Social Network Analysis as a Driver of Continuous Improvement

A Case Study




COVID-19, Kentucky, instructional coaches, continuous improvement, social network analysis


Social network analysis (SNA) is a research method that, when applied to improvement science, can help leaders understand the strength of relationships within their organization. The COVID-19 pandemic has had a lasting impact on organizational norms, and it has interrupted relationship building efforts. This paper documents a case study of the Kentucky Department of Education (KDE), which deployed SNA techniques to strategically identify areas of growth within its network and design intentional, targeted solutions to improve the network health. As organizations emerge from the pandemic environment and begin to plan continuous improvement efforts, they would be well served to examine the impact of the pandemic on their level of connectedness. The broader impact and generalizability of the case study as well as considerations for replication are also discussed.


Download data is not yet available.

Author Biographies

Matthew B. Courtney, Kentucky Department of Education

MATTHEW B. COURTNEY, Ed.D., is the Policy Advisor to the Office of Continuous Improvement and Support at the Kentucky Department of Education. Email:

Kelly Foster, Kentucky Department of Education

KELLY A. FOSTER, Ed.D., is the Associate Commissioner to the Office of Continuous Improvement and Support at the Kentucky Department of Education. Email:


Adisa, T. A., Antanocopoulou, E., Beauregard, T. A., Dickmanm, M., & Adekoya, O. A. (2022). Exploring the impact of COVID-19 on employee’s boundary management and work-life balance. British Journal of Management. DOI:

Alba, R.D. (1982). Taking stock of network analysis: a decade’s results. Research in the Sociology of Organizations, 1, 39-74.

Almack, J.C. (1922). The influence of intelligence on the selection of associates. School and Society, 16(410). 529-530.

Bento, F., & Garotti, L. (2019). Resilience beyond formal structures: A network perspective towards the challenges of an aging workforce in the oil and gas industry. J Open Innov. Technol. Mark. Complex, 5(1), 15. DOI:

Bonchi, F., Castillo, C., Gionis, A., & Jaimes, A. (2011). Social network analysis and mining for business applications. ACM Transactions on Intelligent Systems and Technology, 2(3). 1-37. DOI:

Borgatti, S. P., Everett, M. G., & Johnson, J. C. (2018). Analyzing social networks, (2). SAGE.

Borgatti, S. P., & Ofem, B. (2010). Social network theory and analysis. Social Network Theory and Educational Change, 17, 29.

Bott, H. (1928). Observation of play activities in a nursery school. Genetic Psychology Monographs, 4(1). 44-88.

Brewer, M. J. (2018), Fuel or fizzle: The role of collaboration network centrality on teacher burnout. Theses and Dissertations--Education Sciences. 43.

Bryk, A. S., Gomez, L., Grunow, A., & LeMahieu, P. (2015). Learning to improve: How America’s schools can get better at getting better. Harvard Education Publishing.

Çakmak, Z., & Akgün, I, H. (2017). A theoretical perspective on the case study method. Journal of Education and Learning, (7)1. 96-102. doi:10.5539/jel.v7n1p96 DOI:

Csardi G., & Nepusz, T. (2006). The igraph software package for complex network research. InterJournal, Complex Systems. 1695. 2006.

Daly, A. J. (2019). Social network theory and educational change. Harvard Education Publishing. Cambridge, MA. p. 271.

Freeman, L. C. (1996). Some antecedents of social network analysis. Connections, 19(1), 39-42.

Froehlich, D. E., Waes, S. V., & Schafer, H. (2020). Linking quantitative and qualitative network approaches: A review of mixed methods social network analysis in education research. Review of Research in Education. 44(1). 244-268. DOI:

Given, L. M. (Ed.) (2008). (Vols. 1-0). SAGE Publications, Inc., DOI:

Grosser, T. J., Lopez-Kidwell, V., & Labianca, G. (2010). A social network analysis of positive and negative gossip in organizational life. Group & Organization Management, 35(2). 177-212. DOI:

Grunspan, D. Z., Wiggins, B. L., & Goodreau, S. M. (2017). Understanding classrooms through social network analysis: A primer for social network analysis in education research. CBE: Life Sciences Education, 13(2). 167-178. DOI:

Hagman, E.P. (1933). The companionship of preschool children. University of Iowa Studies in Child Welfare, 7.

