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ABSTRACT
This paper investigates how key elements of school culture are associated with teachers’ capacity to find and act on new information. We analyzed survey data from 3,579 teachers located in 117 schools which were a randomly selected sample from 9 states in the US. We found that school cultural components such as academic press, student support, and trust and respect among teachers promote teachers’ capacity for organizational learning. We also found that the role of teacher professional culture in molding the capacity for organizational learning is critical. In terms of school contexts, we identified that school level (elementary, middle, and high school) was associated with teachers’ capacity for organizational learning in 2 different ways. First, as the school level increases, the capacity for organizational learning tends to decrease. Second, as school level increases, the positive relation between reflective dialogue and teachers’ capacity for organizational learning is weakened. Implications of these results are discussed.
Acknowledgements
We are grateful for the support of The Wallace Foundation for the collection of the data reported in this paper. They are not responsible for the content. An earlier version of this paper was presented at the Annual Conference of the International Congress for School Effectiveness and Improvement (ISCEI), Cincinnati, USA, in 2015 and also at the Annual Conference of the University Council for Educational Administration (UCEA), Pittsburgh, USA, in 2011.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1. The authors freely acknowledge that they have not reviewed all of the different ways that culture has been used in research on schools. That task is well beyond what we could accomplish in this paper since the concept of culture in education has many levels (student culture, teacher culture, community culture, national culture) as well as very distinct disciplinary perspectives (anthropology, sociology, social-psychology, critical race theory, etc.). We believe that we have been consistent in drawing on the way in which culture has been used in organizational studies that are primarily sociological in perspective.
2. In this regard, we follow a more sociological approach to organizational learning that emphasizes that it involves social (collective) interactions, is contextually and historically specific, and typically involves examining the implications of new information for existing collective routines (Levitt & March, Citation1988). In this regard, it is distinct from the work of Argyris and Schön (Citation1978), which looks primarily at individual learning in an organizational context.
3. If a dependent variable is identified as a result of this capacity for learning, it is most often the presence of a bundle of innovative practices (Tucker, Nembhard, & Edmondson, Citation2007).
4. A graduate student who is also a teacher recently reported that his school’s “professional communities” were called D[A]MIT meetings by the teachers (district mandated instructional talk). This attitude is prevalent in many schools that we have been in the US.
5. The communities of practice literature has its origins in Vygotskian psychology, while the professional community concept is grounded in the sociological literature related to group identity. In the view of the authors of this paper, the distinct origins are of less importance to this paper than their common focus.
6. More details about the sampling and data collection procedures may be found elsewhere (Louis, Leithwood, Wahlstrom, Anderson, & Michlin, Citation2010, pp. 301–318). Although the data are several years old, the policy environment in the sampled states and in the US has not shifted significantly in the past few years, and there is no reason to assume that “new” data would alter the analysis (on the stability of state educational policy cultures, see Louis, Febey, & Gordon, Citation2015).
7. The teacher survey was administered to all teachers in the sampled schools during a staff meeting. It was difficult to calculate exact school-level response rates because of incomplete staff lists. However, because of the method of administration, it was typical to receive a large bundle of responses or no responses at all from a given school. From the original sample design (180 schools), we had complete information (sufficient number of teacher responses in 2008 and complete demographic information) for 134 schools, which is the basis for this analysis.
8. We used a single imputation for Level 2 units since HLM 6 software used for this study can accommodate a single dataset for Level 2 units while it can integrate multiple datasets for Level 1 units.
9. The survey instrument is available from the authors and is included in Louis et al. (Citation2010).
11. For a discussion of “rules of thumb” regarding variance inflation factors, see O’brien, Citation2007.
12. Specifically, we checked the variance inflation factor (VIF) by identifying whether a predictor has a strong linear association with the other predictors. And we concluded that there was no cause for serious concern about multicollinearity. Although presented in more detail elsewhere, the construct validity (i.e., convergent and discriminant validity) of our measures of school culture was also supported in a confirmatory factor analysis measurement model.
13. The normality of the Level 2 dataset appeared to be satisfied when we plotted “chipct” against Mahalanobis distance, clearly showing a 45 degree line.
