8

Enabling and Constraining Factors and the Need for System Change

As illustrated throughout this report, there are a number of ways in which an innovation can scale. The committee refers to the potential of an innovation to be “scaled” as its “scalability.” Chapter 4 introduced scale as multidimensional and described the varied approaches that could be used to scale and sustain an innovation. Chapter 5 went on to characterize the landscapes of innovation and implementation and the ways in which the configurations of actors, system-level decision makers, and financial resources can facilitate the implementation, scalability, and sustainability of innovations across settings and populations. In particular, the chapter describes the ways in which innovations are funded and how innovations can share new knowledge and resources and the implications these additional factors have for the scalability of innovations. Especially in the case of science, technology, engineering, and mathematics (STEM) innovations that aim to alter core beliefs or principles regarding STEM teaching and learning, consideration of key aspects of the system in which innovations are introduced and intended to thrive is critical.

Chapter 7 identified several factors—at the level of the innovation—that, when baked into the design, can support or hinder the scaling of a particular innovation. Those factors included: a “tight but loose” framework; alignment of goals, policies, and practices; capacity building and organizational support; ease of adoption; studying the program in a variety of settings with practitioners included during the process; and partnerships and networks. These are not the only factors that are needed nor are they a requirement for successful scaling efforts. The chapter concluded with a brief discussion of some of the challenges to scaling such as changing

policies and priorities, staff turnover, keeping materials updated, and monitoring implementation and outcomes at scale. Although the issues identified were at the level of the innovation, the implementation, scaling, and sustaining of innovations can be enabled or constrained by system-level factors.

This chapter extends the previous discussion by addressing these systemic issues. It begins with a discussion of many of these enabling and constraining factors and the insights for scaling and sustaining innovations that have been highlighted throughout the report. In particular, the section points to (a) the nature of the innovation, (b) resources that catalyze change, (c) professional learning and support for enactors and enablers, (d) leadership, (e) system capacity to support innovation, and (f) coherence. Building upon this discussion, the committee then considers the affordances of a durable system that allow for innovations to scale and sustain. That is, what opportunities can a durable system provide that allow for deep systemic change through the implementation of innovations and how can this change the “business as usual” model. The chapter concludes with a call for systems change.

ENABLING AND CONSTRAINING FACTORS

Policy structures, design features, resources, infrastructure, and leadership influence the STEM innovation implementation activities of various actors (Hopkins et al., 2013). Certain levers hold the potential to increase the agency of district and school leaders to more deeply implement STEM innovations. Here we discuss how levers enable—and sustain—actors’ work related to implementing STEM innovations. Policies and resources can reshape conditions to not only support individual actors, but promote deeper, systemic change. An array of catalysts enables learning so that STEM innovations become implemented in more equitable and sustainable ways across various contexts.

The Nature of the Innovation

The nature of the innovation matters for scalability. As described in Chapter 4, innovations that entail minor adjustments to enactors’ current practices are easier to implement and scale. In contrast, innovations that entail substantial change in enactors’ current beliefs about teaching and learning or students’ capabilities, knowledge, and/or current practices are much harder to implement, sustain, and scale. As elaborated throughout this report, the literature is replete with examples of how substantial changes to teaching and learning require ongoing professional learning as well as attention to and revision of the educational system in which the innovation is integrated (e.g., Cobb et al., 2018; Coburn, 2003; Cohen & Mehta, 2017; Elmore, 1996; McLaughlin & Mitra, 2001; Sarama & Clements, 2013).

Moreover, innovations that provide room for principled adaptation within specific contexts, with specific enactor and beneficiaries in mind, tend to be more scalable, as compared to innovations whose implementation is tightly prescribed, ad discussed in Chapter 4 (National Academies of Sciences, Engineering, and Medicine [NASEM], 2022a). Ample research on implementation points to the importance of local system leaders, educators, and family/community members adapting an innovation to reflect the needs, resources, and challenges of a particular community (Marshall & Khalifa, 2018; Zeichner, 2010).

