Leveraging Multiple Theories of Change to Promote Reform: An Examination of the AAU STEM Initiative

Abstract

An emerging body of literature suggests that systemic efforts to change institutions are enhanced when change actors utilize multiple approaches or strategies to change that capitalize on their individual, team, or organizational assets. Given that little research in higher education has examined the ways leaders deploy multiple strategies in service of change, this study sought to fill this gap in the literature by studying an effort that deployed several strategies or theories of change. Building on emerging literature about the value of multiple theories of change, the study followed the Association of American Universities (AAU) science, technology, engineering, and mathematics (STEM) Initiative, which aimed to improve undergraduate teaching in STEM at research universities and utilized multiple theories to inform a complex strategy. This research shows the value of using multiple theories of change and also provides guidance on the best way to harness or use multiple change approaches.

Keywords

higher education qualitative research education reform

A growing body of literature suggests that systemic efforts to change higher education institutions are enhanced when change actors utilize multiple theories of change that capitalize on their individual, team, or organizational assets (Bensimon, 1989; Boyce, 2003; Kezar, 2013; Laursen, Austin, Soto, & Martinez, 2015; Sporn, 1999). Theories of change provide different ways of thinking about “why change occurs, how it occurs, what are the outcomes of change, types of change . . . [and] strategies” for making change (Kezar, 2013, p. 22).¹ Perhaps, the most well-known framework that explains the use of multiple theories of change is Bolman and Deal’s leadership frames, which examine structural, political, human resource, and symbolic strategies as ways to lead organizations and guide change processes (Bolman & Deal, 2007; Kezar, 2005). For example, Laursen et al. (2015) used Bolman and Deal’s frames to understand how leaders in ADVANCE-funded initiatives in higher education made changes to support women faculty in science, technology, engineering, and mathematics (STEM) disciplines and were more successful progressing and institutionalizing efforts using multiple frames. While multiframe leadership is one way to examine the multifaceted aspects of change processes, Bolman and Deal’s four frames represent some but not all of the strategies associated with creating change in higher education. Scholars such as Kezar (2013) suggest that there are actually six main theories of change that can be deployed; these theories include scientific management (similar to Bolman and Deal’s structural), evolutionary, cultural (similar to Bolman and Deal’s symbolic), social cognition, political (similar to Bolman and Deal’s political), and institutional theories of change.

More recently, building on Kezar’s (2013) work, Corbo, Reinholz, Dancy, Deetz, and Finkelstein (2016) used multiple theories of change to scale up the use of evidence-based teaching practices across several departments involved in an undergraduate science education initiative. Departmental action teams deployed scientific management approaches by securing course buyouts and service credit for participants. Simultaneously, they utilized data from their institutional research offices and conducted qualitative interviews to better understand faculty mind-sets, using social cognition theories of change. They created a shared vision for the direction of the course redesign, adopting cultural approaches to change. Using political theories, they interviewed faculty to get buy in for departmental action teams and had conversations with the chair and executive committee to garner their support for the concepts before moving forward. They drew on institutional theory (IT) to think about ways to obtain administrator buy in and to leverage prestige by garnering funding from prestigious sources to gain the attention of administrators who would prioritize their efforts. They also synergized strategies across three levels—faculty, department, and the administration—using a systems approach to change. While there has been conceptual support and advocacy for more complex approaches to change, this study is part of a very limited empirical literature about how multiple theories can be deployed in change processes (Kezar, 2013; Sypawka, 2008). In the few empirical studies conducted of using multiple change theories, the focus has been on documenting how using more theories enhances the efficacy of the change effort (Corbo et al., 2016; Laursen et al., 2015).

Given that little research has examined the ways leaders deploy multiple theories in service of change, this study sought to fill this gap in the literature by studying an effort that deployed several theories of change. Building on this emerging literature about the value of multiple theories of change, the study followed the Association of American Universities (AAU) STEM Initiative, which aimed to improve undergraduate teaching in STEM at research universities and utilized multiple theories to inform a complex strategy, filling this empirical gap. Our research questions focused on exploring more deeply and in a more nuanced way the nature of using multiple theories by exploring the dynamics in bringing multiple theories together. We examined this issue with the following research questions as a guide:

Research Question 1: How does a change initiative deploy multiple theories of change?

Research Question 2: What does the use of multiple theories look like?

Research Question 3: Are there any challenges in deploying multiple theories?

AAU STEM Initiative

Before reviewing the literature, it is important to set the context for the article by describing the AAU STEM Initiative. In 2011, the AAU launched a 5-year initiative in partnership with its member institutions to improve undergraduate teaching and learning in STEM fields to achieve scale in the use of evidence-based teaching practices. The overall objective of AAU’s Undergraduate STEM Education Initiative was to influence the culture of STEM departments at AAU universities so that faculty are encouraged and supported to use teaching practices proven by research to be more effective in engaging students in STEM education and in helping students learn. The goals of the Initiative were to

develop an effective analytical framework for assessing and improving the quality of STEM teaching and learning;

support project sites at a subset of AAU member institutions to implement the framework;

explore mechanisms that institutions and departments can use to train, recognize, and reward faculty members who want to improve the quality of their STEM teaching;

work with federal research agencies to develop mechanisms for recognizing, rewarding, and promoting efforts to improve undergraduate learning; and

develop effective means for sharing information about promising and effective undergraduate STEM education programs, approaches, methods, and pedagogies.

