strategies Tailoring strategies to the unique cultures and needs of different disciplines offers a promising avenue to enhance social capital and dismantle network insularity at AUS, moving beyond a one-size-fits-all approach to faculty development. Drawing on Becher and Trowler’s ( 2001 ) concept of academic tribes, disciplines like CAAD and CEN—where mean SCI scores are lower (3.02 and 3.28, respectively, with SDs of 0.44 and 0.43)—may benefit from initiatives that encourage creative cross-pollination, such as design-thinking workshops inviting input from the more collaborative humanities faculty in CAS (mean SCI 3.50, SD 0.67). Similarly, engineering departments could host interdisciplinary problem-solving forums to bridge their often-siloed structures, inspired by Trowler’s ( 2008 ) emphasis on context-sensitive interventions. With 39.0% of faculty currently engaging in workshops, there’s a foundation to build upon, but the 12.2% low trust rate (highest at 16.7% in CAAD) suggests a need for trust-building activities, like cross-disciplinary mentor pairs, as Baldwin and Chang (2007) recommend for novice support. This approach offers the change for AUS to pioneer a model of discipline-tailored professional development (PD) that redefines professional identity—perhaps through a semester-long series of symposia tailored to each college’s needs. From the interviews conducted there was strong agreement that cross-disciplinary initiatives are missing, but much needed to the academic landscape at AUS. Implication 5: Connect Scholarship of Teaching and Learning research to university research requirements The final implication which offers a strategic solution to balance the institution's strong research focus with its substantial teaching loads (3/3 for faculty, 4/4 for instructors) would be to promote and encourage research into the growing field of the Scholarship for Teaching and Learning (SoTL). The International Society for the Scholarship of Teaching and Learning offers high value journals and yearly international conferences on this growing field of research. By incentivizing SoTL, such as through grants for classroom-based research or recognizing SoTL publications in tenure evaluations, AUS could encourage faculty to explore their teaching practices, aligning with Boyer’s (1990) framework of scholarship encompassing discovery, integration, application, and teaching. This approach could transform teaching demands into opportunities for scholarly output, enhancing social capital through collaborative pedagogical research. A pilot SoTL fellowship program, where faculty document interventions like AI in classrooms, could be implemented, with metrics tracking publication rates and SCI changes over a semester. This strategy addresses RQ1's workload barriers while boosting RQ2's interventions, offering a sustainable model for faculty development in research-intensive contexts. Conclusion This study reinforces the literature on the power of social capital as a lever for faculty development in higher education. The study highlights the institution’s strengths—supportive leadership and innovative professional development programs—while identifying critical barriers, such as heavy workloads and structural gaps, that must be addressed to cultivate a collaborative teaching environment. The proposed recommendations—reducing teaching loads to 2–2, establishing interdisciplinary grants, implementing discipline specific interventions, inclusion of conducive spaces and a focus on incorporating the research principles of the scholarship of teaching and learning, offer a comprehensive roadmap for AUS to enhance faculty networks, reduce attrition, elevate teaching excellence, and improve student learning. This work lays the foundation for future research and institutional reform, positioning AUS as a potential leader in the Gulf region for innovative faculty development strategies, provided the institution invests in these changes. Through the analysis of both quantitate and qualitative data, and especially reflecting on the 8 in-depth interviews, it is apparent that there is a need and a great desire among faculty to shift the focus from an intense research output to a more nuanced approach, incorporating the ideas presented in this study: collaboration, cross-disciplinary work, focus on culture, trust and access to conversations with colleagues, and development of social networks. This dissertation hopefully advances the understanding of faculty development in higher education but also serves as a call to action for universities to prioritize its teaching community, ensuring that social capital becomes a cornerstone of academic excellence in the years to come. Declarations Ethics Approval and Consent to Participate This study was reviewed and determined to pose minimal risk to participants by the Institutional Review Board (IRB) at the American University of Sharjah. It qualified for exempt IRB approval under 45 CFR 46.104(d)(2) and (3). The protocol, entitled “A SOCIAL NETWORK ANALYSIS OF FACULTY DEVELOPMENT IN HIGHER EDUCATION” (Protocol #: 25-055), was approved on March 20, 2025, with an effective date of March 25, 2025. No external funding was received for this research. All participants provided informed consent prior to involvement. For the survey component, consent was obtained via a digital form embedded in the Qualtrics survey, which outlined the study's purpose, voluntary nature, anonymity, and data usage. Participants could withdraw at any time without penalty. For the semi-structured interviews, written informed consent was secured through signed forms, ensuring participants understood the recording process, confidentiality measures and their right to withdraw. All procedures adhered to ethical guidelines for human subjects research, prioritizing participant privacy and data security. References Becher T, Trowler P (2001) Academic tribes and territories: Intellectual inquiry and the culture of disciplines. McGraw-Hill Education Benbow RJ, Lee C (2019) Teaching-focused social networks among college faculty: Exploring conditions for the development of social capital. High Educ 78(1):67–89. https://doi.org/10.1007/s10734-018-0331-5 Buckley H, Nimmon L (2020) Learning in faculty development: The role of social networks. Acad Med 95(11):S20–S27. https://doi.org/10.1097/ACM.0000000000003627 Cengage (2024) Report on adjunct instructors in higher education. Cengage Learning Chronicle of Higher Education (2024) Trends in teaching quality and faculty development. https://www.chronicle.com Creswell JW, Plano Clark VL (2018) Designing and conducting mixed methods research, 3rd edn. SAGE Dorner H, Belic J (2021) From an individual to an institution: Observations about the evolutionary nature of conversations. Int J Acad Dev 26(3):210–223. https://doi.org/10.1080/1360144X.2021.1934687 Etikan I, Musa SA, Alkassim RS (2016) Comparison of convenience sampling and purposive sampling. Am J Theoretical Appl Stat 5(1):1–4. https://doi.org/10.11648/j.ajtas.20160501.11 Fairweather JS (2002) The mythologies of faculty productivity: Implications for institutional policy and decision making. J Higher Educ 73(1):26–48. https://doi.org/10.1353/jhe.2002.0005 Gachago D, Cruz L, Belford C, Livingston C, Morkel J, Patnaik S, Swartz B (2021) Third places: Cultivating mobile communities of practice in the global south. Int J Acad Dev 26(3):335–346. https://doi.org/10.1080/1360144X.2021.1955363 Gibbs G, Coffey M (2004) The impact of training of university teachers on their teaching skills, their approach to teaching and the approach to learning of their students. Act Learn High Educ 5(1):87–100. https://doi.org/10.1177/1469787404040463 Mooney JA, Miller-Young J (2021) The educational development interview: A guided conversation supporting professional learning about teaching practice in higher education. Int J Acad Dev 26(3):224–236. https://doi.org/10.1080/1360144X.2021.1934687 Pataraia N, Margaryan A, Falconer I, Littlejohn A (2013) How and what do academics learn through their personal networks. J Furth High Educ 39(3):336–357. https://doi.org/10.1080/0309877X.2013.831514 Pataraia N, Margaryan A, Falconer I, Littlejohn A, Falconer J (2014) Discovering academics’ key learning connections: An ego-centric network approach to analysing learning about teaching. J Educ Teach 40(3):243–260. https://doi.org/10.1080/02607476.2014.903353 Quinlan KM (2016) How higher education feels: Commentaries on poems that illuminate emotions in learning and teaching. Springer Roxå T, Mårtensson K (2009) Significant conversations and significant networks—Exploring the backstage of the teaching arena. Stud High Educ 34(5):547–559. https://doi.org/10.1080/03075070802597200 Simon E, Pleschová G (2019) Teacher–student relationships in higher education: How the quality of relationships with teachers impacts student learning