Innovation is seen as a key factor not only in strengthening economic competitiveness in the business sector but also improving quality and performance in public services, including education. Innovation processes are highly complex (Van de Ven et al., 2008; Warford, 2017): their management requires not only advanced leadership skills, but also the availability of relevant data. Measuring innovation processes and outcomes is a major challenge in general in innovation research Godin, 2005), and in particular in education (OECD, 2014). Innovation surveys producing data on innovation processes and outcomes are regularly conducted in the business sector, but they are rare in the public sector, especially in education (Arundel, 2016).

The proposed presentation will be based on the outcomes of the research project “Innova”, implemented by the Research Group on Higher Education and Innovation of ELTE University, Budapest.[1] This project aims at analysing the emergence and spread of local/school level innovations initiated by teachers and teacher teams, on the basis of quantitative and qualitative data collected at the level of educational units (such as schools or university departments). The Innova project is a follow up of an earlier empirical research on the impact mechanisms of educational development interventions supporting curriculum changes (“ImpAla” project). The ImpAla project has demonstrated that the impact of education development interventions is more substantial and more sustainable in schools showing the characteristics of a "knowledge intensive” or “learning” organisations (Fazekas, 2017).

The Innova project has a special focus on “workplace innovation” (Kesselring et al., 2014), “practice-based innovation” (Ellström, 2010; Melkas - Harmaakorpi, 2012), “employee-driven innovation” (Høyrup, 2012) or “invisible innovation” (Fuglsang, 2010). A special attention is given to innovations created or adopted/adapted by individual teachers, teaching teams and educational units as organisations. The main research questions are. “How do individual, team level and organisational factors influence the willingness and capability of individuals, teams and organisation to innovate in education?”; ”What is the impact of these factors on the success or failure of innovation processes?”; and ”How do they influence the impact of innovations on quality and effectiveness?”

Innovation has been defined in the Innova project as deviation from routine practice with the aim of improving the quality and effectiveness of teaching practices and broader school level operations. The analytical framework behind the data collection is based on a systematic review of literature on innovation, in general, and innovation in the public sector and the education sector, in particular. The analytical framework distinguishes four different perspectives of looking at innovation processes: (1) innovation as a product; (2) the birth of innovations; (3) the agents involved in creating/adopting innovations; and (4) the diffusion of innovations.[2] Besides this the temporal and spatial dimensions of innovation processes have also been taken into account. A number of hypothetical variables (both discrete and scalable) have been defined in function of these perspectives. These variables have been included in a static and a dynamic model: the first supporting mainly description, the second supporting the analysis of causal relationships.

The analytical framework of the Innova project has been strongly influenced by approach of the “Minnesota Innovation Research Project” (MIRP) which stresses the temporal dimension and the evolutionary nature of innovation, looking at innovation processes from a complexity perspective (Van de Ven et al., 2008). The MIRP analytical model has been directly guiding our case studies which have been complementing our quantitative analyses.

[1] Project number: 115857. The project is funded by the Hungarian National Research, Development and Innovation Office. See the English website of the project here: http://halaszg.ofi.hu/INNOVAENGLISHWEBSITE/INDEX.htm.

[2] For a detailed presentation of the analytical framework see the website of the Innova project (http://halaszg.ofi.hu/INNOVAENGLISHWEBSITE/Products.htm)

