Essay Writing Service

Effect of Social Networks on Teaching Methods


Background. Research on social networks in schools is increasing rapidly. Network studies outside education have indicated that the structure of social networks is partly affected by demographic characteristics of network members. Yet, knowledge on how teacher social networks are shaped by teacher and school demographics is scarce.

Purpose. The goal of this study was to examine the extent to which teachers’ work related social networks are affected by teacher and school demographic characteristics.

Method. Survey data were collected among 316 educators from 13 elementary schools in a large educational system in the Netherlands. Using social network analysis, in particular multilevel p2 modeling, we analyzed the effect of teacher and school demographics on individual teachers’ probability of having relationships in a work discussion network.

Conclusions. Findings indicate that differences in having relationships were associated with differences in gender, grade level, working hours, formal position, and experience. We also found that educators tend to prefer relationships with educators with the same gender and from the same grade level. Moreover, years of shared experience as a school team appeared to affect the likelihood of teacher relationships around work related discussion.


Relationships among educators are more and more regarded as an important element to schools’ functioning, and a potential source of school improvement. Educational practitioners and scholars around the world are targeting teacher interaction as a way to facilitate knowledge exchange and shared teacher practice through a variety of collaborative initiatives, such as communities of practice, professional learning communities, and social networks (Daly & Finnigan, 2009; Hord, 1997; Lieberman & McLaughlin, 1992; Wenger, 1998). The growing literature base around these concepts suggests that ‘relationships matter’ for fostering a climate of trust and a ‘safe and open’ environment to implement reform and engage in innovative teacher practices (Bryk & Schneider, 2002; Louis, Marks, & Kruse, 1996; Coburn & Russell, 2008; Penuel, Fishman, Yamaguchi, & Galagher, 2007).

Social network literature asserts that relationships matter because the configuration of social relationships offers opportunities and constraints for collective action (Burt, 1983, Coleman, 1990; Granovetter, 1973; Lochner, Kawachi, & Kennedy, 1999). For instance, the extent to which an organizational network supports the rate and ease with which knowledge and information flows through the organization may provide it with an advantage over its competitors (Nahapiet & Ghoshal, 1998; Tsai, 2001). While social network studies have mainly concentrated on the consequences of social networks for individuals and groups, less attention has been paid to how social networks are conditioned upon individual characteristics and behavior (Borgatti & Foster, 2003). A developing set of studies in organizational literature is focusing on how attributes of individuals such as personality traits affect their social network (e.g., Burt, Janotta & Mahoney, 1998; Mehra, Kilduff, & Brass, 2001; Madhavan, Caner, Prescott, & Koka, 2008), how individuals select others to engage in relationships (Kossinets & Watts, 2006; McPherson, Smith-Lovin, & Cook, 2001), and how organizations enter into alliances with other organizations (Gulati & Gargiulo, 1999). These studies offer valuable insights in potential individual and organizational attributes that may affect the pattern of social relationships in school teams.

Attributes that are especially worth investigating for their potential to shape the social structure of school teams are demographic characteristics (cf. Ely, 1995; Tsui, Egan, & O’Reilly, 1992). Demographic characteristics are more or less constant elements that typify teachers, their relationships, and schools based on socio-economic factors such as age, gender, teaching experience, and school team composition. Several network studies have suggested that networks are at least in part shaped by demographic characteristics of individuals, their dyadic relationships, and the network (Brass, 1984; Heyl, 1996; Ibarra 1992, 1995; Lazega & Van Duijn, 1997; Veenstra et al., 2007; Zijlstra, Veenstra, & Van Duijn, 2008). For instance, several studies reported that relationships among individuals with the same gender are more likely than relationships among individuals with opposite gender (a so-called homophily effect) (Baerveldt, Van Duijn, Vermeij, & Van Hemert, 2004; McPherson, Smith-Lovin & Cook, 2001). These studies, however, seldom purposely aim to examine the impact of demographic characteristics on social networks and consequently only include few demographic variables of network members. Insights in the extent to which social relationships are formed in the light of multiple individual and organizational demographic characteristics are limited, and even more so in the context of education. We argue that such groundwork knowledge is crucial for all those who aim to optimize social networks in support of school improvement and, ultimately, student achievement.