AAU developed a Framework for Systemic Change in Undergraduate STEM Teaching and Learning (“Framework”; see the appendix) to guide institutional commitment to facilitate change in undergraduate STEM education. The Framework contained three different areas that AAU deemed necessary for creating sustainable change: pedagogy, scaffolding, and cultural change. Each of these three areas also contains multiple suggested reforms. For example, “Pedagogy” includes such reforms as assessments and educational practices; “Scaffolding” includes structural issues, such as facilities, data, and technology, and “Cultural Change” includes leadership commitment, aligning incentives with teaching excellence, and establishing strong measures of teaching excellence. The organization selected eight member campuses to serve as project sites. Over 3 years, each of the eight project sites implemented a major undergraduate STEM education project that incorporates key elements of the Framework. The project embedded learning from peers by having the eight project sites present to each other on findings from their work. The AAU STEM Initiative aimed to scale practices in several ways—it assumed a systems approach in that the entire campus (through the framework architecture) needs to be engaged. It also assumed that multiple players in the higher education system would need to align priorities to scale new practices. AAU thus worked with disciplinary societies, national organizations such as the National Academies of Science, the National Science Foundation (NSF), the Howard Hughes Medical Institute (HHMI), and other national groups that influence scientists and the teaching of science to build buy in and support for the project. In the next section, we explore in more detail the various theories of change that influenced the AAU STEM Initiative.

Literature Review/Theoretical Framework

This initiative was predicated on the literature and conceptual support that explicit attention to theories of change can drive more effective change processes, and that deploying multiple theories of change can be exponentially beneficial, particularly in scaling change. We review AAU’s strategies noted in their change proposal and design. Four primary theories of change were mentioned in AAU’s proposal: systems theory, organizational learning, network theory, and IT. These theories all informed AAU’s strategy and we studied each for its efficacy as part of the project. The following reviews of the literature on each of these theories of change are not meant to be exhaustive, but rather a summary of some of the key concepts needed to understand the basic theories to understand the way AAU deployed these ideas in its change initiative (for more exhaustive reviews see Kezar, 2005, 2013).

Systems Theory

Systems theory examines the interrelationship of various subsystems within organizations and how organizations are interconnected (Birnbaum, 1988). In systems theory, change is most likely to be achieved when all aspects of the system are adjusted in coordinated ways (Kezar, 2013). For example, to change or affect the use of evidence-based teaching practices, professional development alone will not work as classroom practices are also tied to incentive systems, departmental norms, facilities, campus priorities, and student expectations (Austin, 2011; Kezar, 2013).

In addition, AAU adopted an open systems theory of change that explored beyond the impact of the internal college system to other actors and players that affect the campus. Open systems theory emphasizes how change processes are affected by external organizations, groups, and forces (Gumport & Sporn, 1999; Hearn, 1996). Various studies of change have adopted a systems approach, but fewer studies in higher education adopt an open systems theory, particularly as it applies to areas such as teaching and learning, which are more often considered the domain of academic professionals (Kezar, 2013). Open systems theory tends to be applied to issues such as cost containment, Title IX, increasing regulation, and even diversity; these are areas where higher education seems less open to internal levers for change and in need of external pressures or force (Kezar, 2013; Zemsky, 2013). Yet, AAU predicted that in research universities, various external groups shape norms around teaching, including disciplinary societies, national groups and agencies such as the NSF, or disciplinary accreditors (particularly in groups such as engineering) that have been active in shaping teaching.

As noted above, the AAU developed its Framework to guide institutional commitment to facilitate change in undergraduate STEM education. The Framework uses systems theory in describing linked parts of the campuses that need attention to ensure sustainable change, including the type of leadership commitment and resources needed for change, infrastructure in terms of professional development, changes to promotion and tenure processes, alignment of reward structures with teaching, and new facilities, classrooms and laboratories, and development of pedagogical, curricular, and learning goals and objectives. In addition, the open systems approach is evident in the objectives for the initiative that include and operate at multiple levels: (a) project demonstration sites, (b) the AAU network made up of the entire population of AAU membership institutions, and (c) the broader higher education system with national organizations and groups such as disciplinary societies, accreditors, and national reform groups.

Organizational Learning

Another prominent theory of change driving the initiative was organizational learning (Argyris & Schön, 1996). Organizational learning is typically associated with a branch of literature on change that examines the role of cognition and mental processes within change. Organizational learning is the study of whether, how, and under what conditions organizations can be said to have learned (Boyce, 2003; Kezar, 2005). Within this stream of research, organizations are seen to change when individuals learn and collectively reorient the way that they approach conducting work, in this case teaching undergraduate STEM courses (Huber, 1991). This is often seen as an approach to scaling change because of its emphasis on mind-sets that undergird work, which can promote lasting change across a wide swath of the organization (Kezar, 2013).

Organizational learning scholars tend to look at information and data available within organizations; the way that information is shared; facilitative mechanisms for learning, such as teams, networks, or data dashboards; sharing of best practices; and, more generally, looking at the ways that individuals within organizations examine or understand concepts (Kezar, 2005). Studies of organizational learning focus on issues, such as acquiring information and ideas, interpreting data, turning information to knowledge, knowledge recall and memory, and ways to sustain learning by embedding it into the organizational structures (often termed knowledge management; Argyris & Schön, 1996; Garvin, 1993; Huber, 1991). Research from multiple disciplines demonstrates the infrastructure that needs to be in place to support organizational learning (improved data systems, knowledge management systems), best practices for fostering learning (better formats for displaying information to different stakeholders, team practices that help interpret information to create knowledge), and the leadership and culture (creating a culture of trust, leaders supporting risk-taking and innovation) required to ensure that organizational learning occurs (Argyris & Schön, 1996; Kezar, 2005).

The AAU promoted organizational learning in a variety of ways, including having participants adopt practices from each other’s campuses; spreading learning across the network through presentations, webinars, and meetings; and pitching the eight demonstration sites as laboratories to try out new practices that they hoped would inform and be adopted by other campuses. In examining the five main objectives of the AAU initiative, four of them relate to aspects of learning, including developing means for information sharing about best practices in STEM reform, working with institutions and departments to train and professionally develop faculty, supporting project sites to implement the framework, and the development of the framework itself, which could be seen as a learning tool. The Initiative was also very informed by the collection of data. Surveys were conducted to inform each campus of how widespread use of evidence-based teaching practices was on their campus. Another major goal of the project was the development of measures that could help institutions assess their progress and learn how to improve implementation using data to inform their actions. And a major part of the Initiative that emerged over time was the use of data analytics to follow students and better understand their patterns of performance to inform improvements in curriculum. Most of these practices could be characterized as actions that fit into organizational learning.