The presentation will use data from two education sector innovation surveys. In both surveys electronic questionnaires – based on the analytical framework presented above – have been (will be) sent to all operating education units in Hungary. Both surveys cover all subsystems of education, from pre-school to higher education. The first survey was conducted in early 2017: it resulted in a database of close to five thousand cases. The second data collection is to be executed in the spring of 2018. In the first survey we collected organisational level data from heads of institutions (the outcomes of the analysis of these data were presented at the 2017 ECER conference in Copenhagen – see Halász, 2017). In the second survey (in progress) we shall collect data from both heads and employees (teachers). At the time of the submission of this proposal the data collection instruments are being tested and finalised. Data from the surveys allow the creation of composite innovation indexes used to “measure” the intensity of the innovation activities of individual teachers and educational units as organisations. A rich set of background and contextual variables at both individual and organisational level allow advanced correlational analyses, including the testing of complex causal models, taking the limitations of the cross-sectional database into account. The data collection instrument contains, among others, questions about the source institutions of adopted innovations: this allows the analysis of networks of innovation diffusion. Case studies, being conducted parallel with the questionnaire-based data collection and providing qualitative data, allow the strengthening of the reliability of our data through triangulation, the deepening of analysis and they provide illustration to our findings based on the analysis of quantitative data. The analysis of qualitative data is supported by the MIRP model mentioned above.

The proposed presentation will analyse the impact of organisational characteristics of educational institutions on their innovation activity based on data from the two education sector innovation surveys mentioned above. The results of data from our first innovation survey have demonstrated that the impact of internal (bottom up) innovations correlates with higher level performance in educational institutions having higher level "dynamic capacities" or showing the characteristics of "learning organisations" (Halász, 2017). Our second data collection (to be completed by the end of spring of 2018) will allow the connection of individual and organisational data. Based on this, will shall present the outcomes of analyses aimed at revealing the impact of specific features of the organisational environment on the innovation activity of individual teachers and teacher teams. It is assumed that the intensity of innovations initiated by individual teachers or teacher teams and their quality is significantly higher in educational units with higher level dynamic or adaptive capacities, including factors such as internal knowledge management, capacity development, supportive leadership and active participation in development programs. A further assumption is that our (quantitative and qualitative) data will confirm the highly complex nature of school level innovation processes: they will uncover the risks accompanying these processes and they will also help to understand better the conditions of successes and failures in educational innovation processes.

Arundel, A., Bowen Butchart, D., Gatenby-Clark, S. J. and Goedegebuure, L. (2016). Management and Service Innovations in Australian and New Zealand Universities. Preliminary report of descriptive results, June 2016. Australian Innovation Research Centre, Hobart and LH Martin Institute, Melbourne Ellström, Per-Erik (2010). Practice-based innovation: a learning perspective. Journal of Workplace Learning. 22(1/2. pp. 27-40 Fazekas Ágnes (2017). The impact of EU-funded development interventions on teaching practices in Hungarian schools. Forthcoming Fuglsang, Lars (2010). Bricolage and invisible innovation in public service innovation. Journal of Innovation Economics & Management 1(5). pp. 67-87. Godin, B. (2005). Measurement and Statistics on Science and Technology: 1920 to the Present. London: Routledge Halász Gábor (2017). Measuring innovation in education: the outcomes of an education sector innovation survey. Paper presented at the 2017 ECER conference, Copenhagen, 2017 august 22-25 Høyrup, Steen (2012). Employee-Driven Innovation: A New Phenomenon, Concept and Mode of Innovation. in: Høyrup, S. - Bonnafous-Boucher, M. - Hasse, C - Møller, K. - Lotz, M. (Eds.): Employee-driven innovation: A new approach. Palgrave Macmillan. pp. 3-33 Kesselring, Alexander – Blasy, Cosima – Scoppetta, Anette (2014). Workplace Innovation. Concepts and indicators. European Commission Melkas, Helina and Harmaakorpi, Vesa (2012). Introduction. in: Melkas, Helina and Harmaakorpi, Vesa (eds.): Practice-Based Innovation: Insights, Applications and Policy Implications. Springer. pp. 1-17 OECD (2014). Measuring Innovation in Education: A New Perspective, OECD Publishing. Paris Van de Ven, A. H., Polley, D. and Garud, R. (2008). The innovation journey. Oxford University Press Warford, Mark K. (2017). Educational Innovation Diffusion: Confronting Complexities. in. Sidorkin, M. - Warford M. K. (eds.). Reforms and Innovation in Education. Implications for the Quality of Human Capital. Springer International Publishing. pp. 11-36