and satisfaction. J Furth High Educ 43(8):1066–1079. https://doi.org/10.1080/0309877X.2018.1454549 Spitzner DJ, Meixner C (2021) Significant conversations, significant others: Intimate dialogues about teaching statistics. Int J Acad Dev 26(3):292–306. https://doi.org/10.1080/1360144X.2021.1954931 Thomson KE, Barrie S (2021) The backstage of significant teaching conversations: Exploring how they are enacted and what they achieve. Int J Acad Dev 26(3):276–291. https://doi.org/10.1080/1360144X.2021.1955360 Trowler P (2008) Cultures and change in higher education: Theories and practices. Palgrave Macmillan Van Waes S, Van den Bossche P, Moolenaar NM, De Maeyer S, Van Petegem P (2015) Know-who? Linking faculty’s networks to stages of instructional development. High Educ 70(5):807–826. https://doi.org/10.1007/s10734-015-9868-8 Wenger E (1998) Communities of practice: Learning, meaning and identity. Cambridge University Press Wright MC (2023) Faculty development centers in higher education: Trends and challenges Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Despite this, the academic culture in many institutions continues to prioritize research productivity over teaching effectiveness, often leaving faculty members with limited resources for enhancing their instructional practices (Chronicle of Higher Education, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). When teaching is evaluated, annual reviews and the tenure and promotion processes tend to lack the rigor in differentiating between an excellent teacher and an average teacher, while student course evaluations remain unreliable in effectively evaluating a professors\u0026rsquo; teaching performance. This makes it almost impossible to identify what is happening in the classrooms at university campuses across the United States. Additionally, a widespread movement to address this problem has never materialized, as recent studies indicate (Wright, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) only 26% of higher education institutes have a dedicated teaching center or faculty development center on campus. Furthermore, traditional, top-down faculty development programs have long been the norm among faculty development interventions. One day workshops, short sessions, or lecture-based courses are still widespread among many faculty developers. These types of interventions have been shown to have marginal influence on the quality of faculty instructional methods or performance. To add to the problem, according to a report by Cengage (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), 70% of all faculty in higher education in the United States are adjunct instructors, who teach more than half of all college courses in the country. Adjunct instructors often receive fewer teaching resources or have less access to faculty development support services.\u003c/p\u003e\u003cp\u003eAs these forces converge on universities around the world the study of faculty development has evolved into a broad field aimed at improving teaching, research, and service responsibilities across diverse academic contexts. However, as this dissertation will argue, formal faculty development programs may overlook the critical social dynamics and peer support systems that underpin authentic professional growth. Social networks within institutions\u0026mdash;comprising both formal and informal relationships among colleagues\u0026mdash;offer a valuable but underutilized channel for development. The problem addressed by this study is the disconnect between faculty development practices and the social, collaborative nature of professional growth in higher education. Traditional, one-size-fits-all development programs often fail to engage faculty in meaningful ways, lacking the flexibility and social interaction needed for sustainable improvement. The study seeks to explore how social networks and informal relationships within academic departments can contribute to faculty development, providing faculty members with the peer support and social capital needed to improve teaching quality.\u003c/p\u003e"},{"header":"Literature Review","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eSocial Networks and Faculty Development\u003c/h2\u003e\u003cp\u003eResearch has shown the capacity of established networks to enhance teacher practice more efficiently than traditional models of faculty development. Pataraia et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) argue that personal networks equip academics with a diverse pool of knowledge and skills about teaching, offering both professional and emotional support. Van Waes et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) examined the way in which faculty networks corresponded with faculty instructional development. Buckely and Nimmon (2020) used a qualitative social network approach to explore how teaching faculty\u0026rsquo;s relationships influenced their learning about teaching. Buckely and Nimmon identified four ways social networks influenced faculty learning about teaching: (1) enabling and mobilizing knowledge acquisition, (2) contributing to professional identity formation around teaching, (3) providing opportunity for expression of vulnerability as a prerequisite for deeper sharing and (4) augmenting and scaffolding learning from multiple knowledge sources. Buckely and Nimmon argue that the use of a social network lens in this study allowed them to deepen and transform their thinking about faculty development practices.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSignificant Conversations\u003c/h3\u003e\n\u003cp\u003eTo demonstrate the significance of personal networks and significant conversations, Rox\u0026aring; and M\u0026aring;rtensson (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) explored the conversational partners that university teachers have and the nature of these conversations. The intention of their study was to identify smaller networks in relation to teaching within a larger social context, and to determine if such networks exist, and how teachers should be able to report on how they differentiate between colleagues while talking about teaching. Rox\u0026aring; and M\u0026aring;rtensson hypothesized that teachers can name rather few colleagues with whom they have sincere discussions about teaching, and that they express themselves differently while talking to colleagues not included among those few. They distributed a questionnaire to 109 academic teachers and asked them to describe who they have conversations with about teaching and learning and detail about the nature of those conversations. The results showed that university teachers rely on a limited number of individuals to test ideas or solve problems related to teaching and learning. They argue that the existence of these networks has implications for leadership and management as well as for academic development. As they state, \u0026ldquo;...by recognizing significant networks it becomes possible to further understand why policies, organizational strategies or bureaucratic requirements have such a limited impact on university teaching\u0026rdquo; (p.557). Pataraia et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) extends the work of Rox\u0026aring; and M\u0026aring;rtensson by examining a wider range of aspects of conversations about teaching within networks. Pataraia et al. applied Social Network Analysis to determine who academics talk to about their teaching, the main themes of those conversations how often those conversations take place, and the factors that motivate those conversations. In sum, findings showed that through personal networks academics acquire various kinds of resources (new ideas and teaching materials), share knowledge and experience with one another as speculated by Social Capital Theory. The interviewees appreciated these as benefits that provided incentives for networking. Overall, respondents used their personal networks for exchanging ideas, discussing teaching-related problems and obtaining professional advice (Pataraia et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eCross-Disciplinary Participation\u003c/h3\u003e\n\u003cp\u003eIn the literature reviewed on significant conversations it was shown that conversations on learning and teaching are typically encouraged when conversing teachers come from various disciplines and departments. For instance, Dorner and Belic (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) describe how their institution invested in organizing regular lunch-time discussions about learning and teaching, which were attended over eight years by more than 500 faculty members across many departments. Locating these conversations in the Center for Teaching and Learning reinforced the importance of situated pedagogical reflections. Making these conversations interdisciplinary helped to overcome the hierarchies that often hinder teaching development within a department. Dorner and Belic also report that over time these pedagogical conversations evolved from being mostly focused on individual development, to facilitating collective learning and institutional changes. Mooney and Miller-Young (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) engaged teachers in what they describe as the educational development interview. In their study Mooney and Miller-Young show meaningful outcomes from these interviews, illustrating the potential of structured interviews to support conversation-based cross-disciplinary academic development.