Network Theory

Another important theory for scaling change is the utilization of networks and diffusion theories of change (Rogers, 2003). Many empirical studies demonstrate that changes in behaviors and mind-sets have been a result of networked diffusion models in which innovators utilized new practices and had some success, and then others became aware of the practices and utilized them as well (Rogers, 2003; Tenkasi & Chesmore, 2003). Networks create the informational channels for change ideas to flow, for a community to innovate in safe spaces, and intellectual capital and knowledge about how to implement change (Tsai, 2000). Webs of relationships are often the chief determinant of how well and quickly change efforts take hold, diffuse, and are sustained (Daly, 2010).

Researchers have identified several key ways that social networks lead to change. First, social networks offer a set of mechanisms that enable change—through communication systems, knowledge transfer, alteration of schema or mind-set, shaping of attitudes, increasing of problem solving, and accountability (Ahuja, 2000; Borgatti & Foster, 2003; Kraatz, 1998; McGrath & Krackhardt, 2003; Szulanski, 1996; Wasserman & Faust, 1994). Second, two outcomes of social networks have been related to change—learning and social capital (Borgatti & Foster, 2003; Burt, 2000; Kilduff & Tsai, 2003; Tenkasi & Chesmore, 2003). Many researchers have found a strong linkage between learning and social networks, and learning has been strongly linked to changes in behavior (Tenkasi & Chesmore, 2003). Networks also provide social capital that facilitates the change process (Burt, 2000), varying from knowledge about how the organization works, to influence within the organization, to an organization’s finances. Third, change often involves risk-taking that can be less problematic if it is done collectively rather than individually (Valente, 1995). If one knows many of their peers are going to engage in the same behavior, then one is more likely to also engage in this behavior (Rogers, 2003; Valente, 1995).

The AAU STEM Initiative utilized networks to build relationships, connect various aspects of the system they knew were necessary for change, disseminate information, facilitate learning, and eventually scale change. The AAU STEM Initiative was specifically designed as an effort that would connect eight project demonstration sites within a network, and these sites would meet with the larger set of AAU institutions to create a broader network to help foster change. Indeed, this broader set of institutions was named the AAU STEM Network. Over time, the AAU also created several subnetworks of department chairs, faculty within various STEM disciplines, and directors of centers for teaching and learning, for example. They also networked with other groups, such as the HHMI and the NSF and other networks such as the Cottrell Scholars, Bayview Alliance, and Center for the Integration of Research, Teaching and Learning (CIRTL).

IT

IT describes the impact of broader forces and organizations outside college campuses themselves on change, including accreditation, disciplinary societies, state policy makers, and national agencies such as the NSF—also known as the organizational field (Powell & DiMaggio, 1991). Examples include national associations pushing for a more similar general education curriculum, accreditors pushing for assessment of student learning outcomes, or presidents altering their mission to be more research-oriented in pursuit of prestige to be more like elite institutions (Boyce, 2003). In addition to the organizational field, the societal field also influences change on campuses. The societal field encompasses pressures that are further afield (such as economic changes or political regulations) yet still shape campuses and members of organizational fields such as accreditors that have closer contact with campuses and often help deliver and temper societal forces. Both societal and organizational fields affect campuses, but in varying degrees and depending on the power of the fields in any given time period. The power of fields is dynamic and changes over time.

IT leverages influence as a way to motivate change. This phenomenon often plays out through isomorphism, where institutions mimic each other; in particular, less prestigious institutions often emulate more prestigious ones (W. R. Scott, 2008; Taylor & Morphew, 2010). But influence can take many forms, such as more normative approaches where certain values or approaches are legitimized (W. R. Scott, 2008). In these normative approaches, shaping norms, language, discourse, and logics that underlie organizations are often a focus of influence. Therefore, change is a result of a new schema or set of norms, embedded in language, transferred through discourse, and entrenched in institutional structures over time through a system of institutional logics—a driving rationale for how things should operate (J. W. Meyer & Rowan, 1977). Legitimacy is also critical in that only certain players in the field (generally the most prestigious ones) are seen as being able to drive new norms, standards, and logic (W. R. Scott, 2008).

AAU realized that as a prestige organization, it may have the ability to alter norms and discourse of its own institutions and perhaps more broadly influence other campuses, as well. It developed a new set of values—that AAU institutions would be as excellent in teaching as in research—and worked to influence AAU campuses through dissemination and articulation of this new value system. In addition, it believed that based on its prestige and legitimacy, it could obtain the attention of leaders and help them shift priorities. AAU also thought that it could help align various messages from different organizations in the organizational field, which could also build pressure for changes.

This article explores specific ways in which these theories were enacted, focusing on how particular strategies could reflect multiple theoretical approaches to change. We also examine the efficacy of using multiple theories of change and their potential synergies and conflicts.

Method

Previous studies of scaled change in policy, international development, and education have used predominantly qualitative methods (often case study) to examine the process and underlying mechanisms for how scaled change is achieved and how various change strategies are deployed (Coburn, 2003; Elmore, 1996; Samoff, Sebatane, & Dembele, 2003). As a result, we utilized a case study approach and relied on multiple qualitative approaches—documents, interviews, and observations—to examine perceptions around motivation, sustainability, and strategies that have been successful for helping achieve change at scale, including multiple theories of change. The data for this article are part of a larger study of the AAU STEM Initiative that we conducted over 3 years, during Years 3 to 5 of the 5-year project (Dede, 2006). While we examined several different research questions and topics in our larger study, in this article, we focus on the ways in which AAU used multiple theories of change to inform its approach.