Need for Resources

A number of resources are needed to support educational improvement in STEM and ensure equitable access and opportunities. Resources can be viewed as the components enabling—or fueling—activities and changes to systems and actors in the education field. Resources include such things as funding, research-based curricula, and tools, as well as time (Grubb, 2008, 2009; Kolbe, Steele, & White, 2020; Pareja Roblin, Schunn, & McKenney, 2018; Woulfin & Spitzer, 2023). These resources matter for the direction and extent of educational improvement efforts (Grubb, 2008; Grubb & Allen, 2011).

First, it remains important to fully fund STEM innovation efforts so that actors at different levels of the education system can respond to their implementation in substantive ways, given the inequitable funding structures across states, regions, and districts (see Chapters 2 and 3). This includes properly funding infrastructural elements aligned with an innovation, such as instructional materials, professional learning, and ongoing support for school and district leaders. Moreover, to promote more substantive forms of implementation, there is also a need to ensure adequate funding for improving working conditions to promote educator retention (NASEM, 2020). It appears educator stability functions as a resource with the potential to support STEM innovation efforts (McLaughlin & Mitra, 2001).

Second, providing teachers access to research-based curricula and the integration of technology into practice are steps toward changing teaching and learning, which is why it is important that decisions are based on educational research rather than policymakers’ initiatives (Niederhauser et al., 2018), as adoption of materials mediates access. External review systems (like EdReports) have been put in place to evaluate curricula; however, it is possible that this could create rigidity in curriculum expectations that could impact the scalability of new STEM innovations (see Chapter 5).¹ Aligning technology use with pedagogical goals encourages educators to critically evaluate the relevance and effectiveness of technologies in their teaching

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¹ However, it is not clear what the impact is of external reviews on the scaling and sustaining of Pre-K–12 STEM education innovations.

objectives. It can be a lot to ask of teachers who are now responsible for the orchestration of tools, participatory structures and routines, and supporting small groups and the whole class at appropriate times. Implementing feedback and evaluation mechanisms to gather input from teachers about their experiences with different technologies helps identify areas for improvement and informs future technology adoption decisions. Partnerships and plans based in research on how technology, teachers, peers, and technology tools can work synergistically are ways to help with successful teaching and learning using novel technologies (Puntambekar et al., 2021).

Third, time functions as a supportive condition for instructional change, permitting various actors to fully respond to the principles and practices of a STEM innovation (Kolb, Steele, & White, 2020; Sarama & Clements, 2013). Time for learning about and enacting STEM innovations is both structured and managed by educational leaders (Kraft & Novicoff, 2022; Woulfin & Spitzer, 2023). That is, district and school leaders make localized decisions on the allocation of time for STEM. Such decisions include guidelines for minutes per day for elementary math instruction, blocks of time for classes to work with a STEM specialist instructor, and number of professional learning sessions addressing science. Notably, the calendar and schedules of the school day, week, and year enable—or derail—STEM innovation efforts (Tyler et al., 2020). This can also include teachers’ time for working alongside families and researchers in the design and implementation of STEM education innovations. In sum, it is important to be patient about, and provide additional time for, change associated with the implementation and research of STEM innovation efforts.

Professional Learning and Support for Enactors and Enablers

Another critical factor in the scalability of an innovation regards the provision of high-quality professional learning and support for enactors. In cases where the innovation requires minimal changes to enactors’ current beliefs, knowledge, and/or practice, the professional learning needs are likely less, as compared to innovations that entail deep change (NASEM, 2020). For example, an initial workshop or session may suffice for new enactors, paired with occasional opportunities to share and troubleshoot challenges. On the other hand, when the innovation requires substantial changes to enactors’ beliefs, knowledge, and/or practice, the literature indicates the need for high-quality, sustained professional learning supports (NASEM, 2020), which can be especially true for increasing teachers’ knowledge and skills related to technology (Ertmer et al., 2012; Niederhauser et al., 2018). This might include providing professional learning opportunities that support enactors in deepening their expertise and experience with culturally relevant and sustaining practices (NASEM, 2020). Moreover, professional learning

opportunities are needed for both researchers and developers to ensure that considerations are made from the outset regarding the implementation contexts and the implications for adaptation and scaling.