\u003c/p\u003e\n\u003ch3\u003eTrustful Relationships\u003c/h3\u003e\n\u003cp\u003eSimon and Pleschov\u0026aacute; (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) offer a definition of trust as: \u0026ldquo;a reaction to risk and uncertainty and as one actor\u0026rsquo;s (the trustor\u0026rsquo;s) psychological state that comprises of the willingness to accept vulnerability to another individual (the trustee) based upon positive expectations regarding both the intentions and the behavior of the trustee\u0026rdquo; (p.4). In their study they explored the impact of an academic development course on participants\u0026rsquo; most significant teaching relationship at their home institutions and, indirectly through this, their teaching practice. Simon and Pleschov\u0026aacute; found that participation in an academic development program increased the trustworthiness of doctoral students by making them expert conversation partners. In some cases, program attendance also decreased participant trust in certain colleagues such as supervisors, course leaders, or other faculty members. Lack of trust was found to limit teaching conversations in general and to constrain attention to certain topics in particular, including such pivotal issues as students, the syllabus, and self-reflection on teaching. Spitzner and Meixner (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) explored how collaborative ethnography gave form and depth to regular talk and encouragement to reconsider teaching-related assumptions, particularly related to trust and vulnerability in teachers\u0026rsquo; pedagogy. They argue that by cultivating collaborative autoethnography faculty developers and centers of faculty development would open brave spaces for civil dialogue, mentoring, intergroup dialogue, story circles, and communities among same and diverse peers. Boschman et al. (2021) explores efforts to stimulate significant conversations through a Scholarship of Teaching and Learning (SoTL) Community of Practice (CoP) amongst a diverse group of professors and professional staff in a College of Applied Arts and Technology in Ontario, Canada. Participants shared their reflections on the formation of significant networks and the start of significant conversations through the founding of a Community of Practice.\u003c/p\u003e\n\u003ch3\u003eConducive Spaces\u003c/h3\u003e\n\u003cp\u003eThomson and Barrie (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) explore how academics use informal conversations to overcome unsupportive teaching contexts. They find that proximity, similarity, and camaraderie help academics to have significant conversations about teaching. In their study, a frequently mentioned positive factor is a conducive space for academics to talk about teaching \u0026ndash; a corridor, meeting room, coffee machine, or other place that fosters informal discussion. Thomson and Barrie argue that space alone is not sufficient for meaningful talk and that trustful relationships, often friendships, also play a crucial role in enabling significant conversations about teaching in an institutional environment that privileges research. Ndlovu et al. (2021) created a space, Room32, for themselves at the outskirts of their campus where they refurbished an old, forgotten room. They explain how conversations in Room32 contrasted with the much less helpful frontstage conversations that dominated other university settings. Ndlovu et al. argue that the liminality in Room32 sparked meaningful conversations and change that were not possible elsewhere on campus. Gachago et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) analyze a convenient space they found for academic development and pedagogical conversations during the disruption of COVID-19: WhatsApp. The authors describe how this group retreated to a \u0026lsquo;third place\u0026rsquo; after they could not continue their usual ways of working together. They used this virtual space to build courage and support for each other, and to exchange ideas about effective practices in new conditions. The authors conclude by sharing their understanding of the mission of educational developers: to transform institutions into caring places of teaching and learning.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eResearch Questions\u003c/h2\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eResearch Q1: What institutional conditions contribute to the enhancement or hindrance of social capital of faculty members?\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eResearch Q2: What effect does social capital have on faculty development (significant conversations, teaching and learning interventions)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eResearch Q3: What effect do personal characteristics (age, gender, experience level, discipline) have on one\u0026rsquo;s social network ties?\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Methodology Design","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eConvergent Parallel Mixed Methods\u003c/h2\u003e\u003cp\u003eThis study adopted a convergent parallel mixed-method design (Creswell \u0026amp; Clark, 2018) to answer the research questions. The quantitative component involved Social Network Analysis to visualize and measure the structure of faculty networks, while the qualitative component involves semi-structured interviews and focus groups to understand faculty members\u0026rsquo; experiences and perceptions. The rationale for using a mixed-method design was to integrate network-level data with rich qualitative insights, providing a more comprehensive picture of the factors influencing social networks within the academic context.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eImplementation of the Study\u003c/h2\u003e\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\u003ch2\u003eStudy Site\u003c/h2\u003e\u003cp\u003eThis study took place at The American University of Sharjah, a private, non-profit, liberal arts university in Sharjah, United Arab Emirates. The university is one of only a handful of American style liberal arts colleges in the MENA region. The study site was chosen out of convenience; the researcher has been employed by the university since 2015. According to AUS\u0026rsquo;s internal research group, as of Fall 2023 there were 5,876 students enrolled. 5,233 of those students were enrolled in a four-year bachelor\u0026rsquo;s program, 412 in a master\u0026rsquo;s program, 119 Ph.D. students and 112 were enrolled in the universities Achievement Academy, which specializes in English language preparation. The American University of Sharjah is one of the most diverse universities in the world, with over 97 nationalities represented among the student body. The makeup of the faculty community is also very diverse with faculty coming from 47 different countries, 43.5% of whom are US or Canadian citizens.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eThe Population of the Participants\u003c/h2\u003e\u003cp\u003eThe participants were selected from the existing community of faculty members at the American University of Sharjah. Currently there are 337 full-time faculty teaching in four colleges and various departments. The College of Arts and Sciences has the most faculty with 147, the College of Engineering has a total of 87 faculty, the School of Business Administration has 65 faculty and the College of Architecture, Art and Design has a total of 38 faculty members. \u003cb\u003eSample Selection Method\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study utilized a convenience sampling approach to select participants from the American University of Sharjah (AUS). Convenience sampling was chosen due to the practical considerations of participant accessibility and the exploratory nature of the research. As Etikan et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) explain, convenience sampling allows researchers to gather data quickly and efficiently, especially in settings where participants are readily available and willing to engage. The sample comprises an interdisciplinary group of faculty members at AUS, drawn from various departments to ensure diversity in the social network structures being analyzed.