Abstract

Education in Science, Technology, Engineering, and Mathematics (STEM) increasingly takes place across a wide range of environments. These cross-sector collaborations, referred to as ecosystems, advance STEM learning by combining theory and practice systematically across traditional education, a variety of out-of-school learning opportunities, and new approaches to workforce development. As of March 2018, there are 56 STEM learning ecosystems in North America involving more than 21 million students, 850,000 teachers and informal educators, 1,322 school districts, and over 1,200 out-of-school partnerships. Significant challenges emerge in efforts aimed at coordinating formative assessments and learning progressions for meaningful comparisons of the outcomes obtained within and between ecosystem niches. The conceptualization and implementation of STEM learning ecosystems have been informed by a sensitivity to and awareness of interdependent social relationships. This social ecology must now be complemented by a cognitive ecology that similarly facilitates more meaningful engagement with learning, for students, teachers, and larger communities. Promising directions for development are suggested by recent perspectives connecting Rasch’s probabilistic models for measurement with possibilities for metrological traceability to unit standards. Characterizations of metrological networks as ecological systems emerging from recent work in the philosophy and history of science are of particular interest in this regard.

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