Specific to innovations designed to alter instruction, it is important that the professional learning focuses on making sense of the specific materials, as well as underlying principles and assumptions (e.g., about teaching and learning, about students’ capabilities, about the discipline; NASEM, 2020). Further, opportunities for the enactors to participate in the professional learning with their colleagues, and to discuss how they might adapt the materials and/or approach them in ways that are specific to their contexts, students, and communities, is crucial (NASEM, 2020) and helps to ensure that enactors are adapting experiences in meaningful ways for all learners.

Although professional learning opportunities can function as a lever for substantive change, it is rarely optimized inside current systems. It may neglect evidence-based principles of high-quality professional learning, including the importance of content-specific, engaging, collective, and extended duration learning opportunities (Garet et al., 2001; Woulfin, Stevenson, & Lord, 2023). Moreover, there are flaws in the ecosystem for professional learning. Specifically, district and school leaders face challenges for organizing release time, compensation, and space for high-quality, aligned professional learning on STEM innovations for educators, as well as pursuing such opportunities for themselves. And educators, regardless of their role in the school system, encounter challenges for implementing the principles and practices addressed during professional learning in their particular school and/or classroom contexts (MacLeod, 2020).

While the provision of professional learning across educator roles is often essential for scaling innovations, it is important to simultaneously consider the design, implementation, and scale of professional learning itself. In other words, just as it is important to encourage principled adaptation of an innovation for a given context and community, it is often necessary to also consider how a professional learning design may need to be adapted for a new context or community, with specific resources and strengths, as well as challenges. A key challenge that often emerges is developing professional learning facilitators who have the necessary expertise and resources to design and adapt professional learning specific to particular contexts and communities. Indeed, building and sustaining a cadre of professional learning facilitators is a critical aspect of building systemic capacity to support innovation (see below). Relatedly, many designers of innovations—including academic researchers—would benefit from collaborative opportunities to deepen their knowledge of educational systems and settings. Designers who have a deeper understanding of schools and classrooms are better able to prepare for the transition of an innovation from

its initial implementation to robust use across new settings and to provide appropriate guidance and responsive support.

Organizational learning also matters for the course and depth of STEM innovation implementation. In particular, the ways that districts, as organizations, adapt in response to evidence on STEM outcomes as well as barriers for change, can be treated as organizational learning. Moreover, when districts apply a continuous improvement approach, rather than a compliance orientation, this enables educators to engage more meaningfully with STEM innovations and work in creative ways to advance implementation efforts, bridging the gap between research and practice (Schneider, 2014). For example, district leaders might pilot new mathematics high-quality instructional materials in a small set of schools, collect evidence on how educators and students respond, and then design more effective systems to enable district-wide curriculum implementation in subsequent years. This incremental approach provides time and space for individual and organizational learning, aiding in ensuring the innovation contributes to substantive—and sustainable—change.

Organizational and adult professional learning opportunities are levers with the potential to boost actors’ agency for implementing STEM innovations. Capacity-building instruments play key roles ensuring enactors and enablers—teachers, coaches, and district and school administrators—to understand the rationale for an innovation, key components of the innovation, and how to align their work to the innovation (Coburn, 2001; McDonnell & Elmore, 1987; Woulfin & Gabriel, 2022). In turn, teachers and leaders integrate ideas into their planning and practices for not only implementing the innovation but to create conditions and guidance for others who are involved in implementation.

