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  1. Many engineering problems assigned in undergraduate classes are numerical and can be solved using equations and algorithms—for example, truss problems in statics are often solved using the method of joints or the method of sections. Concept questions, which can be administered in class using active learning pedagogies, aid in the development of conceptual understanding as opposed to the procedural skill often emphasized in numerical problems. We administered a concept question about a truss to 241 statics students at six diverse institutions and find no statistically significant differences in answer correctness or confidence between institutions. Across institutions, students report that they are not accustomed to such non-numerical concept questions, but they grapple in different ways with the experience. Some frame engineering as inherently numerical, and thus do not value the conceptual understanding assessed by the question, while others recognize that developing conceptual knowledge is useful and will translate to their future engineering work. 
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    Free, publicly-accessible full text available June 1, 2024
  2. It has been well-established that concept-based active learning strategies increase student retention, improve engagement and student achievement, and reduce the performance gap of underrepresented students. Despite the evidence supporting concept-based instruction, many faculty continue to stress algorithmic problem solving. In fact, the biggest challenge to improving STEM education is not the need to develop more effective instructional practices, but to find ways to get faculty to adopt the evidence-based pedagogies that already exist. Our project aims to propagate the Concept Warehouse (CW), an online innovation tool that was developed in the Chemical Engineering community, into Mechanical Engineering (ME). A portion of our work focuses on content development in mechanics, and includes statics, dynamics, and to a lesser extent strength of materials. Our content development teams had created 170 statics and 253 dynamics questions. Additionally, we have developed four different simulations to be embedded in online Instructional Tools – these are interactive modules that provided different physical scenarios to help students understand important concepts in mechanics. During initial interviews, we found that potential adopters needed coaching on the benefits of concept-based instruction, training on how to use the CW, and support on how to best implement the different affordances offered by the CW. This caused a slight shift in our initial research plans, and much of our recent work has concentrated on using faculty development activities to help us advertise the CW and encourage evidence-based practices. From these activities, we are recruiting participants for surveys and interviews to help us investigate how different contexts affect the adoption of educational innovations. A set of two summer workshops attracted over 270 applicants, and over 60 participants attended each synchronous offering. Other applicants were provided links to recordings of the workshop. From these participants, we recruited 20 participants to join our Community of Practice (CoP). These members are sharing how they use the CW in their classes, especially in the virtual environment. Community members discuss using evidence-based practices, different things that the CW can do, and suggest potential improvements to the tool. They will also be interviewed to help us determine barriers to adoption, how their institutional contexts and individual epistemologies affect adoption, and how they have used the CW in their classes. Our research will help us formulate strategies that others can use when attempting to propagate pedagogical innovations. 
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  3. In this work-in-progress paper, we apply the ecosystems metaphor to develop a model to address the ways a technology-based tool, the Concept Warehouse (Koretsky et al., 2014), propagates in diverse settings and to how students use the tool in their learning. The ecosystem model goes beyond previous research using the Diffusion of Innovations framework (Rogers, 2005). While Diffusion of Innovations has been applied to educational innovations in engineering education (Borrego et al., 2010), physics education (Henderson and Dancy, 2008), and medical education (Rogers, 2002), it does not adequately account for the ways in which instructional and learning practices are socially situated within specific educational ecosystems, nor how those systems influence the ways in which practices are taken up by individuals and groups. 
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