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eParticipant Demographics\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents demographics for 41 survey respondents and 8 interviewees (a subset of survey participants) at the American University of Sharjah. The sample was diverse across academic discipline, gender and years of teaching experience. For the interviews, the Colleges of Engineering and the School of Business Administration were underrepresented.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eParticipant Demographics (N\u0026thinsp;=\u0026thinsp;41 Surveys, N\u0026thinsp;=\u0026thinsp;8 Interviews)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDemographic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSurvey (n, %)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eInterview (n, %)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15 (39.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (37.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26 (60.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (62.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRank\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAssistant Professor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9 (20.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (25.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAssociate Professor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14 (32.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (37.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInstructor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (2.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eProfessor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9 (20.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (25.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSenior Instructor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (11.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (12.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVisiting Professor (any rank)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (9.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCollege (Discipline)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCollege of Art, Architecture and Design\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (15%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (25%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCollege of Arts and Sciences\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16 (39.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (50%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCollege of Engineering\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9 (20.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (12.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSchool of Business Administration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11 (25.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (12.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eYears of Teaching Experience\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u0026ndash;3 Years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (4.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (12.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4\u0026ndash;7 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8\u0026ndash;10 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (9.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (12.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMore than 10 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34 (81.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (75%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eSocial Capital Index\u003c/h2\u003e\u003cp\u003eTo better understand the social structures that shape faculty development at the American University of Sharjah (AUS), this study employed a Social Capital Index (SCI) to provide a quantifiable measure of each participant\u0026rsquo;s access to and engagement with professional networks, as well as the institutional conditions that affect access to social capital. The Social Capital Index was calculated as the mean of survey items assessing network size and diversity, frequency of conversations, trust and reliance on colleague feedback, and shared pedagogical goals. SCI ranges from 1 (low) to 5 (high). Higher SCI scores indicate conditions fostering social capital (e.g., supportive departments, supportive administration, access to colleagues and trust in receiving and giving feedback on teaching), while lower scores suggest barriers (e.g., limited collaboration opportunities, lack of shared space, workload). Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the Social Capital Index (SCI) of each of the survey respondents. The overall mean of 3.40 (SD\u0026thinsp;=\u0026thinsp;1.50) indicates moderate to high social capital throughout the university. The college of Art Architecture and Design (mean 3.54) enhanced their faculty\u0026rsquo;s social capital through classroom design, collaboration and studio classes. The College of Arts and Sciences (mean 3.51) also had a moderate to high level of social capital mostly fostered by department level collaboration and supportive department heads. The School of Business Administration and the College of Engineering had lower levels of social capital with workload and lack of institutional support mentioned as barriers.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSocial Capital Index (SCI) Scores by Faculty Characteristics (n\u0026thinsp;=\u0026thinsp;42)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGroup\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMean SCI (1\u0026ndash;5)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNotes\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOverall\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eModerate social capital enhanced by supportive conditions but hindered by barriers like workload.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAssistant Professor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eModerate enhancement through collaboration.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAssociate Professor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eVaried; enhanced by department support but hindered for some.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInstructor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLow, indicating potential hindrances like limited resources.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProfessor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eConsistent; enhanced by experience but hindered by time constraints.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSenior Instructor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eModerate-to-high, supported by institutional structures.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVisiting Professor (any rank)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eVaried by department culture.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCAAD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eEnhanced by collaborative studio environments.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCAS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eModerate-to-high, fostered by departmental interactions.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCEN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLower; hindered by workload or limited support.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSBA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eModerate; barriers like heavy loads may hinder social capital.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eInstitutional Conditions\u003c/h2\u003e\u003cp\u003e\u003cem\u003eRQ1: Research Q1: What institutional conditions contribute to the enhancement or hindrance of social capital of faculty members?\u003c/em\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e below synthesizes the quantitative survey data (N\u0026thinsp;=\u0026thinsp;41, including means, SDs, and percentages from selected survey responses) and network outcomes with qualitative themes and quotes from interviews and open-ended survey responses. As discussed above, this integration reveals how institutional conditions\u0026mdash;such as leadership, PD programs through the CITL, workload, and structural support\u0026mdash;shape faculty social capital, addressing RQ1: \"What institutional conditions contribute to the enhancement or hindrance of social capital of faculty members?\" The analysis highlights convergences (e.g., aligned data on workload hindrances) and divergences (e.g., quantitative showing moderate support but qualitative emphasizing burnout), drawing on Social Capital Theory to interpret network strength (e.g., trust, diversity) as influenced by these conditions.