Data Collection

Document analysis

The first year of the project involved extensive document analysis to understand the STEM Initiative. Documents were developed during the first 4 years of the STEM Initiative including annual reports, correspondence about the initiative, the project framework, site visit notes, survey data about teaching practices, AAU-hosted webinars captured through video, and notes from multiple meetings including those of the network, project sites, advisory board, and the AAU team. In total, more than 10,000 pages of documents were reviewed to understand the initiative prior to researchers’ beginning work. After the research work began, we also reviewed all documents produced over the course of the 3 years of study.

Observations

The study also involved 2.5 years of observation and allowed for exploration of how various change theories informed approaches among the project sites as well as the AAU STEM Network. The observations provide empirical data to support perceptions in the interviews and triangulate perceptual data, as well as provide contextual information that helps to interpret interview and document data. Extensive field notes were taken at the following events: bimonthly planning meetings by the AAU initiative staff over 2.5 years—28 meetings in total were observed, annual workshops for the project site leadership teams, annual AAU STEM Network conference, annual in-person meetings and conference call meetings of the AAU STEM Advisory Committee, larger convenings focusing on special topics or themes such as the development of metrics or development of measures for better evaluating teaching, site visits to the eight project sites during Year 3, and national workshops and meetings in which the AAU STEM Initiative was involved.

Interviews

To understand the ways in which multiple theories of change informed AAU’s approach to scaling evidence-based teaching practices, we interviewed four groups that could provide insight: (a) all AAU STEM Initiative key leaders and personnel, (b) faculty and administrators on the eight project sites that were a target of the project—between six and 10 per campus, (c) faculty and administrators on nonproject sites (called points of contact) that are part of the larger AAU STEM Network, and (d) collaborators from outside organizations (groups such as NSF, HHMI, and National Academy of Sciences [NAS]) that have worked with AAU on the STEM Initiative. In total, the study included 104 interviews (48 from project teams, 26 AAU STEM Network members, 13 key leaders and personnel of the Initiative, and 17 collaborators).

The rationale for interviewing each of these groups is as follows: key personnel/advisory board members can describe their own observations about creating and implementing the Initiative and their perceptions about scale. Faculty and administrators that are part of the project teams have knowledge of how Initiative activities influenced the campus. Points of contact can directly speak to the influence of those events on their own thinking and on their campus’ ideas for pedagogical innovation, as well as what appeared to shape efforts at scale. Finally, collaborators provided an outside perspective on how they have seen the AAU STEM Initiative make changes at scale.

A customized interview protocol was developed for each of these different groups; however, there were some core elements that we asked across each interview. These core interview themes tap into all the key constructs related to scaling change (including each theory of change reviewed in the literature review), related to describing participants’ own involvement with the Initiative, challenges and facilitators of scale (where barriers to deploying multiple theories came up), evidence about scale, perceptions of the initiative, what has worked and not worked, strategies, ownership, and sustainability. Examples of the unique questions asked among specific groups include the history and development of the initiative among the AAU staff or awareness about the initiative and its details among collaborators and AAU STEM Network members. The interview protocols were reviewed by an advisory board formed for the project that included STEM reform leaders as well as higher education scholars. Interviews were approximately 1 hr in length and conducted via phone. Some interviews with project team members lasted as long as 2 hr. All interviews were recorded and transcribed.

Data Analysis

The qualitative data (documents, interviews, and observation) were analyzed using HyperResearch (a qualitative software program) that helps manage and analyze large amounts of qualitative data and eases the coding process. Data analysis used Kincheloe and Berry’s (2004) process of bricolage in qualitative analysis. This approach involves utilizing multiple theoretical perspectives to best understand a complex phenomenon, taking a multi- or interdisciplinary approach. This approach avoids reductionism by not taking single theoretical or narrow approaches to interpretation. Instead, various theories are overlaid to interpret data both separately and then simultaneously. For example, the researchers first examined a strategy such as annual meetings and how it could be understood through concepts and themes as part of organizational learning or networking separately. The next step would be to look at this strategy with all the theories together to see how certain themes may run across theories but have different meanings based on the theory. Social capital, for example, plays different roles in each of these theories, so its full capacity is seen when examined analytically by multiple theories. Bricolage acknowledges the complexities of social life and the need to bring in many different interpretive frameworks to best understand complex social processes. Analyzing processes such as change lend themselves to bricolage as the phenomena do not fit neatly into a psychological, sociological, or organizational disciplinary box. Given our emphasis on multiple change theories, bricolage also allowed us to look at change from these multifaceted perspectives. We used the different lenses of IT, systems theory, organizational learning, and networking to analyze the data, all of which address change from different vantage points and frame the AAU STEM Initiative from different perspectives. We also examined the interplay of different theories as we interpreted the data, looking at how theories complemented or contradicted one another.

We utilized situational coding, part of grounded theory, to examine different change theories and combine data from what we observed, from interviewees, and from documents to examine different change theories and what was occurring (Clarke, Friese, & Washburn, 2017). In situational coding, researchers identify the situation of interest—for us situations when multiple theories of change were deployed—then analyze those situations for nuance around that way the phenomenon emerged, including key actors and key characteristics or features. In the situational analysis, the activities, synergies, and challenges emerged that we describe in our findings.

Trustworthiness and Limitations

This study design draws on the most valid and systemic approaches to studying scale of change, emphasizing interviews and observations that help understand the key underlying mechanisms, such as influence and incentives as well as barriers to scale (Dede, 2006). Several approaches to trustworthiness were utilized. First, observations and document analysis were carried out for over a year prior to the interviews to ensure that the researchers were well aware of the context and initiative prior to interviews to maximize interviews being as valid as possible. Second, observations, documents, and interview data were compared to provide multiple data points in support of any finding, thus triangulating findings. Third, multiple researchers coded data, ensuring that the themes were identified by multiple individuals. Fourth, we convened and received feedback from an advisory board on our design, observation and interview protocols, sample, and interpretations of the data. In terms of limitations, we had limited physical exposure to project sites for impromptu conversations with campus participants. We selected a variety of individuals to speak with who had different positions and involvement but skewed toward those more involved with initiative.