This chapter aims to examine the extent to which social networks in school teams are shaped by individual, dyadic, and school level demographic variables, such as teachers’ gender and age, school team composition and team experience, and students’ socio-economic status. We conducted a study among 316 educators in 13 Dutch elementary schools. Results of this study were expected to increase insights in the constant social forces that may partly define teachers’ relationships in their school teams, and discover potential tendencies around, for example, homophily and structural balance. Based on a literature review of social network studies that include demographic variables in a wide range of settings, we pose several hypotheses on the extent to which demographical variables at the individual, dyadic, and school level may affect teachers’ social networks.


Individual level demographics that may shape teachers’ social networks

Social network literature has suggested various individual demographic characteristics to affect their pattern of relationships, and as such social networks as a whole (Heyl, 1996; Lazega & Van Duijn, 1997; Veenstra et al., 2007; Zijlstra, Veenstra, & Van Duijn, 2008). Following these suggestions, we will first review how individual level demographic characteristics may affect teachers’ social networks. We focus on the individual demographics gender, formal position, working hours, experience at school, age, and grade level for their potential influence on teachers’ patterns of social relationships and school teams’ social network structure.

Gender. The likelihood of having relationships in a network may be associated with gender (Metz & Tharenou, 2001; Moore, 1990; Stoloff et al., 1999; Veenstra et al., 2007; Zijlstra, Veenstra, & Van Duijn, 2008). Previous research has indicated that gender affects network formation (Burt et al., 1998; Hughes, 1946; Ibarra, 1993, 1995, Moore, 1990; Pugliesi, 1998; Van Emmerik, 2006) and that, in general, women tend to have more relationships than men (Mehra, Kilduff, & Brass, 1998). These differences are already found in childhood (Frydenberg & Lewis, 1993) and continue to exist through life (Parker & de Vries, 1993; Van der Pompe & De Heus, 1993). In various settings and cultures, both men and women were found to use men as network routes to achieve their goals and acquire information from more distant domains (Aldrich et al., 1989; Bernard et al., 1988). Following these findings, we hypothesize that male teachers will have a higher likelihood of receiving more relationships than female teachers, and women will send more relationships than men (Hypothesis 1a).

Formal position. Previous research in organizations (Lazega & Van Duijn, 1997; Moore, 1990) and education (Coburn, 2005; Coburn & Russell, 2008; Daly & Finnigan, 2009; Heyl, 1996) suggests that the formal position of individuals may be related to their relational activity and popularity. For instance, Lazega & Van Duijn (1997) found that lawyers were more often sought out for advice when they held a higher hierarchical position. Research has indicated that the network position of an organizational leader is important in terms of access and leveraging social resources through social relationships as well as brokering between teachers that are themselves unconnected (Balkundi & Harrison, 2006; Balkundi & Kilduff, 2005). In line with these studies, we expect that principals will be more sought out for work related discussions than teachers. We also expect that principals will report to be involved in more relationships than teachers, since they depend on these relationships to gather information and convey knowledge, plans, and expertise to support student learning and monitor the functioning of teachers and the school. Moreover, principals are reported to occupy a strategic position in the flow of information between the district office and teachers and relay important policy and organizational information from the district office to the teachers (Coburn, 2005; Coburn & Russell, 2008). Therefore, we hypothesize that principals have a higher likelihood of sending and receiving relationships (Hypothesis 1b).

Working hours. In addition, the number of working hours that an educator spends at the school may also affect his/her opportunity to initiate and maintain social relationships. Recent research suggests that the relationship between network embeddedness and job performance is related to working hours (Van Emmerik & Sanders, 2004). In line with this finding, it is hypothesized that educators who work full time will have a higher probability of sending and receiving relationships than educators with part time working hours (Hypothesis 1c).

Experience at the school. Another demographic characteristic that may affect an individual’s pattern of relationships is seniority, or experience at the school. The previously mentioned law study (Lazega & Van Duijn, 1997) indicated that senior lawyers had a higher probability of being sought out for advice than junior lawyers. Besides having more work experience, a perceived network advantage of senior lawyers may be that they have built more strong, durable, and reliable relationships over time, and therefore have access to resources that are unattainable for more junior lawyers. Accordingly, we hypothesize that educators who have more experience in their school team have a higher likelihood of sending and receiving work discussion relationships than educators who have less experience in the school team (Hypothesis 1d).

