C H A P T E R 1 9
Translating Research to Widespread Practice in Engineering Education
Thomas A. Litzinger and Lisa R. Lattuca
Introduction
Governmental, academic, and professional organizations around the world have pointed to the need for changes in engineer- ing education to meet global and national challenges (see, e.g., Australian Council of Engineering Deans, 2008; National Academy of Engineering, 2004; Royal Academy of Engineering, 2007). Some of these organi- zations have specifically pointed to the need for the changes in engineering education to be based on educational research (Jamieson & Lohmann, 2009, 2012; National Research Council [NRC], 2011). In spite of these calls for change, researchers are finding that the rate of change and the nature of the change are not keeping pace with the calls for change.
Reidsema, Hadgraft, Cameron, and King (2011) ask “why has change (in engineer- ing education in Australia) not proceeded more rapidly nor manifested itself more deeply within the curriculum” (p. 345) in spite of funding from the national govern- ment and continuing efforts of engineering
professional societies and Australian Coun- cil of Engineering Deans? Reidsema et al. report that interviews of sixteen coordina- tors of engineering science units at four dif- ferent universities in Australia revealed that traditional lecture combined with tutorials remained the dominant model of instruc- tion. An in-depth study of the state of engi- neering education in the United States by Sheppard, Macatangay, Colby, and Sullivan (2009) makes the case that “in the midst of worldwide transformation, undergraduate engineering programs in the United States continue to approach problem-solving and knowledge acquisition in an outdated man- ner” (Schmidt, 2009, p. 1).
A study of the awareness and adoption of innovations within U.S. engineering pro- grams found high awareness, but low adop- tion. Borrego, Froyd, and Hall (2010) sur- veyed engineering department heads in the United States on the use of seven inno- vations in engineering education, including student-active pedagogies and curriculum- based service learning. Awareness of these two research-based innovations was high,
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at approximately 80% of the 197 respon- dents. Just over 70% reported that student- active pedagogies were being used in their program, whereas only 28% indicated ser- vice learning was being used in their pro- grams. The use of student-active pedagogies, at least, would seem to be quite common. However, when asked what fraction of their faculty members used student-active peda- gogies, the department heads indicated that only about one third were using them.
This state of affairs is not unique to engi- neering educators or even to educators in general. As Henderson and Dancy (2009) have shown, slow adoption of research- based teaching practices exists in science education as well. In fact, workshops spon- sored by the U.S. NRC suggest that these problems exist for science, technology, engi- neering, and mathematics (STEM) educa- tion throughout K–121 and higher education in the United States (NRC, 2011). Indeed, writing about K–12 education, Cohen and Ball (p. 31) note: “We expect innovative activity at every level of education, but typi- cally sketchy implementation. . . . and even when there is broad adoption, to expect variable, and often weak, use in practice.” Other fields, such as healthcare (Bero et al., 1998; Kreuter & Bernhardt, 2009) and social work (Dearing, 2009; Nutley, Walter, & Davies, 2009), also report that research- based practices are not readily taken up by practitioners.
Fortunately, the literature on change and diffusion of innovations, as well as on the use of research-based practices in education and other fields, provides insights into the causes of low rates and low quality of adop- tion as well as strategies for increasing the chances of successful transfer. Drawing on this literature, we have attempted to do the following:
� Identify likely causes for the slow adop- tion and low quality of the adoption of research-based practices.
� Provide summaries of strategies that have been found to be effective at promoting high-quality adoption of research-based practices.
� Discuss opportunities and challenges for further research into the processes of adoption of research-based practices in engineering education.
� Offer an overall summary, in the Final Thoughts section, of key mes- sages for researchers who are developing research-based practices with the goal of widespread use and for leaders of educa- tional change processes.
Before taking up our main discussion, how- ever, we define what we mean by research- based practices. We also discuss the use of research-based practices in engineering edu- cation to set the context for the remainder of the discussion.
Research-Based Practices
So what is a “research-based practice?” Related terms that appear in the literature are “evidence-based practices” and “innova- tions.” A recent report on STEM education published by the NRC of the U.S. National Academies (2011) uses the term “promis- ing practices.” We use the term research- based practice to encompass all of these ele- ments. We take research-based practices to be those that have been studied in well- designed investigations that collect convinc- ing evidence showing that the practice can be effective in promoting learning. Quanti- tative research studies supporting the devel- opment of research-based practices should provide reliable and valid evidence that the practice has a significant and substan- tial effect on learning. As we shall see later in the chapter, however, demonstrat- ing that a new practice has a sizeable, sta- tistically significant effect is not sufficient. High-quality adoption of a practice is more likely when those who adopt the new prac- tice understand why it works. Therefore, a research-based practice must also be based on research that establishes why the prac- tice is effective. Generally, this research will be qualitative and will not involve statistical analysis.
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Limitations of this Review
Our approach to writing this chapter and the literature that we were able to access led to two limitations that are important to state explicitly. First, we focused the chapter on processes for bringing about large-scale change in faculty practice driven by educa- tion research. We do not address the factors that affect why individual educators decide to engage in a large-scale change effort nor do we address the experiences of those who undertake translation of research to practice as a personal journey. The other major lim- itation stems from the literature base that we were able to access, which is dominated by studies in the United States. We were able to locate some excellent work done outside of the United States, but still the majority of the references carry a U.S. per- spective. Furthermore, most of the mate- rials from outside the United States come from other Western countries. As discussed later in the chapter, adapting a practice to local context and culture is a critical part of successful transfer to widespread use. So, the dominance of a single country and cul- tural perspective (Western) in this review is a potentially significant limitation.
