Session Information
26 SES 12 C, Digital and Technology Leadership in the Scope of Education
Paper Session
Contribution
Schools are considered knowledge-creating organizations (Harris, 2008) that are in constant exchange with their environment (Bastedo, 2006). Accordingly, educational research assumes that schools primarily innovate effectively when they are involved in learning networks with other schools (Hargreaves, 2003) and/or when there is an exchange of knowledge with other external partners, e.g., universities (Coburn and Penuel, 2016). In the face of current crises and to keep up with social and technological developments, schools are, nonetheless, more than ever requested to implement innovations, some of which are long overdue (Brown and Luzmore, 2021).
Schools’ motivation to innovate arises from different sources connected with cultural, societal, or political changes and transitions (Goldenbaum, 2012). However, the main drivers of innovation in schools are often local competition between institutions and the regressive effects of large-scale, standardized reform strategies (Sahlberg, 2016). Additionally, external driving forces requiring schools or whole education systems to innovate, i.e., disruptive changes in educational environments like the COVID-19 pandemic (Pietsch et al., 2022), natural catastrophes and disasters (Brown and Luzmore, 2021).
Even though the relevance of innovation, networks, and knowledge mobilization for school improvement has been studied extensively (Harris, 2008; Greany, 2018), little is known about knowledge management practices that make expertise accessible for innovation in schools (Cheng, 2021). Research proved that schools tend to maintain long-standing and well-established systems and serve multiple constituents, which makes implementing changes and innovations hard to plan and predict (Tyack & Tobin, 1994).
Thus, for innovations in schools to be successful, continuous “orchestrated complex combinations of vertical and lateral knowledge mobilisation” (Greany, 2018, p. 66) are required. As schools are open systems that constantly interact with their environment (Bastedo, 2006), their importance for innovation and change is exceptionally high when they act as nodes in educational learning networks (see Hadfield et al., 2006). Open Innovation (Chesbrough, 2006) offers considerable potential to better understand how, for example, knowledge can be shared across borders (for example) between organizations. Accordingly, different ways of inventing new ideas and technologies exist. Either they result from internal knowledge and need external paths to market or develop through external knowledge using internal paths to become successful (Chesbrough, 2006). Regarding schools’ central function for society, the relevance of knowledge flows between organizations, the professionalism of school leaders and teachers, and strategic management capabilities to integrate knowledge are particularly high (Bastedo, 2006; Hadfield et al., 2006).
Against this background, our study was guided by the following research questions to make a contribution to the fields of innovation and knowledge mobilization in the public sector, introducing the concept of open innovation (Chesbrough, 2006) as well as empirically investigate the impact of knowledge inflows on pedagogical innovation in schools.1) Do schools incorporate external knowledge for internal innovation? 2) If so, where does this knowledge for internal innovation come from, and to what extent is it used? 3) Does externally mobilized knowledge (open innovation) increase the likelihood of innovations being introduced in schools compared to knowledge mobilization within schools (closed innovation)? 4) Can different effects of knowledge mobilization be identified depending on the type of innovation?
Method
The context of this study is Germany, a nation comprising 16 federal states that are fully responsible for their individual school system. The database of our study is drawn from the third wave of the Leadership in German Schools (LineS) study. Data was collected between August and November 2021 across Germany. The longitudinal study surveyed a random sample of school leader’s representative of Germany in each measurement wave (Pietsch et al., 2022). The forsa Institute for Social Research and Statistical Analysis, a leading survey and polling company in Germany, collected the data as a field service provider. Participants were recruited via its omnibus and omninet panels: a random sample of around 1,000 people aged 14 and above is interviewed on a mixed-topic daily basis, also asking about the current occupation. Thus, school leaders (N = 411) were identified on a random basis, leading to a nationally representative sample for general schools in Germany. The questionnaire comprised 35 item blocks. Of these, we only use a selection of items and scales. The following variables were used as part of our study: Innovations, the dependent variable (e.g., Have any process innovations, i.e., innovations or noticeable changes that affect the pedagogical work of the school, been introduced at your school in the last 12 months? Open innovation was measured following Laursen and Salter (2006) and thus refers to inbound open innovation (“Now we would like to know where the knowledge came from for pedagogical innovations, i.e., teaching and instruction, introduced at your school in the last 12 months.”). Closed innovation is the amount of internal knowledge a school uses for generating, developing, and implementing pedagogical innovations (“The knowledge we used for the innovations came from the school itself/ the teachers of our school.”), measured on a six-point scale ranging from “not at all” to “to an exceptionally high degree.” Innovation Conditions include innovative climate, teacher innovativeness, innovation networking (Slavec Gomezel et al., 2019), and School Leadership to capture leadership for learning (“I ensure that teachers work according to the school’s educational goals” (Pietsch et al., 2019). The effects of open and closed Innovation practices on different types of educational innovation in schools were investigated through latent multinomial logistic regression models in MPLUS 8.4.