Findings

We identified three different patterns in terms of the way that multiple theories were deployed. These patterns provide insight into the way that theories can either synergize or collide. First, we review how AAU embedded multiple theories of change within single activities or techniques. Second, we describe how the theories of change themselves were intentionally connected to enhance or amplify the work of the other approaches—for example, using networks to enhance learning or influence to enhance learning. Both of these examples suggest synergy in the deployment of the various theories of change. In addition, they show the ways in which the AAU targeted different activities and theories at different levels of the system for maximum impact. We also documented an instance where two theories (organizational learning and IT) collided and negatively affected efforts at scaling change. Thus, our data are able to suggest both the power of multiple theories and some challenges if these approaches are not carefully thought through and navigated.

Embedding Multiple Theories Into Project Activities

We review three project activities (the initial Request for Proposals [RFP], site visits, and annual meetings) that reflect the use of multiple theories of change. It is not that these activities inherently reflect these various change approaches, but rather that AAU deployed them in a way that imbued them with these different theories of change. We documented 11 activities that utilized multiple theories, but due to space purposes, we review three in this section. These three were chosen because they are commonly used strategies and so have practical advantages, were representative of all project activities in terms of their reflection of multiple theories of change, and provide the clearest examples of how multiple theories were deployed. The other eight are listed in Table A1 (see the appendix).

RFP and design of the project sites

One example of an activity that reflected multiple theories of change was the initial RFP for becoming a project site. The RFP was noted by various interviewees as well structured and strategic; it leveraged IT, learning, systems thinking, and networking.

IT

First the RFP was informed by IT, in particular, focusing on AAU’s role as an influencer and its ability, in particular, to capture the attention and shift the priorities of senior leaders. AAU staff reported how bringing in senior leaders was important to influence: “the RFP was a way to set up competition, a way to draw their attention to funding and prestige that we at AAU were making a priority.” In addition, the RFP drew the attention of administrators across AAU campuses to an area they were less likely to be focused on through the promise of funding for an unlikely area—improving teaching in STEM courses—and to the ideas (the Framework) embedded in the RFP, which informed planning. Many of the campuses that did not receive funding talked about how just the development of the proposal itself had helped to create a change initiative on the campus:

So we didn’t even get the funding but we still have several efforts that are now linked and will create an institution-wide change. Normally we would’ve had separate initiatives but the RFP pushed us to start thinking about our work in teaching reform differently and to consider more institutional infrastructure that’s needed. Without the AAU initiative, its influence, that just wouldn’t happen.

Therefore, several of the campuses changed their approach to STEM innovation based only on the RFP and the influence AAU can exert.

Organizational learning

AAU embedded the Framework into the RFP as a way to help campuses think differently about STEM reform. This choice was an intentional effort to create learning through a very thoughtfully crafted RFP that went through many renditions until it was believed it could speak to different campus stakeholders. Many interviewees noted how the initial RFP made their campuses (faculty and administrators) think about STEM reform in new ways—they noted how it promoted learning. Instead of thinking about individual faculty members in departments, they were pushed to think about overall institutional support for STEM reform, as the proposals required the involvement of multiple departments and administrators. One faculty member described the learning as a result of the RFP: “I think it really goes back to the initial request—its design—we had to shift our thinking from individual pockets of work spread around to an institutional effort.” This learning that occurred reinforced the systems theory of change, as embedded in the proposal itself was a requirement to focus on change across multiple levels.

Systems theory

The RFP fostered attention to change across multiple levels of the system by requiring senior administrative commitment to examine and alter campus infrastructure and collaborative leadership among campus stakeholders. First, the RFP asked campuses to provide a leadership commitment in terms of resources (matched funds) and a letter from the president. It also challenged institutions to create teams’ faculty, staff, and administrators to implement the efforts. It required both top-down and bottom-up commitment and support. By fostering leadership across the institution, AAU was also enabling systems change to take hold by requiring work and commitment at these various levels. A faculty member talked about the importance of leadership at multiple levels:

None of the other STEM projects I have worked on have had this push for administrators across levels—president, provost, dean and department chairs as well as faculty—all types of faculty—full professors to instructors and TAs. And I see how change requires leaders at the top and bottom and this project pushed us to do something we had not done before.

Network theory

While AAU deliberately planned the first three areas, the creation of a network through the RFP was more a byproduct of the systems approach and responding to AAU’s influence. By encouraging senior leadership involvement and key faculty and staff, AAU then developed on-campus networks that could also be harnessed for change. A faculty member described how the RFP created a network that would not have existed without the initiative’s encouragement:

Faculty across departments just rarely communicate. Even chairs across science, just so little communication. And vaguely we knew our physics department had gotten national recognition for its changes in teaching, but we never reached out. After the RFP, and our team meetings across departments to develop it, it became more natural to talk across units and we have since on a regular basis.

Site visits

Another example of an activity that reflected multiple theories of change was the site visits conducted by AAU staff. Interviewees described the ways in which site visits were helpful for facilitating change through IT, learning, networking, and invoking systems theory. We describe the ways in which site visits reflected multiple theories of change below.

IT

In terms of IT, interviewees describe how site visits were instrumental for influencing change because the AAU staff met with presidents, provosts, and other key leaders, helping bring attention to the initiative among senior administrators, raise the priority of the work, and obtain support to move forward. An administrator described the value of the site visits:

Each time we have a site visit we’ve really been invigorated. After our last site visit for example, I was able to get administrators’ attention on using data analytics, something I was unable to do in the past, and to think again about setting up some kind working group around promotion and tenure.

Faculty and staff also described using the AAU brand name during site visits to get resistant faculty and administrators into meetings that they might not have attended prior to AAU’s visit; this approach also helped the project teams make headway and later get support.