Research-based Practices in Engineering Education
Research-based practices enter engineering education primarily through two pathways. Until the last decade, the dominant path- way was through the adoption/adaptation of research-based educational practices devel- oped outside of engineering. Over the last ten to fifteen years, however, educational research within engineering has grown dra- matically and has begun to provide addi- tional research-based practices for engineer- ing educators. The scope of research-based practices in education and engineering edu- cation is very broad, spanning from recruit- ment of students to the performance of early career graduates in the workplace and every- thing in between. In this chapter, we focus
on pedagogical practices, but much of what we discuss also applies to increasing the use of research-based practices independent of the specific type of practice.
We use team-based learning to illustrate the time scale of adoption of an innova- tion in engineering education. Team-based learning was recently identified as the most widely adopted research-based practice in engineering education in the United States by participants in a workshop on diffu- sion of innovations in engineering education (Center for the Advancement of Scholar- ship in Engineering Education, 2011). To cre- ate a the timeline of the adoption of team- based learning in engineering education, we used the American Society for Engineering Education (ASEE) proceedings database to search for the terms – teams, cooperative learning, and collaborative learning2. Two different searches were conducted: one for papers with any of these terms in the title and one with any of the terms appearing in the full paper, including references. The title search is taken as an indicator of schol- arly use of team-based learning, whereas the full paper search is an indicator of aware- ness of team-based learning. Because of the number of papers involved, no attempt was made to judge the sophistication of the prac- tice described in the papers.
Figure 19.1 presents the timelines for the number of papers that include teams or cooperative or collaborative learning in the title and anywhere in the paper, for the period from 1996 to 2011 (the full range of dates in the database). The curves show sim- ilar trends with a ratio of number of papers with any of the terms to the number with the terms in the title of roughly 20:1. To give a visual indication of the rate of change in the years prior to 1996, the time scale begins at 1980 because 1981 was the year when the first paper on cooperative learn- ing was presented at an engineering confer- ence in the U.S (Smith, Johnson, & John- son, 1981; Smith, 1998, 2011). The dashed line connects the first paper with the term coop- erative learning in the title to the data from the ASEE database. The figure shows that it took nearly twenty-five years for the number
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Figure 19.1. Number of papers containing terms related to cooperative learning; data from 1996 to 2011 were generated from the Proceedings of the ASEE Annual Meeting.
of papers on team-based learning to reach steady-state, which we take as indicator of the end of change process.
This time scale is consistent the work of Getz, Siegfried, and Anderson (1997), who studied the adoption of innovations in higher education in the United States. They conducted a survey study of the adop- tion of thirty innovations in six categories from curriculum to financial services at more than two hundred colleges and universities. The number of years between the first per- centile adopters to the median percentile was twenty-six years. For the four curricular innovations in their study, women’s studies, computer science major, interdisciplinary major, and formal study abroad, that differ- ence was fifteen, seventeen, fifty-one, and fifty years, respectively. Thus, their work suggests a time scale measured in decades for change in higher education.
The time scale suggested by the publi- cation data on team-based learning and the work of Getz, Siegfried, and Anderson is dis- couragingly long. The literature on change in educational systems and on translation of research to practice provides important insights into the factors that lead to such a slow pace of change and to the reasons
why such efforts often fail. We provide an overview of this literature in the next sec- tion.
Challenges to Successful Transfer from Research to Practice
In this discussion, we are not concerned here with what Cohen and Ball refer to as “agent- less diffusion” through which a research- based practice is discovered and adopted without any direct action on the part of the developer, because such a process is highly unlikely to lead to widespread use of the research-based practice. Rather, we are concerned with the translation of research- based practices to widespread use through direct action on the part of the developers of the practice and/or other agents. The pro- cess by which the developers of a research- based practice seek to persuade others to adopt their research-based practice is often referred to as dissemination.
A common approach to dissemination is the “replication model” in which the instructor targeted as an adopter is expected to passively accept and apply the new practice just as it was developed (Bodilly,
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Glennan, Kerr, & Galegher, 2004). In this model, the researcher identifies the need for a new practice, develops and assesses it, and then seeks to disseminate it to poten- tial adopters. Trowler, Saunders, and Knight (2003) describe the change theory underpin- ning this approach as technical-rational; in this approach “experts plan and then man- age faithful implementation” (p. 7). The underlying belief of the replication approach is that “well designed interventions will cause change” (p. 7). As we shall see, there are a number of issues with the replication model of dissemination.
According to Bodilly et al. (2004), the replication model was commonly used in the 1960s and 1970s in U.S. higher education. The model involved the development of an educational innovation along with associ- ated training for educators that would lead to precise adoption of the innovation. The communication was essentially one-way, from the developers to the educators. Stud- ies of the replication approach found “few new sites that had implemented the design with fidelity” (Bodilly et al., 2004, p. 12). In an article on the state of large-scale educa- tion reform around the world, Fullan (2009) confirms the assessment that the replication model failed to achieve widespread adoption of innovative practices in the United States. He writes that in spite of large expenditures of resources on major curriculum reforms, “by the early 1970s there was mounting evi- dence that the yield was miniscule, confined to isolated examples” (p. 103). Clearly, the replication model was a failure.
