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This work in progress paper we explain our process of co-sharing secondary qualitative data from separate projects funded by the National Science Foundation to better understand factors which influence faculty technology adoption in engineering education and provide a high-level presentation of preliminary results. Study A conducted 21 interviews of engineering faculty at a Midwestern US, STEM-centered university. These faculty were interviewed about the factors influencing their adoption and teaching of new engineering technologies, with a focus on programming languages, software, and instrumentation. Technology adoption models were applied as a theoretical lens for results analysis. Study B conducted 9 interviews with faculty in the College of Engineering at a Southern US university on the adoption of online laboratories in their instructional settings. The interviews focused on how faculty make use of online laboratories in electrical engineering as an essential resource. Innovation and propagation theories were applied as a theoretical lens for data analysis. The two data sets were co-shared for secondary analysis by each research group, using their own theoretical approaches. Preliminary findings lead us to believe that co-sharing of secondary data can expand qualitative data sets while providing a means for theoretical triangulation, improving data analysis.