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This paper describes the creation of an active learning framework and process of module development in efforts to build requisite knowledge and skills for at-risk learners enrolled in university introductory engineering design and technical graphics courses. Specifically, the module sequence, strategy for building direct relevance for at-risk populations, and culminating performance-based learning tasks are identified and detailed. Student-oriented reference points of learning are leveraged through relevant imagery, examples, and objects in further building personalized meaning and deeper comprehension of processes. Ten learning modules were initially developed within the Problem-Based Learning Modules (PBLM) framework and are currently being pilot tested under the Active Learning Modules to Support Problem-Based Learning: Effects on Engineering Retention and Academic Outcomes of At-Risk Students project funded through the National Science Foundation IUSE Program (Award # 1725874) to refine through evidence-based process outcomes. 

All engineering schools in the United States are currently teaching some version of a design graphics course, since it is required by ABET. This project will explore the factors that affect program persistence, in order to create a curricular approach that will improve the student experience, particularly for at-risk, females, underrepresented minority, and first-generation college students. Our overall goal is to refine a transferable Problem-Based Learning framework to promote engineering persistence, academic success, and engagement. The authors feel that such efforts will support the retention of STEM students by addressing shortcomings of introductory STEM courses (i.e. Engineering Graphics). 

Aging, often considered a result of random cellular damage, can be accurately estimated using DNA methylation profiles, the foundation of pan-tissue epigenetic clocks. Here, we demonstrate the development of universal pan-mammalian clocks, using 11,754 methylation arrays from our Mammalian Methylation Consortium, which encompass 59 tissue types across 185 mammalian species. These predictive models estimate mammalian tissue age with high accuracy (r > 0.96). Age deviations correlate with human mortality risk, mouse somatotropic axis mutations and caloric restriction. We identified specific cytosines with methylation levels that change with age across numerous species. These sites, highly enriched in polycomb repressive complex 2-binding locations, are near genes implicated in mammalian development, cancer, obesity and longevity. Our findings offer new evidence suggesting that aging is evolutionarily conserved and intertwined with developmental processes across all mammals.