In conditions of Volatility, Uncertainty, Complexity and Ambiguity (VUCA) all countries face the need for change with limited resources both material and contextual (shortage of organizational skills, creativity, innovativeness, readiness for change, etc). Educational systems as one of the most important social institutions are often criticized for lagging behind. The 2020 shock has only deepened this demand for urgent innovations from the one side and the rigidity of the education system from the other. At the same time, the situation with the pandemic forced societies to seek for new resources and actors to develop creative ideas and solutions for educational transformation. The objective of this research is to study the key actors of innovation, representing different organizations in order to enhance their capacity. This paper is a contribution to innovation management in education. It conceives innovation as an important process in educational organisations and exploring these processes as contribution to better understand how educational organisations work. It sees innovation management as a key area of managing these organisations. 

Differences in education policy in each European country defines development of a variety of education innovation ecosystems. Their key feature is the presence of a large number of interconnected and interacting actors producing, spreading or, often, blocking innovations. A major challenge for researchers exploring innovation processes in the education sector is to identify the relevant actors whose behaviour determines the dynamics of the education innovation ecosystem. These may range from isolated individual teachers creating innovative solutions in their classroom through networks of schools and service providers to large private IT companies developing a new education oriented profile or national regulators setting the rules of the game. The literature on (educational) innovation ecosystems is not conclusive. Oh et al. (2016) warns about the fuzzy nature of the definition. Therefore in our paper we strived for a more operationalized approach utilizing the models of society-level ecosystem of educational innovation (SOECOEI) and educational entrepreneur-level ecosystem of educational innovation (ECOEI) based on Wu and Lin (2019). The two models combine the perspectives of bottom-up initiated educational innovations and the top-down facilitating environment to realise these innovations. The three main components of innovation ecosystems are actors (who perform innovations), artifacts (innovative services and products), and activities (what is the subject of innovation, which process or product are going to be invented, adjusted, produced or implemented). Indeed, it is crucial not only to identify these three elements but the types of interactions between them. These actors might be led by different motivations and guided by different values.

In our study we explore what are the main motivations of actors and what characterises their value structure in the landscape of the two different educational ecosystems.

We discuss how we could activate the existing potential of key innovative actors in such different ecosystems. A comparative perspective (Russia an Hungary) allows a deeper understanding of innovation processes and a deep information to provide support to educational decision-makers in creating and sustaining education innovation ecosystems that could contribute to improve student learning.

In this study the motivation and the values of two different groups of actors in two different education innovation ecosystems are compared, based on the use of the same data collections instruments. The Russian sample consists of participants of the competition of innovations in education (KIVO). The project was set up to explore existing grassroots initiatives in education. The contest supports a broad community of individual developers and startups in the field of new solutions in education. KIVO seems to be a good platform for data collection, as it allows an opportunity to ensure that each respondent is involved in innovative activities in education due to the fact of their participation in the competition. The data was collected as part of an online survey. The study, represented in this paper, involved samples of contest participants for two years: 2015 (n=424) and 2018 (n=355). The Hungarian data provided by a research, devoted to the spread of bottom-up innovations (Innova). The sample which is used in this paper included school teachers from a list of selected Hungarian educational institutions. Questionnaires (in the form of structured interviews) from those teachers who are either especially innovative educators or educators who essentially work routinely but also look for new solutions in his/her work were used (n=181), while teachers who usually resist new solutions were excluded from the sample. Information about the level of innovativeness of respondents was provided on the one hand by the principals (as they were asked to select an innovative and a routinely working employee for the interview) and on the other hand by the interviewer (based on their perceptions regarding the content of the interview). Regarding values, we used the validated scale of human values provided by S. Schwartz. To study the values of innovators, we compared our samples with the representatives of the Russian and Hungarian population provided by the European Social Survey (ESS). To study the motives of innovators in education, we have developed a separate methodology based on the Panel Study of Entrepreneurial Dynamics for our research tasks.