Organizational learning

Site visits were also used to create organizational learning among project teams through sharing of best practices from other campuses by AAU staff; this sharing got campuses to explore or consider new approaches. In addition, AAU staff might describe a change happening in one science department (e.g., biology) to try to influence another (e.g., physics) that led to the spread of ideas across departments. Site visits also provided the opportunity for learning by allowing participants to brainstorm around difficult challenges. One faculty noted, “we wanted to use the model of apprenticeship from North Carolina but were really worried about the tenured faculty’s reaction. But in talking with AAU, we were able to think that through.” Furthermore, AAU staff challenged faculty and administrators’ values and priorities (part of learning)—asking, for example, “Have you reconsidered your hiring criteria? Have you provided data to faculty in formats that are user-friendly? Is there funding for training faculty and TAs on active learning?” The researchers observed AAU staff repeatedly asking questions at site visits that were aimed at prompting learning.

Systems theory

The site visits generated systems thinking by asking campuses to reflect on their progress in comparison with the AAU STEM Framework, which intentionally drew attention to multiple levels of the system needing to be in alignment to drive change. As noted above, throughout the site visits, AAU staff would prompt questions among the administration that asked specifically about institutional commitment and priorities, spending, and infrastructure (e.g., classroom spaces, professional development). These questions were designed not only to provoke reflection and learning but also to promote a more systemic approach to change. AAU staff would similarly ask faculty and department chairs about how the existing infrastructure (e.g., departmental curriculum, learning objectives, reward system) supported their work (or not). AAU staff would communicate perspectives about work across the system, for example, telling administrators how infrastructure support (new classrooms) they created was working to support faculty in the implementation of new curriculum and pedagogy.

Network theory

In terms of supporting network development, AAU staff used site visits to expand project sites’ networks, connecting them to faculty and administrators on other campuses. One faculty member noted how this happened through the site visits: “Each time they visit, we have been able to identify (through AAU staff) another campus or person working on a similar challenge that we could contact.” Thus, site visits led to broadening of the on- and off-campus networks.

Annual meetings

Another strategy that reflected multiple theories of change was annual meetings and workshops. These meetings and workshops were highly regarded, as people enjoyed the opportunity to get together in person. In addition to being enjoyable, they were also valuable venues to promote networking, exert influence, sharing and learning of information, and consideration of the various pieces of the system needed to support sustained change.

IT

Several interviewees commented on meetings being influential in terms of AAU as a group that influenced them personally or drawing attention to STEM innovation back on their campuses. This experience reflects the ways in which an IT approach to change played out through this strategy. Many individuals talked about the impact of having the meetings at AAU’s national offices in Washington, D.C., and including AAU staff and national leaders in meetings. The physical space was noted as influential:

It’s hard to exactly pinpoint but there was something about being in Washington, D.C., and mixing with people I would never get a chance to interact with, and feeling like this is so different from other meetings I might go to.

AAU brought in influential speakers from the most prestigious scientific organizations that interviewees noted “said the same kinds of messages,” which had a strong impact on their faculty and administrative teams:

There are no other opportunities for me to be in a room with national higher education organizations, experts in STEM teaching like the Bayview Alliance or lobbyists from the AAU. All of these different groups but with a similar message that we need to improve teaching in STEM. It has been helpful in thinking about innovation on our own campus—how to get people’s attention, how to frame things.

The meetings leveraged the influence of leaders in the national movement of STEM reform and prestigious national organizations that would affect leaders at AAU campuses. The nature of the speakers being prestigious was mentioned repeatedly: “AAU is able to get the most prestigious and well-known speakers. Because of that, they have had really high attendance at meetings. I was surprised by that, especially given the focus of initiative [on teaching].” Influence was also part of meetings in terms of the repeated language that was used to reinforce new norms. Hunter Rawlings, AAU president, started every meeting and talk by saying that AAU institutions were going to become as excellent in teaching as in research. Nearly every individual we interviewed noted this specific language in discussing the initiative, reinforcing that a new logic was being created.

Organizational learning

Many interviewees also expressed how the annual meetings were important opportunities for learning. As one faculty member described,

I think the most successful aspect were the meetings—they provided us a chance to reflect on our work, to learn about what other people were doing, to hear about what’s happening at the national level, and recommit to the work.

Some interviewees also commented about more specific learning outcomes from the meetings such as the adoption of practices from other campuses, particularly the use of data analytics used at UC Davis, for example. In fact, as a result of annual meetings, we identified adoption of learned practices across 18 campuses related to curriculum, faculty models such as discipline-based education researchers, mentoring, active learning classrooms and facilities, new pedagogical approaches, and learning about the change process itself, particularly around change as being an institutional imperative.

Systems theory

In addition, the annual meetings were an opportunity to reinforce a systems theory of change, as the meeting structure utilized the framework document. Sessions focused on specific areas within the Framework such as addressing promotion and tenure, improving professional development, and considering learning outcomes. Interviewees noted that the meetings helped reinforce what could otherwise be a fairly difficult or complex approach to change due to the many parts of the system that need alteration: “actually making all these different changes—curricular, rewards, professional development, facilities, technology—it could be overwhelming, but the meetings were set up so that you were able to address these, understand these various parts that needed to change.”

Network theory

The annual meetings were a key approach to supporting and linking all types of different networks, from disciplinary groups of faculty to directors of centers for teaching and learning, to innovators in STEM. Annual meetings provided general networking time in terms of socials and free time. However, they also linked specific groups into more formal networks, such as faculty in particular disciplines and administrators in specific roles, and connected champions who were passionate about these issues across different AAU campuses who were often isolated or one of a handful of people on their own campus that cared about these issues. One department chair described the importance of the annual meetings for networking:

I have the opportunity to meet with other biology faculty and discuss curricular ideas but I also get to brainstorm with various administrators about faculty development, and I even talked with another chair about a grant idea and we’re working on that now. So the networking is definitely a big part of the meetings, and their value.