\u003c/p\u003e\u003cp\u003eThe data converges strongly on enhancements through supportive leadership and professional development programs. Quantitatively, high selection of supportive HODs (63.4%) and department value for peer talk (41.5% high) correlate with robust trust in colleagues (76.0% high) and moderate network size (57.0% high), suggesting these conditions build relational and structural social capital. Qualitatively, this aligns with the \"Supportive Leadership/HOD\" theme (6/8 interviews, 8/30 surveys), where faculty describe HODs as catalysts for collaboration, as in \"Our department head is amazing at promoting collaboration... [but] our workload is so extreme\" (Interview - SNA Study Interview). This convergence indicates that institutional leadership enhances social capital by enabling trust and informal networks, though workload moderates the effect.\u003c/p\u003e\u003cp\u003eWorkshops and CITL programs demonstrate moderate convergence as enhancers. Quantitative data shows 39.0% selection for teaching workshops and 31.7% for peer mentoring, linking to moderate network diversity (mean 3.2, 50.0% high) and strategy adoption (mean 3.8, 62% high). Qualitatively, the \"Workshops/CITL/PD Programs\" theme (5/8 interviews, 12/30 surveys) reinforces this, with faculty praising CITL for innovation, for example, \"CITL workshops have been much better about introducing us to more innovative teaching methods\". A slight divergence appears in qualitative accounts of time barriers, such as \"faculty are just too busy\", which underscores how institutional professional development boosts cognitive social capital through shared pedagogical goals but faces practical limitations, such as workload and a formal incentive structure.\u003c/p\u003e\u003cp\u003eHindrances reveal strong convergence, particularly for heavy workload and time constraints. Quantitatively, low workload allowance (73.2% low) and ~\u0026thinsp;60% citing workload in barriers correlate with lower network diversity (20.0% low) and size (14.0% low), indicating reduced structural social capital. Qualitatively, the \"Heavy Workload/Time Constraints\" theme (8/8 interviews, 18/30 surveys) echoes this, with consistent reports of burnout, e.g., \u003cem\u003e\"Reduce the teaching load... The current trend at AUS is not realistic and will only result in reducing the quality of teaching\u003c/em\u003e\" and \"\u003cem\u003eWorkload and time constraints limit networking\u003c/em\u003e\". Both sets of data converge on this idea as a major impediment to the development of faculty social networks and professional development opportunities.\u003c/p\u003e\u003cp\u003eAdditionally, the lack of formal structures and incentives shows convergence with some nuance. Quantitative data highlights low formal structures (61.0% low) and low selections for retreats (7.3%) and shared spaces (, 4.9%), linking to moderate trust (10.0% low). Qualitatively, the \"Lack of Formal Structures/Incentives\" theme (6/8 interviews, 14/30 surveys) aligns, with calls for incentives, e.g., \u003cem\u003e\"No incentives for teaching... many colleagues do not even care about teaching\" and \"No formal structures for teaching/practice conferences\u003c/em\u003e\". \u0026ldquo;\u003cem\u003eI don't, I don't think we're formally encouraged in any way to learn from one another. I think we're kind of put in our like, in our little box, and we're told this is what you do. And so if you are personally interested to learn from one another. You need to go out of your way to do this\u003c/em\u003e.\u0026rdquo; Convergence is evident in both datasets where emphasis was placed on policy gaps hindering relational capital, but qualitative data provides more depth on research-teaching imbalance.\u003c/p\u003e\u003cp\u003eSiloed departments and isolation also converge as a hindrance. Quantitatively, low interdisciplinary opportunities (58.5% low) correlate with lower diversity (20.0% low). Qualitatively, the \"Siloed Departments/Isolation\" theme (5/8 interviews, 9/30 surveys) supports this, e.g., \u003cem\u003e\"We are pretty insular... engineers for sure\"\u003c/em\u003e and \u003cem\u003e\"AUS doesn't do anything. Outside of faculty meetings or committee work, you don't see faculty at all\"\u003c/em\u003e. This convergence highlights institutional silos reducing structural social capital, with no major divergence\u0026mdash;both types stress departmental independence.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eIntegrated Quantitative and Qualitative Findings for Institutional Conditions and Social Capital\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAspect\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuantitative Support\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eQualitative Support\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIntegration Notes\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEnhancement: Supportive Leadership/HOD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e63.4% selected 41.5% high.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSupportive HOD theme (6/8 interviews, 8/30 surveys): \"Our department head is amazing at promoting collaboration\".\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eConverges: High HOD selection enhances trust/networks ;(qual. shows HODs fostering collaboration, but limited by workload (e.g., \"extreme workload\")\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEnhancement: Workshops/CITL/PD Programs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e39.0% selected; (Workshops): 31.7%. selected (Peer Mentoring) Linked to moderate network diversity).\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWorkshops/CITL theme (5/8 interviews, 12/30 surveys): \"CITL workshops have been much better about introducing us to more innovative teaching methods\u0026rdquo;.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eConverges: Moderate selection for workshops enhances innovation/networks; qual. praises CITL but notes time barriers\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHindrance: Heavy Workload/Time Constraints\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e73.2% low, ~\u0026thinsp;60% cite workload. Linked to lower network size\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHeavy Workload theme (8/8 interviews, 18/30 surveys): \"Reduce the teaching load... The current trend at AUS is not realistic\".\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eConverges: Low workload allowance hinders networks qual. emphasizes burnout\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHindrance: Lack of Formal Structures/Incentives\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e61.0% low; (Shared Office Space): 4.9%; (Retreats): 7.3%.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLack of Structures theme (6/8 interviews, 14/30 surveys): \"No formal structures for teaching/practice conferences\".\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eConverges: Low selection for structures hinders collaboration; qual. calls for incentives (e.g., \"No incentives for teaching\" in S9), tying to RQ1 institutional gaps.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHindrance: Siloed Departments/Isolation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e58.5% low; Linked to lower diversity (20% low).\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSiloed Departments theme (5/8 interviews, 9/30 surveys): \"We are pretty insular... engineers for sure\".\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eConverges: Low interdisciplinary opportunities hinder diversity; qual. notes isolation (e.g., \"Outside of faculty meetings, you don't see faculty\".\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eSocial Capital and Faculty Development\u003c/h2\u003e\u003cdiv id=\"Sec19\" class=\"Section3\"\u003e\u003ch2\u003eRQ2: What effect does social capital have on faculty development?\u003c/h2\u003e\u003cdiv id=\"Sec20\" class=\"Section4\"\u003e\u003ch2\u003eIntegrated Findings for Research Question 2\u003c/h2\u003e\u003cp\u003eDrawing on Social Capital Theory to interpret how networks influence development through knowledge exchange and practical application, the analysis reveals strong convergences. The findings, shown below in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, converge on social capital's positive effect through enhanced significant conversations. For example, quantitatively, high reliance on colleagues (mean 3.9, SD 0.9, 68% high) and ease of finding discussion partners (mean 3.8, SD 1.0, 65% high) correlate with moderate conversation frequency (mean 3.0, SD 1.1, 45% monthly or more), indicating networks facilitate insightful exchanges. Qualitatively, this aligns with the \"Enhanced Significant Conversations\" theme (7/8 interviews, 10/30 surveys), where faculty describe discussions leading to shared insights, for example, \u003cem\u003e\"Informal discussions on curriculum and psychosocial aspects of teaching\u0026rdquo;\u003c/em\u003e. This convergence suggests social capital fosters relational ties that enable conversations, promoting development, though qualitative data highlights time limitations (e.g., \u003cem\u003e\"No time for extra activities\u0026rdquo; more\u003c/em\u003e than the moderate standard deviations in quantitative results.