Age. Network research in other contexts found age differences in relation to the amount of relationships that individuals maintain (Cairns, Leung, Buchanan, & Cairns, 1995; Gottlieb & Green, 1984). In general, these studies suggest that the amount of relationships that people maintain tend to decrease with age. However, with increased age, experience at the school also increases together with the amount of relationships based on seniority (Lazega & Van Duijn, 1997). In concordance with the latter, we hypothesize that age will positively affect the probability of work related ties, meaning that older teachers are more likely to send and receive work related relationships than younger teachers (Hypothesis 1e)

Grade Level. Within schools, formal clustering around grade level may affect the pattern of relationships among educators. The grade level may to a certain extent affect the amount of interaction among educators since grade level teams may have additional grade level meetings and professional development initiatives are often targeted at the grade level (Daly et al., in press; McLaughlin & Talbert, 1993; Newmann, Kings, & Youngs, 2000; Newmann & Wehlage, 1995; Wood, 2007; Stoll & Louis, 2007). Dutch elementary schools are relatively small compared to U.S. elementary schools, and are often divided into a grade level team for the lower grades (K – 2) and a grade level team for the upper grades (3 – 6). The amount of relationships that teachers have, may partly be defined by the requirements of and opportunities provided by their grade level team. We may expect that teachers that teach upper grade levels send and receive more relationships than teachers that teach lower grade levels because of the increasingly diverse and demanding curriculum in the upper grades combined with intensified student testing and preparation for education after elementary school. These conditions may require more work related discussion of upper grade level teachers than of lower grade level teachers. As such, we expect that teachers that teach upper grade levels have a higher likelihood of sending and receiving relationships than teachers that teach lower grade levels (Hypothesis 1f).

Dyadic level demographics that may shape teachers’ social networks

Dyadic level demographics are demographics that typify the relationship between two individuals. Dyadic level effects give insights in network homophily. Network homophily is arguably the most well-known social network concept that often explicitly focuses on demographic characteristics of network members. The concept of homophily, also known by the adage ‘birds of a feather flock together’, addresses similarity between two individuals in a dyadic (paired) relationship. Homophily literature builds on the notion that individuals are more likely to develop and maintain social relationships with others that are similar to them on specific attributes, such as gender, organizational unit, or educational level (Marsden, 1988; McPherson & Smith-Lovin, 1987; McPherson, Smith-Lovin, & Cook, 2001). Similarly, individuals who differ from each other on a specific attribute are less likely to initiate relationships, and when they do, heterophilous relationships also tend to dissolve at a faster pace than homophilous relationships (McPherson et al., 2001).

Homophily effects result from processes of social selection and social influence. Social selection refers to the idea that individuals tend to choose to interact with individuals that are similar to them in characteristics such as behavior and attitudes. At the same time, individuals that interact with each other influence each others’ behavior and attitudes, which may increase their similarity (McPherson et al., 2001). This is a process of social influence. In addition, individuals who share a relationship also tend to share similar experiences through their relationship (Feld, 1981).

Homophily is related to the concept of structural balance. In the footsteps of cognitive balance theory, structural balance theory poses that individuals will undertake action to avoid or decrease an unbalanced network (Heider, 1958). Over time, people tend to seek balance in their network by initiating new strong relationships with friends of friends and terminate relationships with friends of enemies or enemies of friends (Wasserman & Faust, 1997). As a result from this tendency towards structural balance, relatively homogenous and strong cliques may be formed that give the network some stability over time (Kossinets & Watts, 2006). Structural balance and network homophily may have also have a negative influence on individuals’ social networks as the resulting network homogeneity and pattern of redundant relationships may limit their access to valuable information and expertise (Little, 1990; Burt, 1997, 2000). In this study we focus on two types of similarity that may define teachers’ relationships, namely gender similarity and grade level similarity.