A major issue with the replication model is that it does not treat the educators as active participants who bring prior knowl- edge, experience, and beliefs about teach- ing and learning to the adoption process. The parallels between the replication model, which treats the potential adopter as a vessel to be filled, and the transmission model of teaching, which looks at students in a simi- lar way, are somewhat disturbing. A related issue is that developers fail to meet the needs of potential adopters. Cohen and Ball note that the particular practice that the devel- oper seeks to disseminate often does not
address an “urgent” need of the potential adopters. In this situation, the developer is faced with creating a market for his or her research-based practice.
The nature of research-based practice that is being transferred to classroom prac- tice can also have a significant impact on the likelihood of successful transfer to large numbers of educators. Regarding the pro- cess of reform in K–12 education in the United States, Elmore (1996) writes that:
Innovations that require large changes in the core of educational practice seldom pene- trate more than a small fraction of American schools and classrooms, and seldom last for very long when they do. By ‘core of edu- cational practice’, I mean how the teachers understand the nature of knowledge and the student’s role in learning, and how these ideas about knowledge and learning are manifested in teaching and classwork. (p. 1)
In a similar vein, Cohen and Ball (2007) note that “ambitious” pedagogical practices that seek to change significantly what an educa- tor does in the classroom face the greatest challenges. They note that such practices are likely to lead to a feeling of “incompetence” on the part of potential adopters because familiar and conventional practices are being uprooted and challenged.
The points made by Elmore and Cohen and Ball are related to compatibility of an innovation as defined by Rogers (1995) within his book, Diffusion of Innovations. He describes diffusion of innovations as “the process through which an innovation is com- municated through certain channels over time among members of a social system” (Rogers, 1995, p. 10). The innovation itself is one of the four main elements of the model of diffusion of innovations; the other ele- ments are the social system within which potential adopters of the innovation live and/or work, the communication channels through which others learn about the inno- vation, and the temporal characteristics of the diffusion process. Rogers defines com- patibility, one of five key attributes of an innovation, as “the degree to which an inno- vation is perceived as consistent with the
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values, past experiences, and needs of poten- tial adopters” (p. 224). Research-based prac- tices aimed at making substantial changes in the core of educational practice are likely to be perceived as incompatible with past experiences and possibly with the needs of potential adopters.
Dearing (2009) discusses research transfer to practice in the field of social work using the framework of diffusion of innovations. He provides a list of the “top ten dissemi- nation mistakes”; a number of the mistakes are also relevant to transfer to practice in higher education. One of his top ten mis- takes is that developers create and advocate only a single research-based practice, rather than offering a set of practices from which potential adopters can choose. Another mis- take noted by Dearing is that developers assume that evidence of effectiveness will persuade potential adopters to implement the new practice. He suggests emphasizing other attributes of the practice, such as com- patibility. On a similar note, Henderson and Dancy (2010) suggest emphasizing personal connections over presentation of data.
Dearing also considers using the devel- opers as the leaders for dissemination as a mistake because the developers are often not the persons most likely to be able to engage and persuade potential adopters. Other researchers (e.g., Baker, 2007; Elmore, 1996; Horwitz, 2007; Schoenfeld, 2006) make a related point that the lack of orga- nizations specifically focused on translat- ing research to practice is a major barrier to widespread adoption of research-based practices. National governments have cre- ated such bodies, for example, the National Diffusion Network and the What Works Clearinghouse in the United States and Learning and Teaching Support Network in the United Kingdom. In the United States at least, the success at bringing about large- scale translation of research to practice has been limited (Fullan, 2009).
Challenges to the successful transfer of research-based practices can also arise as educators adapt them to meet personal and local needs. Coburn (2003) summarizes past work that relates to the nature and
quality of the implementation of new prac- tices. She notes the following characteristics of the transfer process (p. 4):
� Even when educators adopt new prac- tices, they do so in ways that show sub- stantial variation in depth and substance.
� Educators’ knowledge, beliefs, and expe- rience influence how they choose, inter- pret, and implement new practices, mak- ing it likely that they “gravitate” to new practices that align with their prior expe- riences.
� Educators tend to prefer new practices that affect “surface features” such as new materials or classroom organizations, rather than practices involving deeper pedagogical principles.
� Finally, educators tend to “graft new approaches” onto normal classroom prac- tices rather than changing those practices.
The findings of Henderson and Dancy (2009) on transfer of physics education research to practice in higher education are consistent with the trends noted by Coburn.
The sheer number of research-based practices available in the literature presents another challenge to widespread adoption. This situation is consistent with Cohen and Ball’s observation that the present approach to creating research-based practices and translating them to practice will result in “innovative activity at every level of edu- cation but typically sketchy implementa- tion” (p. 31). Their observation is consis- tent with Schoenfeld’s (2006) observation that the process of research is more highly valued than the process of implementa- tion. Within engineering education, the sit- uation is complicated by a lack of a com- mon vision on what needs to be changed and what research-based methods should be adopted.