Expected Outcomes
Both closed and open innovation depth affect innovations in teaching and learning. The schools in our sample for instructional innovation derive much more knowledge from closed innovation (M = 4.45) than from open innovation (M = 2.39) processes (W(1) = 992.587, p<.001). Results further show a strong correlation between open innovation breadth and depth (r = .84, p < .001), indicating that schools using a wide variety of external sources of knowledge for their innovations incorporated much external knowledge into the school’s internal innovation processes. The external knowledge for internal innovations in schools came primarily from professional training and conferences (M = 3.50). Knowledge rarely came from government agencies (M = 2.29), universities (M = 2.09), and parents (M = 2.09). Open Innovation measures revealed mixed effects of open innovation in schools. Positive effects of closed innovation processes for innovations in schools, especially in teaching and learning, can still be observed. Further, incorporating external knowledge for innovation, i.e., innovation depth, in schools is disproportionately larger with regards to innovations in digital teaching and learning (OR = 4.556, p < .05) and other relevant pedagogical innovations (OR = 5.166, p < 0.05) in schools. Internally, the likelihood of introducing such innovations approximately quintuples. However, the diversity of knowledge sources, i.e., open innovation breadth, has a negative effect on all reported innovations (all p < 0.05 or higher). The intensity of knowledge inflow in schools, i.e., open innovation depth, has a far greater effect on pedagogical innovations in schools than closed innovation processes if the conditions of the individual schools. Besides, innovation is primarily related to the school type, conditions, and contexts. Consequently, there are no generalizable mechanisms for how innovations can ideally be implemented in schools from the outside, but schools can be prepared to be open to appropriate knowledge flows.
References
Bastedo, M. N. (2006). Open Systems Theory. In F. W. English (Ed.), The Encyclopedia of Educational Leadership and Administration (pp. 711–12). Thousand Oaks, CA: Sage. Brown, C., & Luzmore, R. (2021). Educating Tomorrow: Learning for the Post-Pandemic World. Emerald Publishing Limited. https://doi.org/10.1108/9781800436602 Cheng, E. C. K. (2021). Knowledge management for improving school strategic planning. Educational Management Administration & Leadership, 49(5), 824–840. https://doi.org/10.1177/1741143220918255 Chesbrough, H. (2006). Open innovation: a new paradigm for understanding industrial innovation. In H. Chesbrough, W. Vanhaverbeke, & J. West (Eds.), Open innovation: researching a new paradigm (pp. 1-12). New York: Oxford University Press. Coburn, C. E., & Penuel, W. R. (2016). Research–Practice Partnerships in Education. Educational Researcher, 45(1), 48–54. https://doi.org/10.3102/0013189x16631750 Goldenbaum, A. (2012). Innovationsmanagement in Schulen: Eine empirische Untersuchung zur Implementation eines Sozialen Lernprogramms. VS. Greany, T. (2018). Innovation is possible, it’s just not easy: Improvement, innovation and legitimacy in England’s autonomous and accountable school system. Educational Management Administration & Leadership, 46(1), 65–85. https://doi.org/10.1177/1741143216659297 Hadfield, M. et. al. (2006). What does the existing knowledge base tell us about the impact of networking and collaboration? A review of network-based innovations in education in the UK. National College for School Leadership. Hargreaves, D. H. (2003). Education Epidemic: Transforming Secondary Schools Through Innovation Networks. Demos. Harris, A. (2008). Leading Innovation and Change: knowledge creation by schools for schools. European Journal of Education, 43(2), 219–228. https://doi.org/10.1111/j.1465-3435.2008.00343.x Laursen, K., & Salter, A. (2006). Open for innovation: the role of openness in explaining innovation performance among UK manufacturing firms. Strategic management journal, 27(2), 131-150. https://doi.org/10.1002/smj.507 Pietsch, M., Tulowitzki, P., & Cramer, C. (2022). Innovating teaching and instruction in turbulent times: The dynamics of principals’ exploration and exploitation activities. Journal of Educational Change. https://doi.org/10.1007/s10833-022-09458-2 Pietsch, M., Tulowitzki, P., & Koch, T. (2019). On the differential and shared effects of leadership for learning on teachers’ organizational commitment and job satisfaction: A multilevel perspective. Educational Administration Quarterly, 55(5), 705-741. https://doi.org/10.1177/0013161X18806346 Sahlberg P (2016). The global educational reform movement and its impact on schooling. In K. Mundy, A. Green, B. Lingard, & A. Verger (Eds.), The handbook of global education policy (pp. 128–144). Wiley-Blackwell. https://doi.org/10.1002/9781118468005.ch7 Slavec Gomezel, A., & Rangus, K. (2019). Open innovation: it starts with the leader’s openness. Innovation, 21(4), 533–551. Tyack, D., & Tobin, W. (1994). The “Grammar” of Schooling: Why Has it Been so Hard to Change? American Educational Research Journal, 31(3), 453–479. https://doi.org/10.3102/00028312031003453
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