Synergy of Multiple Theories of Change

Another way that multiple theories of change operated was in terms of synergy across various theories and how they complemented or supported another area. AAU did not consider these theories as operating separately but typically in service of each other, and they tried to capitalize on synergies. We highlight two of these synergies; space does not allow for a full review of all synergies, but the ones we describe below exemplify the way that theories interacted in support of each other. While we focus on dyadic relationships here, theories were also connected in triads and quadruple connection points; however, dyadic relationships were most common.

Synergy of network theory and organizational learning

The networks were created with the intention of scaling changes by building relationships and sharing information. There was also the hope that campuses may also be able to use the networks to explore and brainstorm more complex issues and learn in more meaningful ways. One area that demonstrates the way that networking leads to learning and then to creation of another network is the area of data analytics. Perhaps, the practice that institutional leaders and faculty most frequently mentioned they were considering adopting was data analytics. Before the AAU STEM Initiative, most institutions indicated that they were not aware of efforts to track students’ academic progress over time, and there were no specific efforts for faculty to review data about student progression or success in different courses. By the end of the initiative, several campuses (both project sites and AAU STEM Network members) had adopted or were considering use of data analytics to improve STEM student success and better understand how teaching practices and curriculum were related to student learning and progression. As one point of contact described,

We’re really excited about the data analytics and not only how we collect a lot of information, talked to Marco [UC Davis data analytics expert], we also have them [AAU leaders] come out to our campus to help people understand and adopt this practice.

The AAU helped campuses to learn about data capacities and consider investments that needed to be made and new systems to be put in place, as well as learn what they need to facilitate on their own campuses to make the data efforts successful. One administrator describes this learning:

Our team went to several sessions across different meetings having to do with data on student learning, pathways, outcomes. All of that helped us to explore and think through our data systems and start to brainstorms ways we can improve.

So campuses learned about and adopted data analytics, which itself is a learning instrument. But then, the campuses adopting data analytics also formed their own separate network of 30 institutions that began to meet just to focus on data analytics implementation. Therefore, the synergy of these strategies created a sort of feedback loop. The networking strategy, which was a known way to create change, was adopted by this subgroup to foster ongoing learning.

Synergy of organizational learning and systems theory

AAU collected a variety of data to inform campus institutionalization across multiple levels of the system. Leaders in the initiative assumed that campuses may not have good information and be fully aware of the types of professional development that existed, infrastructure in support of teaching, awareness among faculty about evidence-based teaching practices, student learning outcomes, or even the success patterns of students. Without information related to aspects of the institution they were trying to change, leaders knew that campuses might falter in their efforts to scale change. Therefore, they initiated multiple data collection efforts at each campus so they had the data needed to address some of the issues that were aimed at institutionalizing STEM reforms across various levels. Data collected ranged from the development of learning outcomes and new curriculum to infrastructure support in terms of classrooms and resources to support technology. One administrator described how the data efforts of AAU supported efforts to create systems change:

The baseline data that was [sic] created suggested we had much lower levels of professional development than some of our peer institutions and that made us consider the kinds of supports we need to put in place. And our faculty’s development of student learning outcomes was also much lower and we have been looking into that and some professional development that might support that area specifically. So I saw the data collection efforts really helping support our efforts to create more institutional-level changes.

Conflicts and Negotiation of Multiple Theories of Change

While different theories of change can be synergistic, they can also come into conflict. This is one of the potential pitfalls of multiple theories of change—that the deployment of one approach may negatively shape or affect another strategy in play. Therefore, it is important to examine the ways that different theories of change can interact and affect each other. While AAU was fortunate to experience few instances of such conflict, we did see one major example in which the influence/IT strategies (particularly harnessing competition) appeared to negatively affect learning. AAU was aware of how their influence and power as an organization might suppress the openness and vulnerability needed for learning. They worried about whether campus participants would be honest and forthright about struggles; indeed, that feared lack of openness did occur.

AAU staff understood that part of the AAU culture is a sense of competition between campuses to “outdo each other.” The AAU leveraged this competition to motivate change, as a leadership team member from AAU described, “we know our campuses are highly competitive, want to be the best. They have this inclination to compare so we can use that.” Many interviewees noted that the competition between AAU campuses did indeed drive change on their campuses, with provosts pushing their project teams because they “heard another AAU institution had created active learning classrooms or new technologies,” for example. A faculty member at an AAU project site referred to this competition as a catalyst for change:

Competition is rooted in our institutions. After the AAU meeting in Laguna, I got this call—they heard what was happening at [two other institutions] and they wanted to know how we compared—what we were doing. It just throws us into motion.

While competition did spur some changes on AAU campuses, it also worked against efforts to spread changes and have learning occur across campuses. Each of the project sites developed an individual project and approach to change that they deeply believed in. Because they had very strong beliefs about their project being best suited for their campus, this may have created a reluctance to learn from the other sites or adopt practices. The sense of competition exacerbated their concerns about learning from and borrowing from other sites. Interviewees noted that if they were to borrow ideas from another site, it would reinforce the value of the other campus’ work; in the competitive culture set up between the AAU campuses, this was not desirable. One faculty member described how competition may have affected learning and adoption of new practices at the project sites: “I think we all just came in strongly believing in our ideas and maybe we felt borrowing ideas from the other campuses would somehow support them and we are competitive with each other.” This idea of competition affecting learning was referenced by an administrator: “taking an idea from another campus is to suggest you do not have equally good ideas on your own campus—this sort of one-upsmanship–well it does not breed uptake of competitors’ ideas.”

Furthermore, at several of the AAU strategic leadership planning meetings, the Initiative leaders described their concern about campuses’ sense of competition preventing them from problem solving together, learning, and sharing. They worried that campuses were missing out on learning within a broader network because of competitive behaviors witnessed at various gatherings, meetings, and webinars/phone conferences. An AAU staff member’s reflection on competition impeding learning in these settings captured this sentiment:

If they will not share information with each other [this was a reluctance to share survey and benchmark data], they are missing out on the whole idea of us connecting and networking them to learn from each other. We cannot hope to have learning when they compete.