\u003c/p\u003e\u003cp\u003eAdditionally, adoption of new teaching interventions shows strong convergence as a key effect. Quantitative data reveals high strategy adoption from colleagues (mean 3.8, SD 1.0, 62% high), linked to access to valuable resources (mean 3.9, SD 0.9, 70% high) and trust (mean 4.0, SD 0.8, 76% high). Qualitatively, the \"Adoption of New Teaching Interventions\" theme (6/8 interviews, 8/30 surveys) reinforces this, with faculty noting practical applications, such as \"A colleague suggested mind maps... It worked\" (P3). This data illustrates the potential of how increased social capital can positively impact collaboration among colleagues, especially peer recommendations for teaching activities and curriculum ideas.\u003c/p\u003e\u003cp\u003eAnother theme that emerged with moderate convergence was building trust and reciprocity with colleagues effects sustained faculty development. Quantitative evidence includes high reciprocal support (mean 4.0, SD 0.8, 74% high) and trust (mean 4.0, SD 0.8, 76% high), correlating with strategy adoption (62% high). Qualitatively, the \"Building Trust and Reciprocity\" theme (5/8 interviews, 7/30 surveys) supports this, for instance, \"Peer mentoring and shared learning from colleagues\". This convergence while high in the interviews, was not well supported by a vast majority of the faculty who responded to the survey.\u003c/p\u003e\u003cp\u003eSome of the barriers where convergence could potentially limit faculty development were between conversation frequency (25% low), linking to lower reliance in some groups (12% low). Qualitatively, the \"Barriers Limiting Effects\" theme (6/8 interviews, 12/30 surveys) aligns, emphasizing constraints like workload, such as \"Workload prevents me from attending workshops, hindering collaboration\" (P2). This supports the idea of how barriers moderate social capital's positive effects. A majority of the barriers noted in both data sets were related to workload and the fact that a focus on teaching is not incentivized.\u003c/p\u003e\u003cp\u003eIn summary, the integration affirms that social capital positively affects faculty development by enabling significant conversations and interventions through trust, reciprocity, and resource sharing. These convergences dominate, with divergences mainly in qualitative depth on barriers. The findings suggest that strengthening networks could amplify faculty development and highlights the importance of focusing on building ground up, department level collaboration in order to increase social networks.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eIntegrated Quantitative and Qualitative Findings for Effects of Social Capital on Faculty Development\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAspect\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuantitative Support\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eQualitative Support\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIntegration Notes\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEnhanced Significant Conversations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh reliance on colleagues (mean 3.9, SD 0.9, 68% high) and ease of finding partners (mean 3.8, SD 1.0, 65% high); moderate conversation frequency (mean 3.0, SD 1.1, 45% high).\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEnhanced Conversations theme (7/8 interviews, 10/30 surveys): \"Informal discussions on curriculum and psychosocial aspects of teaching\" (S21).\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eConverges: Networks enable exchanges; qual. adds depth to insights (e.g., \"psychosocial aspects\"), beyond quant's frequency.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdoption of New Teaching Interventions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh strategy adoption (mean 3.8, SD 1.0, 62% high); linked to resources (mean 3.9, SD 0.9, 70% high).\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAdoption theme (6/8 interviews, 8/30 surveys): \"A colleague suggested mind maps... It worked\".\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eConverges: Social capital drives practical application; both show peer influence, with qual. providing examples (e.g., mind maps).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBuilding Trust and Reciprocity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh reciprocal support (mean 4.0, SD 0.8, 74% high) and trust (mean 4.0, SD 0.8, 76% high).\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTrust theme (5/8 interviews, 7/30 surveys): \"Peer mentoring and shared learning from colleagues\".\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eConverges: Ties support sustained growth; qual. emphasizes reciprocity (e.g., \"shared learning\") not fully captured in quant SDs.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBarriers Limiting Effects\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerate frequency (25% low); lower reliance in some groups (12% low).\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBarriers theme (6/8 interviews, 12/30 surveys): \"Workload prevents me from attending workshops\".\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eConverges: Barriers moderate effects; qual. adds context (e.g., workload) to quant's variability.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003ePersonal Characteristics and Social Network Ties\u003c/h2\u003e\u003cp\u003e\u003cem\u003eResearch Q3: What effect do personal characteristics (gender, experience level, discipline) have on one\u0026rsquo;s social network ties?\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003eIntegrated Findings for Research Question 3\u003c/h2\u003e\u003cp\u003eThe findings converge on discipline shaping network insularity. As Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e displays, Quantitatively, the SCI varies by discipline, with CAAD (mean 3.54, SD 0.67), CAS (mean 3.50, SD 0.66), CEN (mean 3.48, SD 0.48), and SBA (mean 3.46, SD 0.70) showing moderate-to-high ties, but lower diversity (overall 20% low) suggests silos. The qualitative data reinforces the theme of department and college level silos and lack of cross-departmental or cross-disciplinary collaboration. The data suggests that CAS faculty tend to have more department level collaboration and lesson sharing than other colleges. Additionally, this convergence indicates that discipline affiliation, particularly in STEM or design fields, restricts cross-departmental ties, reducing network diversity, with quantitative variability (SD 0.48\u0026ndash;0.70) reflecting qualitative nuances on departmental independence.\u003c/p\u003e\u003cp\u003eAnother theme which emerged from the data analysis was the fact that experience and mentorship and network strength shows moderate convergence. Quantitatively, faculty with more than 10 years of experience have a mean SCI of 3.48 (SD 0.62), slightly higher than mid-career (8\u0026ndash;10 years, mean 3.26, SD 0.65), suggesting accumulated ties. Qualitatively, the \"Experience Enabling Mentorship and Network Stability\" theme (5/8 interviews) supports this, with senior faculty leveraging tenure. The convergence suggests that experience fosters mentorship and stable ties, though quantitative data shows less variation (SD 0.62) than qualitative accounts of novice reliance on diverse connections. This would suggest that longer tenure tends to restrict the adoption of new network ties, whereas newer faculty possibly seek out older faculty for guidance and advice. Interviews with more senior level faculty with 10 or more years of teaching experience reinforce this analysis. Many noted that in the beginning of their careers they were more active in both department level collaboration and cross-disciplinary collaboration. Often the theme of institutional changes or policy directions were noted as indicators for barriers, as noted in the analysis of RQ1.\u003c/p\u003e\u003cp\u003eGender influencing network access and dynamics reveals convergence with some divergence. Quantitatively, females have a mean SCI of 3.37 (SD 0.65) compared to males at 3.56 (SD 0.59), a slight negative effect possibly due to barriers. There as little qualitative data on the effect of gender on faculty social ties, one faculty member mentioned being the only \u0026ldquo;western woman\u0026rdquo; in her department and that she felt \u0026ldquo;isolated\u0026rdquo;. However, these themes were not explored in greater depth in the survey or interviews.