Improving educational systems is a socially and technically complex process, involving many diverse stakeholders and complex cultural patterns of change and stasis. Educational research, in this context, has broadly been critiqued in terms of how research insights are hardly translated into real-world practice. Educational design research (McKenney & Reeves 2018, Mintrop 2020) can be described as one response to these critiques. Within this expansive tradition, concepts such as Networked Improvement Communities (NICs, Bryk et al. 2015, LeMahieu et. al 2017), and Researcher-Practitioner Partnerships (RPPs, Penuel 2019) have emerged to suggest the need for networked co-design of innovations with school stakeholders as a driver of effective implementation, evaluation, and improvement. Hence, we are committed to engage a diversity of stakeholders, including scientists and philosophers from across the educational and life sciences, teachers across disciplines, teacher educators, university and secondary students, both as participants and as co-designers of our educational design concept. 

The work of OpenEvo explicitly moves into an uncharted landscape in terms of its focus on human behavior as an interdiscplinary theme in curricula and teaching practice. The current education system most likely does not provide the capacities, tools, freedom, and/or competencies to fully implement our vision on a system-wide scale. 

Therefore, a central aim of educational systems improvement must be on creating infrastructure (i.e. infrastructuring; Penuel 2019), or creating the tools, resources, processes, institutions, technologies, knowledge, attidutes, and skills to drive effective implementation, evaluation, and improvement of innovations at the required scale. In this context, the extensive conceptual clarification, education design concept development, diversity of teaching resources and open source publications, as well as the digital design-based research infrastructure that have emerged within the development of OpenEvo, all represent a central commitment toward capacity building through infrastructuring activities. 

Like the need for creating infrastructure for networked co-design, the change processes envisionend by OpenEvo also need time, because changing education systems takes time.   

As Richard McElreath (2018), director of the Department of Human Behavior, Ecology and Culture at the Max Planck Institute for Evolutionary Anthropology,  describes:

“Human societies display long-form adaptation. Humans adapt behaviorally, and human behavior requires years to acquire and generations to develop. Long-form behavioral adaptations explain our species’ extraordinary diversity and its ecological success. 

The study of long-form adaptation will benefit from long-form research that is both longitudinal and comparative, allowing it to inform theories of human evolution and the dynamics of human societies.“  

McElreath is framing this concept of long-form research in the context of the foundational scientific aims of his department of human behavioral ecology, where he and his colleagues study societies around the world and their societial and cultural eolutionary change processes, e.g. when hunter-gatherer societies experience increasing market integration, ecological sustainability issues, or the establishment of schools. A commitment to the establishment of long-term field sites is a prerequisite for studying such long-form change processes.

We apply the same long-form view to initiating and studying changes to education systems: OpenEvo is not a project with an end date and we are interested in what education systems might (be able to) look like and in what way our innovations spread twenty years in the future and what characterizes this process. The long-form view of OpenEvo is also required for our needed focus on the curriculum level. Change on the level of state and national standards and curricula can be understood as a cultural evolutionary process that is influenced by many factors, including the novel advances in computational technologies and artificial intelligence. Our project Computational Curriculum Studies seeks to take advantage of the rise of machine-readable curricula and use computational methods to better characterize in what way our educational design concept can relate to or even reshape current and future curriculum standards.