Leadership

Leadership also functions as a lever catalyzing the implementation of STEM innovations. Leaders positioned at different levels and in various organizations can take steps to select priorities and align initiatives that, in turn, increase the likelihood that teachers (as well as other leaders) take active steps matching the principles and practices of a particular STEM innovation. They play roles in framing innovations (Coburn, 2006; Woulfin, Donaldson, & Gonzales, 2016). The strategic communication about problems as well as solutions associated with STEM teaching and learning can motivate others to shift their beliefs and practices related to STEM (Coburn, 2006; McLaughlin & Mitra, 2017; Sarama & Clements, 2013; Woulfin, 2015). This communication matters for delineating how and why teachers and leaders adopt aspects of a STEM innovation. For example, a district administrator’s framing of how teachers use new math high-quality instructional materials can promote

changes aligned with the new curriculum. And, if an intermediary organization leader sets up Framework-aligned science standards in resonant ways, district and school leaders could be more likely to allocate funding and time necessary for promoting and enacting science instruction.

Leadership activities also serve to promote the agency of other actors involved in implementing STEM innovations (Elmore, 2016). In a sense, leaders who are aware of how learning happens at all levels in STEM education can catalyze the agency of others in the STEM arena. In particular, perceptive leaders in different roles at different levels can create conditions enabling teachers and other system and school leaders to interpret, learn from, and then respond to messages about STEM innovations in substantive ways (Elfers & Stritikus, 2014; Woulfin & Gabriel, 2020).

System Capacity to Support Innovation

Enactors implement innovations in complex contexts, which often entails the management of multiple and competing demands. Providing high-quality professional learning supports for those charged with enacting the innovation is necessary but not sufficient for supporting sustainable implementation at some scale, especially, again, if the innovation entails substantial change to the enactors’ current beliefs, knowledge, and/or practice (e.g., Bryk et al., 2015; Cobb et al., 2018; Coburn, 2003; Elmore, 1996, 2016; NASEM, 2020). Instead, if innovations are to take hold, research provides ample evidence that aspects of the educational system must be supportive of—not hindrances to—educators’ implementation of the innovation (Coburn, 2003; Elmore, 1996; Fullan, 2016; Johnson, 2019). One aspect is the coherence between the focus of the innovation, and other instructional reform initiatives and materials that educators are expected to simultaneously implement (Desimone et al., 2002; Garet et al., 2001) Teachers, in particular, are often expected to learn about and implement new forms of practice, or new materials, without consideration of how these fit with existing practices and materials, and what might be best to set aside or forgo (Schneider, 2014).

The sustainability of an innovation is easily threatened by turnover in the enactors. Thus, whether the innovation entails a minor or substantial change to “business as usual,” it is critical to build in structured opportunities to “onboard” new enactors (McLaughlin & Mitra, 2001). One strategy is to identify and grow a cadre of experienced educators who are provided with resources (e.g., time, compensation) to create ongoing opportunities for new members to learn about the innovation and participate in research activities, as observed in the Tennessee Math Coaching Project (see Box 4-2) and other professional learning community examples discussed in Chapter 4. For example, Yoon and colleagues (2020a) have discussed the importance

of designing for “social capital” in teacher professional learning. They describe social capital as “building teacher networks, sharing knowledge and resources, and providing access to expertise” (p. 253). The shift from human capital—that is developing knowledge and skills at the individual level—to social capital emphasizes being connected and a part of a social community in which teachers have access to expertise from peers, and a community in which teachers are “scaffolded to develop social ties, build trust by sharing experiences and resources, participate in collective sensemaking on practice and access peer and expert support through multiple channels” (Yoon et al., 2020b, p. 689). District leaders, principals, and coaches can similarly benefit from participating in peer networks across schools.

Fundamental to this type of work is understanding that schools implement reforms and innovations through localized social processes: members of a school are part of a social system that can gain access to each other’s expertise and may respond to social pressures to implement innovations, even if they run counter to their own perceptions of value of the innovation (Frank, Zhao, & Borman, 2004). Schools and teachers within them may develop a shared understanding of their instructional vision (Munter & Wilhelm, 2020), and positive change in instructional practice can be achieved through interactions with close colleagues (Sun et al., 2014), given their expertise (Wilhelm et al., 2016).