Hwang, T. J., Rabheru, K., Peisah, C., Reichman, W., & Ikeda, M. (2020). Loneliness and social isolation during the COVID-19 pandemic. International psychogeriatrics, 32(10), 1217–1220. DOI:

Liu, W., Xu, Y., & Ma, D. (2021). Work-related mental health under COVID-19 restrictions: A mini literature review. Frontiers in Public Health, 9. 788370. DOI:

Matos, M., McEwan, K., Kanovský, M., Halamová, J., Steindl, S. R., Ferreira, N., Linharelhos, M., Rijo, D., Asano, K., Vilas, S. P., Márquez, M. G., Gregório, S., Brito-Pons, G., Lucena-Santos, P., da Silva Oliveira, M., Leonardo de Souza, E., Llobenes, L., Gumiy, N., Costa, M. I., Habib, N., et al. (2021). The role of social connection on the experience of COVID-19 related post-traumatic growth and stress. PLoS ONE, 16(12): e0261384. DOI:

Michinov, E., Ruiller, C., Chedotel, F., Dodeler, V., & Michinov, N. (2022). Work-from-home during COVID-19 lockdown: When employees’ well-being and creativity depend on their psychological profiles. Frontiers in Psychology, 13, 862987. DOI:

Oakman, J., Kinsman, N., Stuckey, R., Graham, M., & Weale, V. (2020). A rapid review of mental and physical health effects of working at home: How do we optimise health?. BMC Public Health, 20. 1-13. DOI:

Pancani, L., Marinucci M., Aureli, N., and Riva, P. (2021). Forced social isolation and mental health: A study on 1,006 Italians under COVID-19 Lockdown. Frontiers in Psychology, 12. 663799. doi: 0.3389/fpsyg.2021.663799 DOI:

Park, S., Hironaka, S., Carver, P., & Nordstrum, L. (2013). Continuous improvement in education. [White Paper] Carnegie Foundation for the Advancement of Teaching.

Pelly, D., Daly, M., Delaney L., and Doyle O. (2022). Worker stress, burnout, and wellbeing before and during the COVID-19 restrictions in the United Kingdom. Frontiers in Psychology, 13.823080. doi: 10.3389/fpsyg.2022.823080 DOI:

Pietrabissa, G., & Simpson, S. G. (2020). Psychological consequences of social isolation during COVID-19 outbreak. Frontiers in Psychology, 11. 2201. doi: 10.3389/fpsyg.2020.02201 DOI:

R Core Team (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.

Santini, Z. I., Jose, P. E., Cornwell, E. Y., Koyanagi, A., Nielsen, L., Hinrichsen, C., Meilstrup, C., Madsen, K.R., & Koushede, V. (2020). Social disconnectedness, perceived isolation, and symptoms of depression and anxiety among older Americans (NSHAP): A longitudinal mediation analysis. The Lancet, (5)1. 62-70. DOI:

Varshney, D. (2021). How about the psychological pandemic? Perceptions of COVID-19 and work–life of private sector employees—A qualitative study. Psychological Studies, 66(3). 337–346. DOI:

Wellman, B. (1926). The school child’s choice of companions. Journal of Educational Research, 14(2). 126-132. DOI:

Xiong R., Xia Y., & Tian, B. (2022). Social Disconnectedness and Mental Health Problems During the COVID-19 Pandemic in China: A Moderated Mediation Model. International Journal of Public Health, 67. 1604742. doi:10.3389/ijph.2022.1604742 DOI:






Best Practice Articles