Past work has also shown that ignoring the reality of the environment in which instructors find themselves, and the chal- lenges that environment may present to the adoption of the new practice, also contribute to failure of transfer (e.g., see
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Elmore, 1996). Environmental characteris- tics include instructional resources, disci- plinary expectations, policies, and man- agement. Lack of sufficient institutional resources and appropriate facilities can also hinder implementation of novel teach- ing practices. Disciplinary and institutional teaching norms can further impede or dis- courage experimentation with novel meth- ods (Henderson & Dancy, 2010). Cohen and Ball (2007) note that many developers of research-based practices fail to consider the need for special equipment and spaces on the transferability of their innovative prac- tice. Lack of incentives and recognition for the use of innovative pedagogies is widely noted (e.g., Cohen & Ball, 2007; Elmore, 1996; Fairweather, 2005) as a reason for the lack of use of innovative practices. Fair- weather (2008) notes yet another challenge to widespread adoption of research-based practices: faculty and institutions bear the costs of implementing and sustaining new practices whereas the majority of the ben- efits accrue to the students and those who employ them.
A recent study of some of the most improved school systems around the world has demonstrated that cultural differences can have an impact on the adoption process and what is required for success (Mourshed, Chijioke, & Barber, 2010). One example of how culture can affect the implementation process relates to the use of evaluation data. Mourshed and colleagues make the point that evaluating the impact of the new prac- tices is crucial to successful implementation, but that the results of those assessments must be used in a culturally sensitive man- ner. They report that it is common to make assessment data public in Anglo-American school systems, but that public release of such data would not be acceptable in many Asian and Eastern European school systems. A leader of an Asian system is quoted on this topic: “No good for our students could ever come from making school data public and embarrassing our educators” (p. 70).
Other work suggests that the culture of engineering education itself may contribute to failure, or at least increase the challenges
to successful translation to widespread use. A study of more than 10,000 faculty at 517 colleges and universities by Nelson Laird, Shoup, Kuh, and Schwarz (2008) investi- gated the importance that faculty members in a variety of disciplines placed on deep approaches to learning.3 In comparison to colleagues in other fields with less codified knowledge, for example, philosophy and literature, faculty members in engineering and science rated the importance of deep approaches to learning lower by nearly 0.75 standard deviations (p < .001). Thus, the cul- ture of teaching in engineering seems to be a significant challenge to the use of many research-based pedagogies that are intended to increase student engagement. Student resistance to changing accepted practices in the classroom is also a potential challenge to the use of nontraditional teaching methods (Dancy & Henderson, 2004).
Another cultural tension common in engineering (as well as other fields) is the relative value placed on research and teach- ing in decisions regarding tenure and pro- motion (Fairweather, 2008). Fairweather’s research, using data on approximately 17,000 faculty who responded to the National Sur- vey on Postsecondary Faculty in 1992–3 and 1998–9, showed that the more time a fac- ulty member spends in the classroom, the lower his or her salary, regardless of the type of four-year institution (Fairweather, 2005). His work also shows that the strongest predictor of faculty salary is the number of career publications. Comparing the differ- ential cost/benefit of one hour teaching or publishing “in the mean” demonstrates that time spent teaching costs a faculty mem- ber money whereas time spent publishing is rewarded with higher pay. Fairweather (2008) concludes that:
These findings strongly suggest that enhanc- ing the value of teaching in STEM fields requires much more than empirical evi- dence of instructional effectiveness. It requires active intervention by academic leaders at the departmental, college, and institutional level. It requires efforts to encourage a culture within academic programs that values teach- ing. (p. 24)
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Adopting research-based practices that lead to major shifts from traditional practices for teaching require a substantial invest- ment of time to learn about and imple- ment the new practices appropriately. The data from Fairweather indicate that invest- ing effort in a process adopting new peda- gogical practices is not the most productive use of time, at least when measured by salary compensation.
Schoenfeld (2006) makes a complemen- tary point about the effect of values on the process of transfer to practice. He asserts that the academy places higher value on research, that is, the process that creates and evaluates innovative teaching meth- ods, compared to development, that is, the process of transfer to practice. This dif- ference in value would make it less likely that researchers would undertake studies of transfer to practice.
An additional set of influences, exter- nal to colleges and universities, that can affect the process of adoption of research- based practices are offered by Lattuca (2010). In the case of engineering education, these include accreditation agencies pro- fessional societies, and organizations, such as the National Academies in the United States, which attempt to influence educa- tional practice. Ideally, external organiza- tions should be drivers for change rather than barriers. Indeed the growth of interest in the use of teams in engineering educa- tion, evident in Figure 19.1, to some extent can be attributed to ABET’s accreditation criterion 3, which includes the requirement that all engineering graduates develop team skills.
Fishman (2005) suggests a three-part framework for judging the “usability of inno- vations” that provides additional insights into reasons for failure to achieve wide- spread adoption. The three dimensions of his framework encompass many of the ele- ments discussed in this section; they are Capability, Culture, and Policy and Manage- ment. The capability of potential adopters is an indication of the extent to which they have the conceptual and practical knowl- edge required to use the new practice.
Culture refers to the “norms, beliefs, values, and expectations for practice.” Policy and management are organizational features such as faculty reward structures and support for professional development sets. He envisions these as coordinates of a three-dimensional space in which one can plot, at least concep- tually, the characteristics of the adopters and the organization in which they work and the characteristics required of the adopters and organization for the research-based practice to be successfully transferred to practice. Gaps will exist that must be closed if the translation to large-scale practice is to be successful.