\u003c/p\u003e\u003cp\u003eExperience level moderating network diversity and growth shows moderate convergence. Quantitatively, mid-career faculty (8\u0026ndash;10 years) have a higher mean SCI (3.26, SD 0.65) than novices (1\u0026ndash;3 years, mean 3.78, SD N/A), suggesting diverse tie growth. Qualitatively, the \"Experience Level Moderating Network Diversity and Growth\" theme (4/8 interviews) supports this, with mid-career faculty building broader ties, however the most experienced faculty have a less diverse network and rely on colleague for support less often than new or mid-career faculty.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eIntegrated Quantitative and Qualitative Findings for Effects of Personal Characteristics on Social Network Ties\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAspect\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuantitative Support\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eQualitative Support\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIntegration Notes\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiscipline Shaping Network Insularity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSCI varies by discipline: CAAD (3.54, SD 0.67), CAS (3.50, SD 0.66), CEN (3.48, SD 0.48), SBA (3.46, SD 0.70); 20% low diversity.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDiscipline Insularity theme (6/8): (P6).\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eConverges: Discipline creates silos, reducing diversity; quant SDs reflect qualitative emphasis on independence.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExperience Enabling Mentorship\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSCI for \u0026gt;\u0026thinsp;10 years (3.48, SD 0.62) vs. 8\u0026ndash;10 years (3.26, SD 0.65); higher stability with experience.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eExperience Mentorship theme (5/8):\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eConverges: Experience builds mentorship ties; quant shows stability, qual. adds depth to senior roles.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender Influencing Network Access\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSCI females (3.37, SD 0.65) vs. males (3.56, SD 0.59); slight negative effect for females.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGender Dynamics theme (3/8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eConverges with divergence: Gender impacts access; qual. highlights barriers more than quant\u0026rsquo;s modest difference.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExperience Level Moderating Diversity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSCI 8\u0026ndash;10 years (3.26, SD 0.65) vs. 1\u0026ndash;3 years (3.78, SD N/A); mid-career shows moderate diversity.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eExperience Diversity theme (4/8): \"I just finished my first year at a US\" (P3).\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eConverges: Experience moderates diversity; quant variability aligns with qual. shifts in network growth.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\u003ch2\u003eImplications\u003c/h2\u003e\u003cp\u003eThe research findings from this study have many implications for faculty development in higher education. As mentioned at the outset, universities are facing many headwinds which have a negative impact on the way that teaching is valued and practiced at higher education institutions around the world. With the advent of Artificial Intelligence and Large Language Learning Models, the challenges have become even larger. The basic relevance of higher education and teaching in particular has become a common theme in media outlets and, I believe in the minds of undergraduate students. Finding relevance through social learning, building community and advancing social networks may help universities navigate these uncertain times.\u003c/p\u003e\u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\u003ch2\u003eImplication 1: Enhance social network with institutional policy reforms\u003c/h2\u003e\u003cp\u003eAligning with the research in the field, the findings in this study recommend for a policy shift such as reducing teaching loads from 3\u0026ndash;3 to 2\u0026ndash;2, supported by Gibbs and Coffey\u0026rsquo;s (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) evidence that time availability boosts network engagement. The high percentage of faculty responses indicated that workload was a barrier to the creation of teaching related social networks (mean 1.38, 73.2% low) suggests a critical need for policy reform in this area. This is exacerbated by the fact that institutional incentives are primarily focused on research output, specifically journal articles published in the top percentile of Scopus ranked journals. These incentives are a part of end of year reviews and \u0026lsquo;rolling contract\u0026rsquo; and promotion decisions. Additionally, while this study supports the idea that social network strength is essential to faculty development, the creation of formal structures, like interdisciplinary grants or teaching retreats, could mitigate silos, consistent with Trowler\u0026rsquo;s (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) call for cross-departmental initiatives. While this study contends that the strongest social networks are those which are created from the bottom up, without clear direction and buy-in from the institution there would be very little incentive for faculty to develop new department level or inter-departmental networks. One example of this would be at AUS, where research pressure overshadows teaching, rebalancing evaluation criteria to include network-building efforts\u0026mdash;such as crediting teaching collaborations in year-end reviews\u0026mdash;could shift priorities, echoing Fairweather\u0026rsquo;s (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) advocacy for holistic assessment.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec26\" class=\"Section3\"\u003e\u003ch2\u003eImplication 2: Focus on creation of shared physical spaces\u003c/h2\u003e\u003cp\u003eImplementing shared physical spaces, such as offices, lounge areas, or collaboration hubs, could significantly enhance faculty ties, addressing the low 4.9% selection rate for shared spaces (Q17_4) and the pervasive lack of conducive environments (mean agreement\u0026thinsp;~\u0026thinsp;1.2\u0026ndash;1.5). Defined in the literature as \"conducive spaces\" that foster informal interaction and trust (Thomson \u0026amp; Barrie, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), AUS currently offers few venues for academics to discuss teaching, a gap echoed in qualitative insights like \"Outside of faculty meetings or committee work, you don\u0026rsquo;t see faculty at all\" (S22). The weak correlation between lack of shared space and low trust (e.g., 12.2% overall, 16.7% in CAAD) suggests physical isolation undermines social capital, particularly in siloed colleges like CAAD (mean SCI 3.02). A pilot project converting underutilized areas into shared spaces, monitored with pre/post SCI surveys, could boost network formation. Complementing this, virtual spaces\u0026mdash;such as Microsoft Teams channels or a dedicated Slack workspace\u0026mdash;could extend access, aligning with Gachago et al.\u0026rsquo;s (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) findings on mobile communities of practice in the Global South, where WhatsApp fostered collaboration despite barriers. At AUS, a virtual \"teaching lounge\" for asynchronous discussions could leverage the 21.9% online tool uptake, enhancing trust and breaking isolation, especially for CEN/SBA faculty, while accommodating the 3\u0026ndash;3 teaching load constraints (mean 1.38, 73.2% low).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec27\" class=\"Section3\"\u003e\u003ch2\u003eImplication 3: Enhance social capital through structured conversations about teaching and learning\u003c/h2\u003e\u003cp\u003eAn additional implication would be to leverage social capital through structured conversations (e.g., monthly teaching rounds facilitated by HODs) and interventions (e.g., peer observation programs or co-teaching initiatives) could enhance development, resonating with Wenger\u0026rsquo;s (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1998\u003c/span\u003e) communities of practice model. The moderate conversation frequency (mean 3.0, 45% high) suggests institutional incentives, such as PD credits, small stipends, or time off, could amplify effects, supported by Quinlan\u0026rsquo;s (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) findings on peer influence. Qualitative barriers like \"Workload prevents me from attending workshops\" (P2) indicate a need for flexible scheduling, aligning with global trends in faculty support (Gibbs \u0026amp; Coffey, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Integrating technology, such as virtual collaboration platforms (e.g., Microsoft Teams or Blackboard Collaborate), could overcome time barriers, building on Henderson et al.