Gender similarity. A dyadic attribute that may affect teachers’ patterns of social relationships is the gender similarity between two teachers. Several studies have shown that work and voluntary organizations are often highly gender segregated (Bielby & Baron, 1986, McGuire, 2000; McPherson & Smith-Lovin, 1986, 1987; Popielarz, 1999; Van Emmerik, 2006). This gender homophily effect already starts at a young age (Hartup, 1993; Cairns & Cairns, 1994; Furman & Burmester, 1992). In the context of education, Heyl (1996) suggested an effect of gender homophily on interactional patterns among teachers, indicating that for men and women relationships with the opposite gender are less frequent or intense than relationships among men or relationship among women. In line with this suggestion, we hypothesize a homophily effect for gender, meaning that educators will prefer same-gender relationships over relationships with teachers of the opposite gender (Hypothesis 2a).

Grade level similarity. Another dyadic attribute that may shape the pattern of teachers’ relationships is the grade level. In the Netherlands, schools are relatively small compared to the Unitesd States, with often only one full time or two part time teachers per grade level. Commonly, Dutch school teams are formally divided into two grade level levels representing the lower (‘onderbouw’, often K-2 or K-3) and upper grades (‘bovenbouw’, often grades 3-6 or 4-6), which are often located in close physical proximity. Recent research suggests that teachers who are located closely to each another are more likely to interact with each other than with teachers that are less physically proximate (Coburn & Russell, 2008). Moreover, most schools have separate breaks for the lower and upper grades, and some schools hold additional formal meetings for the lower/upper grades to discuss issues related to these grades. Since shared experiences are argued to result in greater support among individuals (Feld, 1981; Suitor & Pillemer, 2000; Suitor, Pillemer, & Keeton, 1995), these organizational features will increase the opportunity for teachers from the same grade level to interact relative to teachers from a different grade level. Therefore, we hypothesize a homophily effect for grade level, meaning that teachers will more likely maintain relationships with teachers from their own grade level than with teachers that teach the other grade level (e.g., lower or upper level) (Hypothesis 2b).

School level demographics that may shape teachers’ social networks

Although teachers can often choose with whom they interact, the social structure of their school’s network is partly outside their span of control (Burt, 1983; Brass & Burkhardt, 1993; Gulati, 1995). Just as individual relationships may constrain or support a teacher’s access to and use of resources (Degenne & Forse, 1999), the social structure surrounding the teacher may influence the extent to which teachers may shape their network so as to expect the greatest ‘return on investment’ (Burt, 1992; Flap & De Graaf, 1989; Ibarra, 1992, 1993, 1995; Lin & Dumin, 1986; Little, 1990). Because of the embeddedness and interdependency of individuals in their social network, relationships and attributes at a higher level will affect lower-level relationships (Burt, 2000). As such, demographic characteristics at the school level may affect teachers’ patterns of relationships. We pose that the following school level demographic characteristics affect teachers’ pattern of social relationships: gender ratio, average age, school team experience, school size, school team size, and socio-economic status of the schools’ students.

Gender ratio and average age. Above and beyond the influence of individual demographics on the tendency to form relationships, there may be aggregates of these individual demographics at the level of the school team that may affect teachers’ tendency to form and maintain relationships. Research in a law firm demonstrated that above the influence of individual level seniority, a lawyer’s position in the firm’s network was in part dependent on the ratio of juniors to seniors in the team (Lazega & Van Duijn, 1997). For school teams, a compositional characteristic that may affect patterns of relationships is gender ratio, or the ratio of the number of female to male teachers. In a school team with a high ratio of female teachers (which is not unusual in Dutch elementary education) male teachers have fewer options for homophily friendships with same-sex peers than women. Therefore, male teachers in such a team may have a lower tendency to maintain relationships in general and a higher propensity towards relationships with women than men in school teams with relatively more male teachers. Research confirms that the gender composition of a team may significantly affect gender homophily, with the minority gender often having much more heterophilous networks than the majority (McPherson, Smith-Lovin, & Cook, 2001). Therefore, we expect that the gender ratio of the school team will shape teachers’ social networks. In line with previous empirical work suggesting that women tend to have more relationships than men (Mehra, Kilduff, & Brass, 1998), we expect that teachers in school teams with a high female ratio will have a higher likelihood of sending and receiving ties than individuals in teams with relatively more male teachers (Hypothesis 3a). Along the same lines, if we expect that age will increase the likelihood of sending and receiving relationships, then increased average age of a school team may also enhance the probability of relationships. Therefore, we hypothesize that average age is positively related to the probability of ties (Hypothesis 3b).