14. More details about descriptive statistics and correlations of the measures are presented in Appendices 1, 2, and 3.
15. We used group-mean centering for the Level 1 predictors, since, conceptually, it is reasonable to assume that individual teachers’ perceptions of organizational learning as well as school culture variables are more influenced by individual school organization’s characteristics to which teachers belong rather than the average characteristics of the whole-sample schools. Specifically, we think that each school organization can be regarded as a norm-setting group that influences individual teachers’ standards and norms of certain collaborative or collective behaviors (e.g., professional community, organizational learning). For whatever reasons, if individual teachers want to be part of the school organization, they will have to choose the level of acceptance of the norms and standards of collaborative or collective behaviors, expected from the school organization (cf. De Fraine, Van Damme, & Onghena, Citation2002). When individual teachers choose their attitudes of such school organization’s norms and standards, they would go through socio-psychological processes where they compare their collaborative or collegial behaviors to those of their peers within the school organization (cf. Enders, Citation2013; Hofmann & Gavin, Citation1998). According to their observation of peers and identification of their relative position, individual teachers would develop their feelings that would shape their motivation to choose the level of accepting collaborative or collective norms (e.g., certain aspects of school culture) set by the school organization (cf. De Fraine, Van Damme, & Onghena, Citation2002; Enders, Citation2013). This kind of organizational dynamics, mainly due to membership composition, is called a “frog pond effect” (Hofmann & Gavin, Citation1998, p. 637).
16. While adding a common set of Level 2 predictors (or the same Level 2 predictors) in Level 1 slopes of interest is more common in the analysis of cross-level interactions, in this study we added only one Level 2 predictor (i.e., building level) in the slopes of teacher professional community, as previous research (e.g., Wahlstrom & Louis, Citation2008) suggests that different levels of activities around teacher professional community are found by building level. In addition to this conceptual reason, we adopted this analytical approach in order to make our final model parsimonious (see Raudenbush & Bryk, Citation2002, p. 151, for this approach).
17. The variance within schools explained was computed by (0.720 – 0.303)/0.720. The variance between schools explained was calculated by (0.113 – 0.035)/0.113. The total variance explained was computed by ((0.720 – 0.303) + (0.113 – 0.035))/ 0.720 + 0.113.
Additional information
Notes on contributors
Karen Seashore Louis
Karen Seashore Louis is a Regents Professor and the Robert H. Beck Chair in the Department of Organizational Policy, Leadership, and Development at the University of Minnesota. She has also served as the Director of the Center for Applied Research and Educational Improvement at the University of Minnesota, Department Chair, and Associate Dean of the College of Education and Human Development. Her work focuses on school improvement and reform, school effectiveness, leadership in school settings, and the politics of knowledge use in education. Her most recent books include Building Strong School Cultures: A Guide to Leading Change (with Sharon Kruse, 2009), Linking Leadership to Student Learning (with Kenneth Leithwood, 2011), and Educational Policy: Political Culture and Its Effects (2012). A Fellow of the American Educational Research Association, she also served as the Vice President of Division A, and as an Executive Board member of the University Council for Educational Administration. She has received numerous awards, including the Lifetime Contributions to Staff Development award from the National Staff Development Association (2007), the Campbell Lifetime Achievement Award from the University Council for Educational Administration (2009), and a Life Member designation from the International Congress for School Effectiveness and School Improvement.
Moosung Lee
Moosung Lee holds one of the University of Canberra’s prestigious Centenary Professor appointments, 10 of which have been made across the University’s five strategic areas of research. Having been appointed full professor within 4.5 years of completing his PhD, Moosung is currently the University’s youngest Centenary Professor. Prior to joining the University of Canberra, he held appointments as Associate Professor and founding Deputy Director of the Education Policy Unit at the University of Hong Kong. He has published widely in high-quality academic forums, in the areas of educational leadership and administration, urban education, and comparative education. Some of his articles have received “best paper” awards from academic societies, such as the American Educational Research Association’s (AERA) Special Interest Group and the International Association for the Evaluation of Educational Achievement (IEA). He received the AERA’s Emerging Scholar Award (Division A – Administration, Organization, and Leadership) in 2015.