In sum, the literature on transfer of educational research to practice identifies a number of reasons that a dissemina- tion approach is unlikely to succeed; these include:
� Failing to focus on the needs that poten- tial adopters see as most important
� Offering only a single practice rather than a cluster of practices
� Failing to account for the desire of adopters to adapt, modify, and choose new practices to suit their teaching pref- erences
� Failing to assist adopters in understanding and incorporating the key elements of the new practice that ensure its effectiveness
� Failing to address potential barriers in the environment in which the potential adopters work, which include resource limitations, academic culture, and reward systems.
Increasing the Chances of Successful Transfer
In this section, we discuss strategies that address a number of the reasons for fail- ure summarized in the preceding section. We also discuss an overall model that inte- grates many of the individual strategies. In addition, we have included summaries of two studies of successful implementations of new pedagogical practices around the world;
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one study focuses on engineering programs and the other on K–12 school systems. Both provide insights into achieving and sustain- ing change in pedagogical practices.
Strategies
Consistent with the literature on diffusion of innovations (Rogers, 1995), several authors note the importance of addressing needs that educators see as important (see, e.g., Cohen & Ball, 2007; Glennan, Bodily, Galegher, & Kerr, 2004). To ensure that they are address- ing important needs, the research team developing a new practice must understand the needs of potential users before beginning their research. Traditional needs assessment will not be adequate, however, because con- tinuing dialogue among developers and users is needed as the research-based practice is developed. Therefore, strategies that involve continuing dialog from the beginning of a project, such as including potential adopters from the beginning of the project, should be utilized. Indeed, Fairweather (2008) rec- ommends that every research study of ped- agogical innovation should be conducted from the beginning as if the ultimate goal of the work were to take the innovation to widespread practice.
Dearing (2009) and also Cohen and Ball (2007) suggest that providing educators with more than one practice that will address an important pedagogical need will increase the chances of successful transfer to practice by allowing educators to choose the practice that best matches their teaching preferences and environment. This strategy is consis- tent with the use of “intervention clusters” that are composed of alternative practices to address the same need (Rogers, 1995). Chances of widespread adoption should also be increased if researchers design a practice that can be adapted to meet local needs and that supports local innovation (Baker, 2007; Henderson & Dancy, 2010).
Dearing (2009) suggests the use of “guided adaptation” of research-based practices through which educators come to under- stand which aspects of the practice are central to its success and why the prac-
tice works. This approach would encourage effective adaptation of the practice, and it embraces the educator as an active partici- pant in the implementation process. Cohen and Ball (2007) similarly argue that educa- tors must understand the “underlying ped- agogical principles” of the new practice if successful transfer is to occur. They describe two processes that are important to helping educators learn about and adopt new prac- tices – elaboration, “the detail with which a reform is developed,” and scaffolding, “the degree to which the innovation includes a design for and other means of learning to carry it out” (p. 24). Detailed elaboration allows potential users to understand the new practice more fully and should, Cohen and Ball contend, include the underlying peda- gogical principles. Cohen and Ball point out, however, that a highly elaborated design could be seen as restrictive and conflict with the desire of educators to adapt the new practice to best suit their needs. Thus, a balance must be struck between the level to which a research-based practice is elab- orated and the need to allow educators to adapt that practice to their needs, with- out losing the key elements that made it successful.
Goldman (2005) provides a list of design principles for educational improvement. She advocates inquiry-based approaches to allow educators to construct understanding of new practices and how they can be imple- mented. She further notes the potential for learning communities and practitioner networks to facilitate implementation and support educators as they learn new prac- tices. McLaughlin and Mitra (2001) echo the potential of strong communities of practice to improve successful transfer of research to practice. Mourshed and colleagues (2010) note that peer led learning was particularly important for sustaining new practices and for creating a culture of innovation to drive continued improvement. Recent discussions of change in higher education have focused on the need for sociocognitive strategies that address the learning needs of instruc- tors and instructional staff, suggesting a vari- ety of learning experiences to promote the
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adoption or adaptation of curricular and instructional innovations. Reading groups, staff development, and ongoing professional development all provide opportunities for instructors to understand and learn new skills, roles, and educational beliefs asso- ciated with curricular change (Lattuca & Stark, 2009). Kezar (2001) notes that these strategies are well aligned with the academic culture of colleges and universities.
In “Change Thinking, Change Practices,” Trowler and colleagues (2010) focus on the role of leaders of academic departments and programs in promoting and embedding good practices in higher education. They contrast a technical-rational model for change to a social practices model and conclude that the latter is a better approach for leaders in higher education. Some of the implications of this model for leaders of change in higher education include the following: expect that the people that you are trying to persuade to adopt a new practice will see that prac- tice differently than you do; expect different faculty members to implement the practice in different ways; and be sensitive to the dif- ferent histories of individual faculty mem- bers and departments, if you want to max- imize the chances of successful adoption of the new practice (p. 19). Lattuca and Stark (2009) observe that changing academic pro- grams requires knowledge of program norms and the social skills necessary to work with these norms. Those who study change note that practices and artifacts reflect values and commitments (e.g., Eckel, Hill, & Green, 1998). Understanding how changes in class- room practices affect deeply held beliefs is essential to understanding how to pro- mote change, just as understanding a depart- ment’s cultural norms will suggest strate- gies for building support for educational improvements.
