This paper describes the adaption and implementation of the Virtual Laboratory Project from its home university to other institutions. In the Virtual Laboratory Project students do not interact with real equipment to obtain data, but rather with computer simulations of laboratory equipment, obscured by noise. This innovation was developed with the intent of complimenting physical laboratory experiences by allowing future engineers to practice designing experiments, analyzing and interpreting data and making informed choices based on their analysis, skills they will need in industry. The idea of using virtual laboratories to facilitate project based learning is compelling since, once the software has been developed, the cost to transport a virtual laboratory to a new institution is relatively small, consisting mostly of developing teacher expertise. Understanding and planning for the transportability of educational interventions is being emphasized by funding agencies at the national level. The aspects of transportability specifically studied in this paper include usage history and current adoption information, the Virtual Laboratory Project’s perceived sources of effectiveness, barriers to implementation and adaptations made during the implementation process. This paper is a subset of a larger investigation on student learning in virtual laboratories. Artifacts of implementation and teacher and student perceptions were the primary data sources for this investigation. Thus far, the Virtual Laboratory Project has been adapted to high school, community college and other university settings and implemented in a total 15 institutions and 59 cumulative classes. Some of its perceived sources of effectiveness include the industrially situated context which is reinforced by the budget, and the components that afford students the ability to quickly and easily collect authentic data. This preliminary report suggests that this learning environment may have the potential for widespread adoption and adaptation; however, additional research is needed. Introduction Transportability is a widespread goal of education research and curriculum development. If an intervention is effective in one environment, many developers want to share the intervention with other teachers and institutions to have a larger impact and improve the educational process as a whole. Often developers of curricular interventions provide suggestions for implementation, curricular materials, and support; however, one aspect commonly missing is more reflective and evidence-based description of the implementation process as technical and pedagogical innovations move from the institution at which they were developed to other institutions with different faculty, different students and a different culture. The need for more systematic understanding has recently been emphasized at the national level. The President’s Committee of Advisors on Science and Technology Panel on Education Technology reported in 1997 that significant investment needed to be made in understanding learning and supporting the development of best practices. In supporting best practices, the P ge 22139.2 report emphasized the need for large-scale studies to determine best practices and provide information on generalizability. The Interagency Education Research Initiative, formed in response to that report, was created to support research and develop a knowledge base to “support the development, testing, and implementation of scalable and sustainable interventions to improve teaching and learning, particularly through the use of technology.” Additionally, funding agencies like the National Science Foundation (NSF) require a “broader impact” component in all grant proposals. Transportability is specifically emphasized in the new Transforming Undergraduate Education, in Science, Technology, Engineering and Mathematics (TUES) Program, which requires transportability as a main component for funding of proposals. The Institute of Education Sciences (IES) specifically listed “Scale-up Evaluation” as a research project goal in the most recent Request for Applications and approximately two percent of IES funded projects since 2004 had the goal of researching scale-up evaluations. This paper describes the adaptation of a virtual laboratory curriculum from its home university to other institutions. The Virtual Laboratory Project developed at Oregon State University is very early in the scaling or diffusion process. This innovation’s eventual fate is unknown, but investigation of the process at multiple stages is useful for informing future work, both within this project as well as for others. This paper presents preliminary results intended to assess the current adoption, investigate sources of the innovation’s effectiveness and examine issues and adaptations of this industrially situated Virtual Laboratory Project during implementation in various settings. Transportability and Scale-up Transportability is a broad topic that is difficult to research and assess. The ultimate question in this type of research is what works, with whom, where and in what conditions? It is concerned with both the overall diffusion of an innovation as well as the details of that process in assessing changes and effectiveness. Diffusion of innovations is a theory put forth by E.M. Rogers in his first book on the topic in 1962. Diffusion of innovations has been used as a theoretical framework for decades and has accounted for more than 5,000 publications in the field. According to Rogers “diffusion is the process in which an innovation is communicated through certain channels over time among the members of a social system.” 6 Characteristics that contribute to the rate at which an innovation is adopted include relative advantage, compatibility, complexity, triability, and observability. The innovation-decision process used by an individual in consideration of adopting an innovation consists of five stages “(1) from first knowledge of an innovation, (2) to forming an attitude toward the innovation, (3) to a decision to adopt or reject, (4) to implementation of the new idea, and to (5) confirmation of this decision.” Assessment of implementation is emphasized in the literature because of the major role it plays in evaluating the effectiveness of interventions. Implementation of an educational intervention may be performed with fidelity or adaption. Implementation fidelity, also known as integrity or adherence, is defined as “the degree to which teachers and other program providers implement programs as intended by the program developers.” Implementation fidelity has been used to assess interventions and training in parenting, suicide prevention, drug abuse prevention, violence prevention and many other programs. However, recreating the original implementation P ge 22139.3 as intended by the developers is challenging in practice. Implementation adaption, also known as adaptation, reinvention, or flexibility, allows for modifications to an intervention in order to suit the needs of the individual teachers and program providers. The acceptability of adaptation has been in debate since the 1980s, and has recently turned to a closer examination of what kinds of adaptations are acceptable. Coburn pointed out that there was tension between the viewpoints of scaling-up via implementation fidelity versus scaling-up via implementation adaptation and further argued that scaling-up was more than just the use of an intervention in multiple settings, but included other factors. Coburn proposed a conceptualization of scale that includes dimensions of depth, sustainability, spread, and shift. Dede added to Coburn’s conceptualization of scale with a dimension of evolution. From a design perspective, innovation development within those five, interrelated dimensions might necessitate certain activities: • Depth: conducting evaluation and research to understand and enhance causes of effectiveness; • Sustainability: adapting to inhospitable contexts via developing hybrids tailored to adverse conditions; • Spread: modifying to retain effectiveness while reducing the level of resources and expertise required; • Shift: moving beyond “brand” to support user ownership as co-evaluators, codesigners, and co-scalers; and • Evolution: learning from users’ adaptations to rethink the innovation’s design model. McDonald emphasizes the importance of the context in which an intervention is implemented, a point of view that supports careful and evidence based adaptation of an intervention to suit different contexts. Dede also emphasized the adaptation of innovations and summarized scaleup as “adapting an innovation that is successful in one setting to be effectively used in a wide range of contexts.” This paper integrates perspectives from both the diffusion of innovation theory and the scale-up framework. We use the diffusion of innovation theory particularly to track the metrics of the adoption process while scale-up provides a beneficial framework to characterize the important and unique attributes of the innovation. Research Design The research design is presented loosely in the form of the diffusion of innovations framework while incorporating Dede’s scale-up and innovation development framework. The timeline is presented first, to provide context. Next, the innovation is described along with evolution of the innovation at the home institution. This description includes the authors’ expected sources of effectiveness. Communication channels are expressed in two parts, the selection of initial institutions for adaptation and implementation, and the widespread dissemination of the Virtual Laboratory Project via additional diffusion mechanisms.
