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  1. Socially-relevant and controversial topics, such as water issues, are subject to differences in the explanations that scientists and the public (herein, students) find plausible. Students need to be more evaluative of the validity of explanations (e.g., explanatory models) based on evidence when addressing such topics. We compared two activities where students weighed connections between lines of evidence and explanations. In one activity, students were given four evidence statements and two models (one scientific and one non-scientific alternative); in the other, students chose four out of eight evidence statements and three models (two scientific and one non-scientific). Repeated measures analysis ofmore »variance (ANOVA) showed that both activities engaged students’ evaluations and differentially shifted students’ plausibility judgments and knowledge. A structural equation model suggested that students’ evaluation may influence post-instructional plausibility and knowledge; when students chose their lines of evidence and explanatory models, their evaluations were deeper, with stronger shifts toward a scientific stance and greater levels of post-instructional knowledge. The activities may help to develop students’ critical evaluation skills, a scientific practice that is key to understanding both scientific content and science as a process. Although effect sizes were modest, the results provided critical information for the final development and testing stage of these water resource instructional activities.« less
  2. The construct of active learning permeates undergraduate education in science, technology, engineering, and mathematics (STEM), but despite its prevalence, the construct means different things to different people, groups, and STEM domains. To better understand active learning, we constructed this review through an innovative interdisciplinary collaboration involving research teams from psychology and discipline-based education research (DBER). Our collaboration examined active learning from two different perspectives (i.e., psychology and DBER) and surveyed the current landscape of undergraduate STEM instructional practices related to the modes of active learning and traditional lecture. On that basis, we concluded that active learning—which is commonly used tomore »communicate an alternative to lecture and does serve a purpose in higher education classroom practice—is an umbrella term that is not particularly useful in advancing research on learning. To clarify, we synthesized a working definition of active learning that operates within an elaborative framework, which we call the construction-of-understanding ecosystem. A cornerstone of this framework is that undergraduate learners should be active agents during instruction and that the social construction of meaning plays an important role for many learners, above and beyond their individual cognitive construction of knowledge. Our proposed framework offers a coherent and actionable concept of active learning with the aim of advancing future research and practice in undergraduate STEM education.« less
  3. There is a large gap between the ability of experts and students in grasping spatial concepts and representations. Engineering and the geosciences require the highest expertise in spatial thinking, and weak spatial skills are a significant barrier to success for many students [1]. Spatial skills are also highly malleable [2]; therefore, a current challenge is to identify how to promote students’ spatial thinking. Interdisciplinary research on how students think about spatially-demanding problems in the geosciences has identified several major barriers for students and interventions to help scaffold learning at a variety of levels from high school through upper level undergraduatemore »majors. The Geoscience Education Transdisciplinary Spatial Learning Network (GET-Spatial; http://serc.carleton.edu/getspatial/) is an NSF-funded collaboration between geoscientists, cognitive psychologists, and education researchers. Our goal is to help students overcome initial hurdles in reasoning about spatial problems in an effort to diversify the geoscience workforce. Examples of spatial problems in the fields of geochemistry include scaling, both in size and time; penetrative thinking to make inferences about internal structures from surface properties; and graph-reading, especially ternary diagrams. Understanding scales outside of direct human experience, both very large (e.g. cosmochemistry, deep time) and very small (e.g. mineralogy, nanoparticles) can be acutely difficult for students. However, interventions have successfully resulted in improvements to scale estimations and improve exam performance [3]. We will discuss best practices for developing effective interdisciplinary teams, and how to overcome challenges of working across disciplines and across grade levels. We will provide examples of spatial interventions in scaling and penetrative thinking. [1] Hegarty et al. (2010) in Spatial Cognition VII 6222, 85- 94. [2] Uttal et al. (2012) Psychology of Learning and Motivation 57, 147-181. [3] Resnick et al. (2016) Educational Psychology Review, 1-15.« less