Based on a review of 650 studies in edu- cation, healthcare, social care, and criminal justice, Walter, Nutley, and Davies (2003) identified eight mechanisms for translation of research to practice. In a later publication (Nutley et al., 2009), they grouped these into five strategies: Dissemination, charac- terized as a one-way flow of information;
Interaction, characterized as two-way flow of information; Social Influence, defined as using influential peers to persuade poten- tial adopters; Facilitation, defined as giv- ing technical, financial, organizational, and emotional support to potential adopters; and Incentives and Reinforcement, including financial incentives and feedback. An eval- uation of the effectiveness of these strate- gies led to the conclusion that “interac- tive approaches currently seem to show most promise in improving use of research” (Nutley et al., 2009, p. 554). This obser- vation is consistent with recommendation of a social practices model of change in higher education by Trowler et al. (2010) and with recommendations of Kezar (2001, 2012) that combining social cognition approaches to change with other strategies yields the greatest results in higher education settings.
An Overall Model for Translating Research to Practice
In Extending the Reach of Education Reforms, Glennan and colleagues (2004) offer a “mutual adaptation model for a translation of research to practice that relies on a non- sequential process of interaction, feedback and adaptation among groups of actors” (p. 27). Their model, which falls in the interaction category as defined by Walter and colleagues (2003), was developed for a K–12 context and advocates interaction among developers, educators, schools, and their district/state. Glennan et al. note three key elements of this model: (1) develop- ing approaches and tools to enable mul- tiple users to implement the new prac- tice at a variety of sites; (2) ensuring high- quality implementation at each site; and (3) evaluating and improving the new prac- tice. This interactive approach is intended to address the major reasons for failure of more traditional approaches through inten- sive interaction among all those involved, by focusing on adaptation, as opposed to adoption, and by attending to the context in which the research-based practices will be implemented. Goldman (2005) echoes
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translating research to widespread practice in engineering education 385
Researchers
• Develop and ‘prove’ new prac�ce
• Develop implementa�on support
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implementa�on • Market the prac�ce
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Engr. Department
• Define needs
• Assess and choose among op�ons
• Form ‘working group’ • Align professional development and
suppor�ng infrastructure with selected op�ons
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• Review and align assessments and
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• Provide incen�ves for adop�ng new prac�ces
• Provide resources • Ensure that polices are suppor�ve of
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• Define needs
• Assess and choose among op�ons
• Engage in needed professional development
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Figure 19.2. Mutual adaptation model for engineering education. (After Glennan et al., 2004, p. 649.)
the key role of ongoing interaction among all parties involved. The model of Glen- nan et al. also explicitly includes attention to processes required to sustain the prac- tices. A variation on the mutual adapta- tion model for an engineering education context is presented in Figure 19.2. It is important to note that model is based on a single practice, which is not consistent with the need to provide adopters with multiples practices from which they can choose.
Case Studies
The Royal Academy of Engineering (RAE) and the Gordon Engineering Leadership Program at the Massachusetts Institute of Technology (MIT) funded a study on achieving sustainable change in engineer- ing education (Graham, 2012). The final report summarizes common themes about change in engineering education based on interviews with more than seventy interna- tional experts from fifteen countries with significant experience in bringing about
change in engineering education. It also pro- vides six case studies of successful change in engineering programs in Australia, Hong Kong, the United Kingdom, and the United States. The case studies provide important insights into how change is initiated, imple- mented, and sustained.
McKinsey & Company supported a study with a similar approach to the RAE–MIT study, but focused on K–12 school systems (Mourshed et al., 2010). In the McKinsey project, twenty highly successful school sys- tems on five continents were studied. The schools fell into two broad categories: “sus- tained improvers” with five years or more of consistent increases on international assess- ments of student performance and “promis- ing starts” who “have embarked on large- scale reform journeys employing innova- tive techniques that have shown significant improvements in national assessments in a short period of time” (p. 11). The report pro- vides important results on starting, imple- menting, evaluating, and sustaining change in very different environments and cultural contexts.
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386 cambridge handbook of engineering education research
Research Opportunities and Challenges
A number of authors point to the need to study the process of translation to wide- spread practice, for example, McLaughlin and Mitra (2001), Glennan et al. (2004), Goldman (2005), and Fairweather (2008). In this section, we take up this topic, highlighting major challenges to conducting such research and providing connections to related literature.
Numerous authors advocate the use of theory-based approaches in the design of research studies of transfer to practice. How- ever, some among them question whether available theories are adequate to guide rig- orous research on transfer to practice. Con- stas and Brown (2007) assert that the field is lacking true theories. They write about the need to design and conduct systematic studies that will yield generalizable findings about strategies for achieving widespread transfer to practice. Ideally, such studies are “built upon a set of disciplinary-based the- oretical propositions and analytical models capable of guiding decisions about how best to collect, analyze and interpret data. Cur- rently no well codified set of propositions or empirically anchored analytical frame- works exist” (p. 247). They also note that “little progress has been made in developing a comprehensive theory about how school improvement works and how such efforts might be scaled across schools, across pro- grams, and across populations of students and teachers” (p. 245). Schoenfeld (2006) echoes this sentiment: “the theoretical state of the field . . . and the current state of theo- retical disputation seriously undermine the R↔P (research to practice) process” (p. 22). It would appear that an important issue in studies of translation to widespread prac- tice is development of an adequate theory to guide the research. Constas and Brown offer an example of a possible research design based on theories from other fields – imple- mentation theory and developmental sys- tems thinking.
