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The science, technology, engineering and mathematics (STEM) workforce contributes to the U.S. economy by supporting 67% of jobs and 69% of the gross domestic product [1]. Currently, there is an increased demand for engineering and computer science (E/CS) professionals, particularly those from underrepresented (e.g., gender, racial, ethnic) and underserved (socio-economic, geographically isolated) groups who bring diversity of thought and experience to the national E/CS workforce [2]. Correspondingly, educational institutions are called upon to develop capabilities to attract, engage, and retain students from these diverse backgrounds in E/CS programs of study. To encourage and enable diverse students to opt into and persist within E/CS programs of study, there is a critical need to engage students in supportive and enriching opportunities from which to learn and grow. The importance of student engagement for promoting student growth and development has been researched to such an extent that its utility is widely agreed upon [5]. Importantly, it has been shown that both academic and extracurricular aspects of a student’s learning processes are characterized by engagement [6]. High Impact Educational Practices (HIP) provide useful opportunities for deep student engagement and, thus, positively influence student retention and persistence [4]. Kuh [3] identified eleven curricular and extracurricular HIP (i.e., collaborative assignments and projects, common intellectual experiences, eportfolios, first year seminars and experiences, global learning and study abroad, internships, learning communities, senior culminating experiences, service and community-based learning, undergraduate research, and writing intensive courses). In computer science and engineering education fields, however, the extent to which HIP affects persistence and retention has not been fully investigated. This project aims to examine E/CS undergraduate student engagement in HIP and to understand the factors that contribute to positive engagement experiences. 

The formation of biomolecular materials via dynamical interfacial processes such as self-assembly and fusion, for diverse compositions and external conditions, can be efficiently probed using ensemble Molecular Dynamics. However, this approach requires a large number of simulations when investigating a large composition phase space. In addition, there is difficulty in predicting whether each simulation is yielding biomolecular materials with the desired properties or outcomes and how long each simulation will run for. These difficulties can be overcome by rules-based management systems which include intermittent inspection, variable sampling, premature termination and extension of the individual Molecular Dynamics simulations. The automation of such a management system can significantly reduce the overhead of managing large ensembles of Molecular Dynamics simulations. To this end, a high-throughput workflows-based computational framework, Pipeline for Automating Compliance-based Elimination and Extension (PACE2), for biomolecular materials simulations is proposed. The PACE2 framework encompasses Simulation-Analysis Pipelines. Each Pipeline includes temporally separated simulation and analysis tasks. When a Molecular Dynamics simulation completes, an analysis task is triggered which evaluates the Molecular Dynamics trajectory for compliance. Compliant Molecular Dynamics simulations are extended to the next Molecular Dynamics phase with a suitable sample rate to allow additional, detailed analysis. Non-compliant Molecular Dynamics simulations are eliminated, and their computational resources are either reallocated or released. The framework is designed to run on local desktop computers and high performance computing resources. In the future, the framework will be extended to address generalized workflows and investigate other classes of materials.