We compared how the ecosystem institutions of the two countries contribute to creating an environment for innovation. In Hungary, the educational innovation system is flexible enough to allow innovation at the local level. School teachers become key drivers of implementing new solutions. They do not need to go beyond the formal system. Russian education ecosystem is more structured. The innovations from the local level do not have organised ways to the top. Therefore drivers of innovations are actors external to the formal system – entrepreneurs, startupers. Comparing two countries' educational innovators' values to the values of the society and examining their motives we found similarities and differences that highlight the complex interplay between society-level and educational entrepreneur-level ecosystems. For both countries’ innovators values of Self-Direction, Benevolence and Universalism were the most high-ranked. The desire for Self-Direction is not surprising for innovators – people who create innovative things and acting independently. In the same time there a slight difference in the average values of Stimulation and Achievement, which were more expressed among Russian innovators than among Hungarian ones. The value of the innovation motive in both cases is quite high and the value of motivation for self-realization is smaller. For both groups of innovators, the desire to be at the frontier of technology, to implement new ideas is significantly more important than improving their own social status and getting approval from others. Though educational ecosystems in both countries include all types of core elements: actors, activities and artifacts, the intensity of the ties between them is different. Combining the perspectives of ECOEIs and SOECOEIs we can better understand the co-evolving nature of bottom-up and top-down processes, the embeddedness of individual level factors in the wider socio-economic context and the role each stakeholder can play in facilitating educational transformation.

Arundel, A., Bloch, C., & Ferguson, B. (2019). Advancing innovation in the public sector: Aligning innovation measurement with policy goals. Research Policy, 48(3), 789-798. Gomes, V.L. A., Facin, A. L. F., Salerno, M. S., & Ikenami, R. K. (2018): Unpacking the innovation ecosystem construct: Evolution, gaps and trends. Technological Forecasting and Social Change, 136, 30-48 Germak, A. J., & Robinson, J. A. (2014). Exploring the motivation of nascent social entrepreneurs. Journal of Social Entrepreneurship, 5(1), 5–21. Granstranda, Ove – Holgersson, Marcus (2019): Innovation ecosystems: A conceptual review and a new definition. Technovation, 90 Han, Jiying – Yin, Hongbiao (2016): Teacher motivation: Definition, research development and implications for teachers. Cogent Education. 3(1). Hofstede, Geert - Hofstede, Gert Jan - Minkov, Michael (2010). Cultures and Organizations: Software of the Mind, 3rd Edition. McGraw Hill Professional, New York. Koroleva, Diana – Khavenson, Tatiana (2017). Innovators from Within and from Without the Education System. in: A.M. Sidorkin, M.K. Warford (eds.), Reforms and Innovation in Education. Science, Technology and Innovation Studies. Springer International Publishing Oh, D. S., Phillips, F., Park, S., & Lee, E. (2016). Innovation ecosystems: A critical examination. Technovation, 54, 1-6. Ramos-Rodríguez, A. R., Martínez-Fierro, S., Medina-Garrido, J. A., & Ruiz-Navarro, J. (2015). Global entrepreneurship monitor versus panel study of entrepreneurial dynamics: comparing their intellectual structures. International Entrepreneurship and Management Journal, 11(3), 571-597. Schwartz Shalom H. (2007): Value orientations: measurement, antecedents and consequences across nations. In: Jowell, Roger - Roberts, Caroline – Fitzgerald, Rory and Eva, Gillian (eds) Measuring Attitudes Cross-Nationally. Lessons from the European Social Survey. London. Sage. pp. 169-204 Vincent-Lancrin, S., G. Jacotin, J. Urgel, S. Kar and C. González-Sancho (2017). Measuring Innovation in Education: A Journey to the Future. OECD Publishing, Paris. Wu, Sehwa - Lin, Carol Yeh-Yun (2019). Innovation and Entrepreneurship in an Educational Ecosystem. Springer, Singapore.