A related issue concerns the workplace culture, including the extent to which educators are trusted and encouraged to make sense of, experiment with, and adapt new materials and practices (e.g., Bryk et al., 2010; Johnson, 2019; NASEM, 2020). School leaders play a critical role in establishing and maintaining a school culture that is supportive of innovations in teaching and learning (e.g., Bryk et al., 2015; Grissom, Egalite, & Lindsay, 2021; Kazemi, Resnick, & Gibbons, 2022). Just as school leadership matters, so does district leadership (e.g., Cobb et al., 2018; Honig, 2012). One issue regards the nature of district leaders’ accountability relations with school leaders, and whether district expectations are coherent with the focus of the innovation. For example, if principal supervisors primarily press principals to increase student achievement on a limited assessment of learning, absent attention to teaching quality or students’ wellbeing, those principals are, in turn, likely to press teachers to focus narrowly on student achievement. On the other hand, if principal supervisors not only expect but encourage school leaders to organize opportunities for teachers to develop more ambitious ways of engaging students in STEM, principals are likely to act accordingly (Honig, 2012; Jackson et al., 2018; Kazemi et al., 2024). These sets of accountability relations (between district leaders and school leaders; and school leaders and teachers) shape the workplace culture and the extent to which the enactors and enablers view experimenting with innovations in service of expansive views of teaching and learning as both expected and desirable.

Since the “implementation of a complex process in the context of a complex system necessitates a rich set of data to facilitate meaningful action,” districts have begun to utilize various models of data collection to support planning and measuring implementation of one or more innovations in context beyond simply tracking end-of-implementation student outcomes (Olson et al., 2020, p. 56). One such model, the Concerns Based Adoption Model (CBAM), seeks to measure quality of, degree of, and reactions to the implementation of a given innovation both personally for individual enactors as well as for the educational system as a whole. Utilizing robust data collection models designed to capture the changes systems make to support implementation of innovations can give insight into the enabling conditions for successful implementation across contexts, which can ultimately be used to shape future policy in supporting strong STEM learning.

Coherence

The coherence of STEM innovations with other educational improvement efforts influences the degree of organizational and individual change. By aligning with—or building upon—other improvement strategies and reducing the too-muchness of educational reform, coherence can catalyze the implementation of STEM innovations (Bryk et al., 2015; Honig & Hatch, 2004). Here, leaders play key roles in intentionally aligning and then strategically connecting STEM innovations with other improvement efforts. For instance, state administrators can connect mathematics high-quality instructional materials with school improvement models. And principals and coaches can meld Framework-aligned science standards learning with professional learning community routines so that teachers have opportunities to collaborate on—and learn together about—this approach to science instruction. As such, system leaders need opportunities to learn about methods for assessing and revising system-level policies and practices that may be impeding implementation of innovations, which might include developing orientations and enacting principles aimed at fostering experimentation and learning “along the way” as innovations are implemented (Bryk et al., 2015).

Relatedly, there are potential benefits for refining accountability policies, including high stakes testing, to enable the deeper implementation of STEM innovations. By decreasing the pressures of accountability reforms, leaders and teachers could devote greater attention toward STEM innovations. Inside schools, this might involve teachers replacing mathematics and English language arts test preparation activities with Framework-aligned instruction that interweaves science, math, and literacy (NASEM, 2022b). Notably, as compared to most STEM innovations, mathematics is more proximal to accountability policies. Based upon this, educators encounter

pressure to teach and assess mathematics in particular ways—with consequences for schools and students.

AFFORDANCES OF RESILIENT SYSTEMS

As articulated in earlier chapters, factors that affect scaling of innovations include the need to have a strong, core program with ample room for adaptations for different contexts and learners. In order for innovations to have the potential for scale and sustainability, the innovation and implementation landscapes must be bridged. And for that to happen, there needs to be a system in place that can make it happen. Resilient systems exhibit alignment of goals, policies, and practices.