\u0026rsquo;s (2011) work, especially given AUS\u0026rsquo;s hybrid teaching model post-COVID. A specific intervention could involve a semester-long virtual teaching seminar series, tracking participation and development outcomes to assess impact. These strategies could be piloted in high-SCI departments like CAS to model success for others, with evaluations using pre/post SCI surveys to measure changes in conversation frequency and strategy adoption over a 12-month period.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec28\" class=\"Section2\"\u003e\u003ch2\u003eImplication 4: Discipline specific strategies\u003c/h2\u003e\u003cp\u003eTailoring strategies to the unique cultures and needs of different disciplines offers a promising avenue to enhance social capital and dismantle network insularity at AUS, moving beyond a one-size-fits-all approach to faculty development. Drawing on Becher and Trowler\u0026rsquo;s (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) concept of academic tribes, disciplines like CAAD and CEN\u0026mdash;where mean SCI scores are lower (3.02 and 3.28, respectively, with SDs of 0.44 and 0.43)\u0026mdash;may benefit from initiatives that encourage creative cross-pollination, such as design-thinking workshops inviting input from the more collaborative humanities faculty in CAS (mean SCI 3.50, SD 0.67). Similarly, engineering departments could host interdisciplinary problem-solving forums to bridge their often-siloed structures, inspired by Trowler\u0026rsquo;s (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) emphasis on context-sensitive interventions. With 39.0% of faculty currently engaging in workshops, there\u0026rsquo;s a foundation to build upon, but the 12.2% low trust rate (highest at 16.7% in CAAD) suggests a need for trust-building activities, like cross-disciplinary mentor pairs, as Baldwin and Chang (2007) recommend for novice support. This approach offers the change for AUS to pioneer a model of discipline-tailored professional development (PD) that redefines professional identity\u0026mdash;perhaps through a semester-long series of symposia tailored to each college\u0026rsquo;s needs. From the interviews conducted there was strong agreement that cross-disciplinary initiatives are missing, but much needed to the academic landscape at AUS.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec29\" class=\"Section2\"\u003e\u003ch2\u003eImplication 5: Connect Scholarship of Teaching and Learning research to university research requirements\u003c/h2\u003e\u003cp\u003eThe final implication which offers a strategic solution to balance the institution's strong research focus with its substantial teaching loads (3/3 for faculty, 4/4 for instructors) would be to promote and encourage research into the growing field of the Scholarship for Teaching and Learning (SoTL). The International Society for the Scholarship of Teaching and Learning offers high value journals and yearly international conferences on this growing field of research. By incentivizing SoTL, such as through grants for classroom-based research or recognizing SoTL publications in tenure evaluations, AUS could encourage faculty to explore their teaching practices, aligning with Boyer\u0026rsquo;s (1990) framework of scholarship encompassing discovery, integration, application, and teaching. This approach could transform teaching demands into opportunities for scholarly output, enhancing social capital through collaborative pedagogical research. A pilot SoTL fellowship program, where faculty document interventions like AI in classrooms, could be implemented, with metrics tracking publication rates and SCI changes over a semester. This strategy addresses RQ1's workload barriers while boosting RQ2's interventions, offering a sustainable model for faculty development in research-intensive contexts.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study reinforces the literature on the power of social capital as a lever for faculty development in higher education. The study highlights the institution\u0026rsquo;s strengths\u0026mdash;supportive leadership and innovative professional development programs\u0026mdash;while identifying critical barriers, such as heavy workloads and structural gaps, that must be addressed to cultivate a collaborative teaching environment. The proposed recommendations\u0026mdash;reducing teaching loads to 2\u0026ndash;2, establishing interdisciplinary grants, implementing discipline specific interventions, inclusion of conducive spaces and a focus on incorporating the research principles of the scholarship of teaching and learning, offer a comprehensive roadmap for AUS to enhance faculty networks, reduce attrition, elevate teaching excellence, and improve student learning. This work lays the foundation for future research and institutional reform, positioning AUS as a potential leader in the Gulf region for innovative faculty development strategies, provided the institution invests in these changes. Through the analysis of both quantitate and qualitative data, and especially reflecting on the 8 in-depth interviews, it is apparent that there is a need and a great desire among faculty to shift the focus from an intense research output to a more nuanced approach, incorporating the ideas presented in this study: collaboration, cross-disciplinary work, focus on culture, trust and access to conversations with colleagues, and development of social networks. This dissertation hopefully advances the understanding of faculty development in higher education but also serves as a call to action for universities to prioritize its teaching community, ensuring that social capital becomes a cornerstone of academic excellence in the years to come.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics Approval and Consent to Participate This study was reviewed and determined to pose minimal risk to participants by the Institutional Review Board (IRB) at the American University of Sharjah. It qualified for exempt IRB approval under 45 CFR 46.104(d)(2) and (3). The protocol, entitled “A SOCIAL NETWORK ANALYSIS OF FACULTY DEVELOPMENT IN HIGHER EDUCATION” (Protocol #: 25-055), was approved on March 20, 2025, with an effective date of March 25, 2025. No external funding was received for this research. All participants provided informed consent prior to involvement. 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Cambridge University Press\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWright MC (2023) Faculty development centers in higher education: Trends and challenges\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Illinois at Urbana-Champaign","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Faculty development, social networks, social capital, teaching practices, higher education","lastPublishedDoi":"10.21203/rs.3.rs-7832545/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7832545/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study examines the role of social networks in faculty development. Grounded in Social Learning Theory and Social Capital Theory, the study explores how collaborative ties provide access to resources, mentorship, and innovation, while barriers like isolation and workload constraints limit their potential. Employing a mixed-methods design at the American University of Sharjah, UAE data were collected from 41 faculty surveys and 8 in-depth interviews, representing diverse ranks, disciplines, and experiences. Quantitative analysis, including a Social Capital Index, revealed patterns of network influence on engagement, while qualitative themes illuminated mentorship's role in fostering student-centered teaching. Integrated findings highlight that robust networks align with institutional goals for teaching excellence, but systemic issues like heavy workloads undermine social capital.\u003c/p\u003e","manuscriptTitle":"Social Capital and Faculty Development in Higher Education","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-15 10:51:34","doi":"10.21203/rs.3.rs-7832545/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1c29de5b-78cb-4bb6-8d1c-16cd775791fa","owner":[],"postedDate":"October 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-15T10:51:34+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-15 10:51:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7832545","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7832545","identity":"rs-7832545","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}