Although not rising to the level of theory as defined by Constas and Brown, there are
conceptual frameworks related to change at the individual and organizational level that can inform research in this area. The classic work of Rogers (1995) on diffusion of inno- vations synthesizes much of what is known about how novel practices propagate in a wide range of fields. Dearing (2009) pro- vides a good summary of Rogers’ work and describes how he has applied it in his studies of translation to practice in healthcare.
Senge’s work on learning organizations (1990) provides another lens through which to view the actions that are needed within an organization to build a culture that val- ues and invests in learning new practices. In her book, Changing Academic Work: Devel- oping the Learning University, Martin (1999) applies the five disciplines from Senge’s work – personal mastery, mental models, shared visions, team learning, and systems thinking – to academe. Her work provides insight into the organizational challenges involved in making substantive change based on a survey and interviews of academics in the United Kingdom and Australia.
The “Concern-Based Adoption Model,” first described by Hall, Wallace, and Dorsett in 1973, is focused on the process by which individual educators adopt innovations and also provides a process for facilitating the adoption process. The current version of the Concern-Based Adoption Model (CBAM) is described in Implementing Change (Hall & Hord, 2011). A key aspect of the model is attending to the concerns of the potential adopters as they learn about and adapt the new practice for their use. The two scales within CBAM are the Stages of Concern and Levels of Use. The Stages of Concern range from unconcerned to refocusing. In the first stage, the potential user is uncon- cerned about the new practice; in the high- est stage of the scale, the refocused user has substantial experience with the innovation and is exploring ways to improve it. The Levels of Use scale ranges from non-use to renewing. The highest stage on this scale is a user who is evaluating and improving the innovation. Focused very tightly on the individual educator, this model comple- ments organizational change models.
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translating research to widespread practice in engineering education 387
Motivational factors are present in many of the models that we have discussed and are among the challenges to successful trans- fer to practice. For example, we earlier noted Rogers’s focus on the compatibil- ity of an innovation, which suggests that innovations will be more successful if they are “perceived as consistent with the val- ues, past experiences, and needs of poten- tial adopters” (1995, p. 224). Dearing (2009) similarly stressed compatibility and included among his top ten mistakes the assump- tion that evidence of effectiveness is suffi- cient to persuade individuals to implement new practices. In the Royal Academy of Engineering’s report on successful change in engineering schools, Graham (2012) argued that although pedagogical evidence may influence course-level change,
. . . successful widespread changes are usu- ally triggered by significant threats to the mar- ket position of the department/school. The issues faced are strongly apparent to faculty and, in some cases, university management have stipulated that a fundamental change is necessary for the long-term survival of the programme and/or department. (p. 2)
From the perspective of motivation theory, this statement highlights the role of exter- nal and internal influences on motivation for change. In general, motivation theories view motivation as potentially “intrinsic” to the individual or “situational,” that is, stim- ulated by external factors (see, e.g., Ren- niger, 2000). In addition, motivation is influ- enced by an individual’s expectations about the consequences of a particular behavior or activity as well as the value he or she places on that behavior or activity. “Expectancies” of success or failure and one’s perceptions of whether adopting new practice will yield rewards or be personally satisfying affect the individual’s motivation to learn and engage in new practices (see, e.g., Eccles & Wigfield, 2002). As noted in our earlier discussion of the work of Trowler et al. (2010), individuals in the same setting (a school or department) will often interpret the same events or infor- mation differently, which will lead to dif- ferent levels of motivation. Social cognition
models (see Kezar, 2001) acknowledge these differences and suggest that change is more likely to succeed if individuals can come to a common understanding of the need for change and of the meaning of that change for themselves and for their organization. Clearly, theories of motivation are impor- tant to understanding how change can be successfully initiated and sustained.
Beyond identifying appropriate models, or perhaps creating them, researchers study- ing translation to practice must decide what constitutes successful translation to practice, how to measure it, and how to design and conduct appropriate experiments. In early research on translation to practice and the adoption of educational reform, the mea- sure of success was simply the number of educators who were counted as using the new practice (Coburn, 2003). This simple counting approach proved to be unsatis- factory, so more complex measures have been proposed. Coburn’s definition of suc- cess provides an example of a more rig- orous set of measures. She recommends that the researchers studying the degree of success in the adoption of new practices consider four elements: Depth, Sustainabil- ity, Spread, and Shift in reform ownership. Successful transfer to widespread practice would correspond to
� Depth – the process of implementing the innovation leads to changes in “teachers’ beliefs, norms of social interaction, and pedagogical principles as enacted in the curriculum” (p. 4).
� Sustainability – the innovation continues to be used widely even after the imple- mentation process, and associated exter- nal resources, have ended.
� Spread – spread of the use of the inno- vation is accompanied by the spread of “underlying beliefs, norms, and princi- ples” (p. 7).
� Shift in reform ownership – the owner- ship of the reform shifts from the external researchers who developed and spreads to the educators and schools who sub- sequently “sustain, spread, and deepen reform principles themselves” (p. 7).