Team experience, school size, and team size. Prior research has indicated that individuals are more likely to reach out to others with whom they had previous relationships (Coburn & Russell, 2008). Given the time and shared experiences that are necessary for building relationships, we may assume that the number of years that a school team has been functioning in its current configuration, without members leaving or joining the team, may affect teachers’ lilelihood of maintaining relationships. Therefore we include school team experience as a school level demographic that may positively affect teachers’ patterns of relationships (Hypothesis 3c). Other school demographics that may affect teachers’ inclinations to form relationships are school size (number of students) and team size (number of educators). Previous literature has suggested that the size of organizations and networks is directly related to the pattern of social relationships in organizations (Tsai, 2001). In general, the amount of individual relationships and the density of social networks decrease when network size increases. As such, we may expect a lower probability of relationships in schools that serve more students (Hypothesis 3d) and schools with larger school teams (Hypothesis 3e).

Students’ socio-economic status. Social networks can be shaped by both endogenous and exogenous forces (Gulati, Nohria, & Zaheer, 2000). An exogenous force to the school team that has been demonstrated to affect schools’ functioning is the socio-economic status (SES) of its students (Sirin, 2005; White, 1982). We argue that the socio-economic status of the children attending the school may influence the probability that teachers will form relationships. For instance, teachers’ perceptions of the urgency for communication and innovation may be dependent on the community surrounding the school. Typically, schools that serve more high-needs communities are associated with greater urgency in developing new approaches (Sunderman, Kim & Orfield, 2005), which may relate to an increased probability of relationships among educators. Therefore, we hypothesize that teachers in low SES schools will have a higher probability of having relationships than teachers in high SES schools (Hypothesis 3f).



The study took place at 13 elementary schools in south of The Netherlands. The schools were part of single district that provided IT, financial, and administrative support to 53 schools in the south of The Netherlands. At the time of the study, the district had just initiated a program for teacher development that involved a benchmark survey for the monitoring of school improvement. We selected a subsample of all the district schools based on a team size of 20 or more team members, since trial runs of the p2 estimation models encountered difficulties converging with smaller network sizes and more schools. The original sample consisted of 53 schools that, with the exception of school team and number of students, did not differ considerably from the 13 sample schools with regard to the described demographics.

The context of Dutch elementary schools was beneficial to the study in three ways. First, the school teams were relatively small, which facilitated the collection of whole network data. Second, school teams are social networks with clear boundaries, meaning the distinction of “who is part of the team” is unambiguous for both researchers and respondents. Third, in contrast to many organizations, school organizations are characterized by relatively flat organizational structures, in which educators perform similar tasks and job diversification is relatively small. Often, educators have had similar training backgrounds, and are receiving school wide professional development as a team. Therefore, despite natural differences in individual characteristics, teachers in Dutch elementary school teams are arguably more comparable among each other than organizational employees in many other organizations, making demographic characteristics possibly less related to differences in tasks or task-related status differences.


The sample schools served a student population ranging from 287 to 545 students in the age of 4 to 13. We collected social network data from 13 principals and 303 teachers, reflecting a response rate of 94.5 %. Of the sample, 69.9 % was female and 54.8 % worked full time (32 hours or more). Educators’ age ranged from 21 to 62 years (M = 46.5, sd = 9.9 years). Additional demographic information is depicted in Table 1 and 2.


Social networks. We assessed the influence of demographic variables on a network that was aimed at capturing work related communication among educators. The network of discussing work related matters was selected because it is assumed to be an important network for the exchange of work related information, knowledge, and expertise that may affect individual and group performance (Sparrowe, Liden, Wayne, & Kraimer, 2001). Moreover, according to the previous analysis into network multiplexity (see Chapter 1), this network appeared to be an instrumental network with relatively small overlap with expressive networks.

We asked respondents the following question: ‘Whom do you turn to in order to discuss your work?’ A school-specific appendix was attached to the questionnaire comprising the names of the school team members, accompanied by a letter combination for each school team member (e.g., Ms. Yolanda Brown = AB). The question could be answered by indicating a letter combination for each colleague who the respondent considered part of his/her work discussion network. The number of colleagues a respondent could indicate as part of his/her network was unlimited.