Some individual innovations have accomplished scaling by growing their own system. That is, these innovations that have achieved some degree of scaling and/or sustainability have invariably done so through creating and leveraging partnerships (see Chapter 5). There have even been some historical attempts through federally funded programs to build resilient systems with durable, sustained capacity and infrastructure to support multiple innovations or a single innovation to scale over time (see Chapter 3).

Research suggests that the design of a resilient, stable system is one that is organized around a “backbone” entity that gathers together the various and varied individuals and organizations that might coalesce around STEM education values, ideas, and/or actions (National Research Council [NRC], 2015). In practice, the backbone may be a government created entity, a grass roots community group, an institution of higher education, a school district, a business, a museum, a foundation, a professional organization, or even an entity created for the sole purpose of providing structural support. Resilient, stable systems also take into account the geography, funding sources, policy, and/or common/cultural identity. Place-based leaders are able to make evidence-informed decisions about local needs and the potential solutions to address those needs given a constellation of factors that matter, such as policy, values, resources, human capital, and facilities aligned with a vision. In other words, there is structure and leadership to enable and encourage the work of tending to the system and making decisions about the implementation needs of an innovation that balances broad understanding of STEM education with deep understanding of localized context.

Figure 8-1 represents the system of actors who engage with an innovation or enable it to take shape. Unlike the system of actors as described in Chapter 1, which positions the learner as the center, or the system of actors as described in Chapter 2, which principally focuses on the formal K–12 education system, Figure 8-1 puts the innovation at the center. From the innovation are the expanding spheres of influence from the learner within the classroom context to the community and formal K–12 education system

to local agencies and STEM focused institutions to national organizations and media all embedded within place. Place serves to acknowledge the histories, cultural practices, ideologies, values, politics, and ethics that are part of both the local context within which an innovation is implemented as well as how it has influenced the broader educational system. Across the expanding spheres, the actors can serve as enablers or enactors, with their positionality changing throughout the life course of an innovation.

Cutting across each of these levels of influence are the enabling and constraining factors highlighted throughout this report. These factors include vision, values, policy, economic capital, human capital, social capital, and physical resources. Starting with the top center wedges (Vision and Values), the overall issue is one of “fit”—enablers and enactors can ask “Does the innovation fit with who we are and where we are going in STEM?” If the answers are, “Yes,” then the next issue would be “Can we implement the innovation?” This is where the Policy and Physical Resource wedges come into play as both facilitators and barriers. Again, if the answers to the questions are, “Yes,” then it is feasible to consider the scaling and sustaining of the innovation.

For any actor within the system for a given innovation, they can begin to ask themselves questions to help guide implementation of an innovation with considerations related to scaling and sustaining (see Table 8-1). Across all factors and questions, it is important to consider who gets to make the decisions, what influence those decision makers have, and over what time period (see Chapter 2).

TABLE 8-1 Considerations Related to Scaling and Sustaining Innovations

Whereas facilitating the scaling and sustainability of innovations requires a stable, resilient system, systems are vulnerable to disruptions in leadership and funding. These disruptions can bring about an abrupt end to their capacity to act. Strong partnerships among school districts and historically stable organizations such as government agencies, institutions of higher education, trade associations, and business/industry can help safeguard against such disruptions (Krainer et al., 2019; Maas et al., 2019;

Young et al., 2016) and work to move toward a more durable system that can continuously improve itself through cycles of reflection, innovation, implementation, and improvement (Lowrie, Leonard, & Fitzgerald, 2018; Sabelli & Harris, 2015). For this aspirational goal, there is a need for robust systems change.