Discussion

In the literature, theories of change are typically described as discrete schools of thought, even as researchers acknowledge that reality is more complex and multifaceted (Poole & Van de Ven, 2004). Heuristic devices in research aimed at pointing out a particular mechanism of change often disguise the complexity and interrelated nature of change strategies, as well as the complexity of organizations such as colleges and universities (Kezar, 2013; Poole & Van de Ven, 2004). Practitioners often also adopt single theories of change based on biases in their perspective and in an effort to reduce complexity (Bensimon, 1989; Bolman & Deal, 2007). Our research on the AAU STEM Initiative—a project that deployed multiple theories of change—allowed for the study of utilizing multiple theories of change, exploring advantages as well as potential challenges. This study leads to new insights into the change research, which is typically studied and understood in terms of singular theories or mechanisms of change, rather than in a more interdisciplinary approach that brings in various theories and insights to inform change agents (Kezar, 2013). Such multidisciplinary explorations also mirror reality in which neat boxes in terms of conceptual clarity or a singular phenomenon are less likely to account for or describe complex social phenomena such as change. The project and the study are unique in that they are among the few that adopt and document a multitheory approach. The few studies to explore multiple theories of change do not explore dynamics unique to multiple theories that can emerge, such as synergies and any potential problems from their intersection (Corbo et al., 2016; Poole & Van de Ven, 2004). Our study provides a detailed description of how multiple theories can be deployed to target different aspects of the change process, as well as how theories can work together or undermine one another.

In projects that involve multiple stakeholders and complex motivations and issues, using multiple theories of change to promote scale and institutionalization of change likely will increase the efficacy of the effort, especially if those theories are intentionally targeted at various levels of the system (Kezar, 2013; Poole & Van de Ven, 2004). Leaders in AAU adopted a multitheory approach to the change process that enhanced their efforts at scaling change and, ultimately, the efficacy of their project (Kezar, 2018). Stakeholders noted several perceived benefits of using multiple theories of change to guide action. Findings from our larger study identified specific ways in which IT worked to garner attention, resources, and make teaching excellence a priority among presidents, provosts, and other key leaders. In addition, networks helped to disseminate and spread ideas among faculty, staff, and administrators, whereas systems theory helped to address reward systems and infrastructure necessary to implement changes in teaching. Data and learning helped challenge ideas (or myths) about student success that blocked faculty from engaging in evidence-based teaching practices. Our study shows how influence/IT provided motivation for change, networks provided spaces for deliberation to get buy in and consensus, learning provided information to embed the change into individual mind-sets, and systems approaches helped sustain the initiative by targeting multiple levels. Systems thinking, learning, influence/IT, and networks all played different and critical roles to facilitate this complex change process. If the project’s leaders had utilized only a single change theory to guide their work, they would have risked oversimplifying the change process and missed out on the unique benefits that other theories promote.

The notion that theories of change can also be brought together to amplify the effect of a particular mechanism, such as networks and learning or influence and networks, has not been the focus of previous research and presents an important new area of inquiry (Collins, 1998; Poole & Van de Ven, 2004). Future studies that focus on capturing and perhaps identifying patterns where certain approaches have more success when coupled together could be helpful. This study also identified pitfalls of using multiple theories of change that have not been identified in previous studies of change—the way that multiple theories might come into conflict and slow or deter change processes (Kezar, 2013). As noted in the introduction to this article, there is an emerging belief that more theories or strategies deployed will be helpful in facilitating scaled change, but this study suggested that intentionality in deployment (actively looking for and creating synergies) and examining for potential conflicts in theories of change is also important (Bolman & Deal, 2007; Kezar, 2013; Poole & Van de Ven, 2004).

The implications of this study for change agents are important, as it provides empirical examples of how to deploy multiple theories of change into frequently used change activities or vehicles. Such examples have not been presented in prior research. Given the cost, time, and human capital expended for change initiatives and the low success rates (Kezar (2013) notes that less than 30% succeed), understanding ways to maximize multiple theories to amplify efforts and identifying ways to use particular change vehicles (e.g., site visits, annual meetings) to achieve multiple change goals is important to hone change agents’ approaches. Embedding change vehicles with multiple theories of change, as AAU did, is a very efficient way to use time and resources, especially as resources are increasingly finite. Change leaders typically register their concern over limited time and resources, and utilizing these multifaceted strategies is a very effective way to deploy multiple theories into a change process (Cameron & Quinn, 1988; Curry, 1992; Peterson, Dill, & Mets, 1997). If practitioners were aware of multiple theories of change and how to synergize and pull them together into a coordinated approach, they likely would save time, money, and human capital.

Conclusion

Foundations and government agencies are increasingly asking organizations and campuses proposing change efforts to identify their theory of change, focusing on a singular approach. However, pushing change agents into using single theories of change may be problematic. Our study showed the value of using multiple theories of change and also provided guidance on the best way to harness or use multiple change approaches. Establishing the value of multiple theories of change and having information about how they can best be deployed helps to expand the thinking of funders and government agencies and increase the efficacy of efforts to scale change. Documenting and understanding change processes in their full complexity has been rarely achieved in research, and this study offers an important first foray into the promise, deployment, and synergies of multiple theories of change.

Footnotes

Appendix

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The article was developed from a grant project funded by the National Science Foundation, Scaling STEM Pedagogical Reform at Association of American Universities (AAU): NSF# DUE-1432766.

Notes

Author Biographies

Adrianna J. Kezar is the Dean’s professor of Higher Education Leadership at the University of Southern California and Director of the Pullias Center. Dr. Kezar is a national expert on change, governance, and leadership in higher education, and her research agenda explores the change process in higher education and the role of leadership in creating change.

Elizabeth M. Holcombe is a visiting research associate at Indiana University Bloomington’s Center for Postsecondary Research. Dr. Holcombe’s research focuses on teaching, learning, and assessment in higher education, as well as the processes that lead to changes in the educational environment.

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