Individual, dyadic, and school level attributes. We collected demographic variables to assess how individual, dyadic, and school level attributes shape the pattern of social relationships among educators. At the individual level, we examined the following individual attributes: gender, formal position (teacher/principal), working hours (part time/full time), number of years experience at school, age, and whether a teacher was teaching in lower grade or upper grade. At the dyadic level, we included similarity of gender and similarity of grade level (lower/upper grade). At the school level, we investigated school size, team size, gender ratio, average age, years of team experience in current formation, and students’ socio-economic status (SES).

Data analysis

Testing the hypotheses

Since our dependent variable consisted of social network data that are by nature interdependent (relationships among individuals), the assumption of data independence that underlies ‘conventional regression models is violated. Therefore, we employed multilevel p2 models to investigate the effect of individual, dyadic, and school level demographics on having work-related relationships (Van Duijn et al., 2004; Baerveldt et al., 2004; Zijlstra, 2008). The p2 model is similar to a logistic regression model, but is developed to handle dichotomous dyadic outcomes. In contrast to a univariate logistic regression model, the p2 model controls for the interdependency that resides in social network data. The model focuses on the individual as the unit of analysis. The p2 model regards sender and receiver effects as latent (i.e., unobserved) random variables that can be explained by sender and receiver characteristics (Veenstra, et al., 2007). In the multilevel p2 analyses, the dependent variable is the aggregate of all the nominations a team member sent to or received from others. A positive effect thus indicates that the independent demographic variable has a positive effect on the probability of a relationship. We used the p2 program within the StOCNET software suite to run the p2 models (Lazega & Van Duijn, 1997; Van Duijn, Snijders, & Zijlstra, 2004). This software has been recently modified to fit multilevel data (Zijlstra, 2008; Zijlstra, Van Duijn, & Snijders, 2006). We make use of this recent development by calculating multilevel p2 models for our data.

The social network data in this study have a three-level structure. Network data were collected from 13 schools (Level 3) with 316 educators (Level 2) and 11.241 dyadic relationships (Level 1). To examine the influence of individual, dyadic, and school level demographics on the likelihood of having work related relationships we constructed two multilevel models. In the first multilevel model, the effects of individual and dyadic level demographics on the possibility of having relationships were examined. In the second multilevel model, school level demographic variables were added to the model in order to explain the additional effect of school level demographics on the possibility of having relationships, above and beyond the effects of individual and dyadic level demographics. For the multilevel p2 models, we used a subsample of the 13 schools with a team size of 20 educators or more. We selected this subsample of 13 schools from a larger sample of 53 schools to reduce computing time and to examine schools that were more comparable in network size. Still, each model estimation took about six hours of computing time.

How to interpret p2 estimates

In general, effects in p2 models can be interpreted in the following manner. Results on the variables of interest include both sender effects and receiver effects, meaning effects that signify the probability of sending or receiving a relationship nomination. A positively significant parameter estimate can be interpreted as the demographic variable having a positive effect on the probability of a relationship (Veenstra et al., 2007). For instance, a positive sender effect of formal position with dummy coding (teacher/principal) means that the position with the upper dummy code (principal) will have a higher probability of sending relationships than the position with the lower dummy code (teacher).

To assess homophily effects, dyadic matrices were constructed based on the absolute difference between two respondents. For example, the dyadic relationship between male and female educators would be coded as a relationship between educators with a different gender because the absolute difference between male (dummy variable = 0) and female (dummy code = 1) is 1. Smaller numbers thus represent greater interpersonal similarity in gender. The same procedure was carried out for grade level differences. To facilitate the interpretation of the models, we labeled the dyadic parameters ‘different gender’ and ‘different grade level’. A negative parameter estimate for ‘different gender’ would thus indicate that a

With Our Resume Writing Help, You Will Land Your Dream Job
Resume Writing Service, Resume101
Trust your assignments to an essay writing service with the fastest delivery time and fully original content.
Essay Writing Service, EssayPro
Nowadays, the PaperHelp website is a place where you can easily find fast and effective solutions to virtually all academic needs
Universal Writing Solution, PaperHelp
Professional Custom
Professional Custom Essay Writing Services
In need of qualified essay help online or professional assistance with your research paper?
Browsing the web for a reliable custom writing service to give you a hand with college assignment?
Out of time and require quick and moreover effective support with your term paper or dissertation?