| Literature DB >> 35936339 |
Beat Rechsteiner1, Miriam Compagnoni1, Katharina Maag Merki1, Andrea Wullschleger1.
Abstract
Individuals in brokerage positions are vital when further developing complex organizations with multiple subgroups only loosely coupled to each other. Network theorists have conceptualized an individual's brokerage as the degree to which a person occupies a bridging position between disconnected others. Research outside the school context has indicated for quite some time that an individual's social capital in the form of brokerage is positively associated with professional development-not only on a collective but also on an individual level. Schools are without any doubt complex organizations with multiple loosely connected stakeholders involved when further developing their educational practice. Thus, it is not surprising that in recent years, the concept of brokerage has gained interest in research on school improvement as well. Up to now, in school improvement research brokerage has been operationalized in different ways: as individuals' formal entitlement to act as intermediaries (formal brokerage), their position within a social network (structural brokerage), or their behavior when linking disconnected groups of staff members (behavioral brokerage). As these perspectives have often been examined separately, this study, as a first step, aimed to simultaneously assess school staff members' formal, structural, and behavioral brokerage, and examine their degree of interrelatedness. In a second step, associations of brokerage with professional well-being were analyzed. Even though there is evidence for the positive impact of brokerage on professional development, only little is known about its associations with professional well-being. In a third step, interaction effects were examined when formal brokerage is congruent or incongruent with other facets of brokerage. Based on a sample of 1,316 school staff members at 51 primary schools in the German-speaking part of Switzerland, we conducted both bivariate correlational and multiple-group structural equation modeling analyses. The findings revealed that formal, structural, and behavioral brokerage are interrelated facets. However, formal entitlement did not determine either structural position or behavior. Moreover, brokerage within schools was only partially related to professional well-being. In the discussion section, the study's key contributions and practical implications are presented in detail.Entities:
Keywords: brokerage; principals; professional development; professional well-being; social capital; teachers
Year: 2022 PMID: 35936339 PMCID: PMC9346444 DOI: 10.3389/fpsyg.2022.885616
Source DB: PubMed Journal: Front Psychol ISSN: 1664-1078
Measurement instrument to assess school actors’ behavioral brokerage.
| Item | N |
|
| r | α-drop | α |
| 1. I introduce people to each other who might have a common strategic work interest. | 1,115 | 3.48 | 1.19 | 0.73 | 0.78 | – |
| 2. I see opportunities for collaboration between people. | 1,118 | 4.05 | 1.03 | 0.68 | 0.81 | – |
| 3. I point out the common ground shared by people who have different perspectives on an issue. | 1,116 | 3.79 | 1.03 | 0.58 | 0.85 | – |
| 4. I introduce people when I think they might benefit from becoming acquainted. | 1,115 | 3.77 | 1.16 | 0.75 | 0.77 | – |
| Latent construct |
M = mean and SD = standard deviation. r
FIGURE 1Illustration of the data collection for both the online questionnaire at the beginning of the school year 2019/20 and the three waves in which daily practice logs were collected.
Intercorrelations between demographic variables, brokerage (formal, structural, and behavioral), and school staff’s well-being.
| Variables | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
|
| |||||||
| 1. Tenure (in years) | – | ||||||
| 2. Percentage of full-time employment | −0.068 | – | |||||
|
| |||||||
| 3. Formal brokerage |
| 0.155 | – | ||||
| 4. Structural brokerage | 0.200 | 0.130 | 0.273 | – | |||
| 5. Behavioral brokerage |
|
| 0.106 | 0.177 | – | ||
|
| |||||||
| 6. Competency improving educational practice | 0.116 |
| 0.073 | 0.177 | 0.270 | – | |
| 7. Satisfaction |
|
|
|
| 0.065 | 0.324 | – |
| 8. Stress |
| 0.153 |
|
|
| 0.095 | –0.313 |
Correlation coefficients are given at the individual level. ***p < 0.001, **p < 0.01, *p < 0.05; non-significant effects in italics. Latent construct (5) is based on four items, each rated on a 6-point Likert scale ranging from 1 (strongly disagree) to 6 (strongly agree).
Comparison of test statistics when establishing configural, weak, and strong measurement invariance across groups.
| Model | df | AIC | BIC | χ | △χ | △df | |
| Configural invariance | 28 | 27,226 | 27,521 | 85.395 | – | – | – |
| Weak invariance | 31 | 27,229 | 27,509 | 94.132 | 7.386 | 3 | 0.061 |
| Strong invariance | 38 | 27,271 | 27,517 | 150.399 | 59.618 | 7 | < 0.001 |
Fit indices for the configural, weak, and strong invariance model.
| Model | χ | RMSEA [90% CI] | CFI | TLI | SRMR | Tenable? |
| Configural invariance | 81.794 | 0.063 [0.047 –0.079] | 0.97 | 0.95 | 0.024 | yes |
| Weak invariance | 89.016 | 0.063 [0.048 –0.078] | 0.97 | 0.95 | 0.028 | yes |
| Strong invariance | 145.099 | 0.076 [0.063 –0.089] | 0.95 | 0.92 | 0.041 | yes |
FIGURE 2Results of the multiple group structural equation modeling analysis of formal and non-formal brokerage (cluster = school; MLR). χ (28) = 81.794, p < 0.001, scaling correction factor Yuan-Bentler correction (Mplus variant) = 1.044: CFI = 0.97, TLI = 0.95; RMSEA [90% CI] = 0.062 [0.047 –0.079], SRMR = 0.024. *p < 0.05, **p < 0.01, ***p < 0.001.