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Research built upon these four elements would examine the processes by which indi- vidual educators adopt the new practice, the impact of the process on educators’ beliefs and conceptions of teaching and learning, the communities of practice that play a role in sustaining and continuing to develop the practice, and how different administra- tive levels within an organization support and sustain the new practice. Engaging such a large-scale study presents substantial chal- lenges. Schoenfeld (2006) asserts that the effort to take research-based practices to widespread use is not valued highly in academia. He also notes that forming and sustaining the teams of researchers and users over the time period required to develop and take successful practices to widespread use is also very difficult.
Beyond these issues are those related to selecting the types of study and design- ing the complex experiments that would be required to execute them. Glennan et al. (2004) outline two different classes of research studies that can be undertaken: studies conducted during the process of development and spread of an innovation and studies of major scale-up efforts. They suggest that both successful and failed scale- up efforts are worthy of study. In “Design- ing Field Trials of Educational Innovations,” Raudenbush (2007) proposes a conceptual model for studies of the transfer of research to practice similar to that used in clinical trials in medicine. Raudenbush (2007) also discusses issues related to the design such as randomization, generalization, and mini- mizing bias.
Raudenbush’s conceptual model for stud- ies of transfer to practice has two stages. In the first stage, the research-based practice is studied under ideal conditions, for exam- ple, use by highly motivated educators sup- ported by generous resources, to establish its efficacy. In the second stage, which he describes as field trials, the research-based practice is tested under conditions that will exist when the practice is put in place under realistic conditions, for example, potential users are skeptical and they are not sup- ported with generous resources. Such a two-
stage study would uncover many challenges to the successful transfer to widespread practice.
Conducting research on transfer to wide- spread practice clearly presents formidable challenges. First, there are the issues of scale, the large number of educators and students who would be involved and the timescale over which the effort must be sustained. Then there is the complexity of the param- eters involved in establishing success includ- ing effects on student learning, changes in classroom practice, and changes in educa- tors’ beliefs about teaching and learning. The early stages of the transfer to prac- tice are much more amenable to study because the size and duration of the stud- ies will be substantially reduced. However, the issues of establishing appropriate mea- surement methods and analyzing the data remain.
Final Thoughts
In writing this chapter, we had three groups in mind: researchers undertaking investiga- tions of the process of translating research to practice, researchers developing innova- tive practices that they hope will achieve widespread use, and academic leaders who wish to increase the use of research-based practices in engineering education. In the section on research opportunities and chal- lenges, we highlighted some of the research topics from the literature for those inter- ested in studying the process of transfer to widespread practice. There are many excit- ing opportunities for research including fur- ther development of the theoretical foun- dations of this field of study. However, the scale, duration, and complexity of investiga- tions of the process of transfer of research to practice are significant challenges to researchers, especially if they wish to study the entire process from the conception of the practice to large-scale implementation.
In the sections on challenges to success- ful transfer and strategies for increasing the chances of successful transfer, we summa- rized results from the literature that we hope
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translating research to widespread practice in engineering education 389
will assist researchers who are developing new practices with the goal of widespread use. Some of the key messages for those researchers include: (1) align the practice with important needs of intended users; (2) begin planning for transfer to widespread practice from the very start of the develop- ment process; (3) engage the intended users as early as possible in the development of the research-based practice and of the trans- fer methodology; (4) incorporate research approaches that will determine why the practice is effective; and (5) plan for the fact that many users will want to adapt the prac- tice to match their needs and work environ- ment. Much of the literature cited in this chapter points to the importance of viewing the process of change as a learning process for participants; structuring ongoing interac- tions among those who seek to enact change with those who are being asked to imple- ment that change is an overarching recom- mendation.
Finally, we believe that this chapter has salience for academic leaders who are attempting to bring about change in engi- neering education in response to calls for change by governments and professional organizations. These academic leaders face unique challenges. One of the major chal- lenges is that answering the calls for change will require significant changes in how engi- neering instructors teach. The literature makes quite clear that such change is among the most difficult to achieve. Another major challenge is that the research-based prac- tices that are best aligned with the calls for change are not likely to align with urgent needs of the intended users, that is, those who teach engineering. Many who teach engineering feel that they are doing just fine, with some justification, based on the success of their students in finding good jobs or spots at top graduate programs. Consequently, they see little need for change in their teach- ing approach. Even in the face of these chal- lenges, however, there is hope for success as evidenced by engineering programs around the world that have achieved and sustained substantial changes in how engineering is taught and learned (Graham, 2012).
Acknowledgments
We thank the reviewers for their insightful comments and suggestions, which have sig- nificantly improved this chapter, and also Dr. Sarah Zappe for her input on an earlier version of this chapter.
Footnotes
1. K–12 refers to pre-elementary, elementary, and secondary education, i.e., kindergarten to Grade 12.
2. Cooperative learning compared to collabora- tive learning is “more structured, more pre- scriptive to teachers, more directive to stu- dents about how to work together, and more targeted (at least it was in its beginnings) to the public school population than to post- secondary or adult education” (Oxford, 1997). For a more in-depth comparison of the two see Matthews, Cooper, Davidson, and Hawkes (1995). Team-based learning may be either form, but is likely to describe students working together with little or no guidance on how they should conduct themselves within the team.
3. The construct of deep approaches to learn- ing, a term related to the work of Marton and Säljö (1976), was originally used to describe students who read text with the intention of understanding and used strategies such as look- ing for main themes and underlying principles and examining arguments critically (Entwistle & Peterson, 2004).
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