NEED FOR SYSTEM CHANGE

Scaling is not just about scaling a particular innovation, but rather seen as part of a larger effort to improve the education system as a whole and make lasting changes to organizations and policies that allow for a system that better supports continuous improvement in part through the implementation and sustaining of innovations. Innovation, while necessary to address immediate problems of practice, is insufficient in addressing systemic challenges in STEM education. What is needed is a deeper understanding of scaling across various levels of the system. Stronger systemic infrastructure would enable designers to work with enablers and enactors to set up a system where the essential principles of an innovation can be sustained. This could help to shift the focus from simply putting an innovation into practice to the work of addressing a problem of practice by utilizing an appropriate innovation. Moreover, organizations and systems could then take the lead (Sabelli & Harris, 2015) to ensure that there are policies, practices, and resources available for systems to identify problems of practice so that the system can identify, create, and implement innovations to address those problems, learning along the way.

Schools, districts, and states can have trouble successfully scaling innovations when there is a lack of attention to each classroom’s varied context across all levels, including the political context, teacher support from leadership, quality instructional materials, teacher professional learning support, and student learning norms, among other micro- and macro-contextual factors. Each actor is not simply implementing “best practices” but learning to become a different kind of educator (Elmore, 2016). What’s more, these leveled contexts need to be considered as interdependent. Maass and colleagues (2019) note that improvement must also take place across interested parties, especially outside of the classroom, and can be addressed through aligning the aims of various partners.

In a decentralized national public education system of nearly 13,000 school districts, large-scale “systems change” can at first seem to be a vague concept with little in the way of a starting point or central locus of power from which change emanates, even within the confines of making the scaling of innovations more practical and possible. This vagueness is in part because, as detailed in Chapter 2, the responsibility to provide public education lies with the states and, across states, most relegate power over school governance to local school

boards. One thing that can help to concretize or organize change is data. Central to resilient learning systems are both access to useful data about student learning, instructional practice, and their enabling conditions, as well as the means to utilize these data effectively for organizational change (Peurach et al., 2022).

This report suggests that “systems change” might mean empowering state and local education agencies to build responsive systems that can implement, adapt, and innovate based on local context and the needs of current students to incorporate innovations over time with families and communities as key partners and sources of expertise in the work. Currently, there is a need to ensure that federal agencies are positioned to provide incentives to states and districts to develop policies, practices, and resources that allow for innovation and continuous improvement through the use of locally-collected data that is specific to particular contexts. Developing robust research and development infrastructure within state and local education agencies will require (a) a restructuring of the recipients and purpose of educational research grants, (b) evolving the relationship between educational researchers and educational administrators, (c) shifting research questions from “What works?” to “What is likely to work in this context?” to “What are the infrastructure supports needed for scaling?”, and (d) reconfiguring the relationship between local, state, and federal education agencies and the communities they are a part of.

A focus on improvement in this way could support continuous learning and innovation that is grounded firmly in problems of educational practice. It would move away from a system that is stronger in support for evaluating program impact and weaker in supporting continuous improvement (Peurach, 2016). Building system capacity in this way could harness the potential for nimble systems at the federal, state, and local levels that can respond and innovate using evidence based on the local context and student needs with the aspirational goal of ensuring equitable Pre-K–12 STEM learning opportunities for all students.

SUMMARY

The complexity of educational environments results in both embedded challenges as well as opportunities for successfully scaling and sustaining Pre-K–12 STEM education innovations. An array of catalysts—nature of the innovation, resources, professional learning, leadership, system capacity, and coherence—enable the implementation of STEM innovations to scale in more equitable and sustainable ways across various contexts. Policies and resources can reshape conditions to not only support individual actors, but also promote deeper, systemic change. Leaders can create conditions enabling teachers and system and school leaders to interpret, learn from, and then respond to messages about STEM innovations in substantive ways. The coherence of

STEM innovations with other educational improvement efforts influences the degree of organizational and individual change. It is also crucial to consider the need for system change and provide opportunities to not only support the building of individual and organizational capacity to scale and sustain STEM education innovations, but also to seek to continuously improve.

REFERENCES