Natural Disaster, Crime, and Narratives of Disorder: The 1861 Mendoza Earthquake and Argentina’s Ruptured Social and Political Faults

Social scientists studying natural disasters have generally found an absence of panic, a decrease in crime, and survivors working together to find basic necessities in the days and weeks after a catastrophe. By contrast, political and military authorities implement measures such as martial law to prevent chaos and lawlessness threatening private property. The media amplifies narratives of disorder, creating the perception of uncontrolled masses wantonly committing crimes in a disaster’s aftermath. Historians study natural disasters to view political, social, economic, and cultural structures stripped of their everyday veneer. The 1861 earthquake that destroyed the provincial capital of Mendoza in western Argentina provides an opportunity to examine narratives of disorder in newspapers and in survivor accounts that highlighted rampant looting and attributed these actions to rural peoples and the popular masses. Reports from the earthquake’s aftermath reflected the political conflicts between the hegemonic urban center of Buenos Aires and the interior provinces of Argentina, as well as the social divisions between urban elites and the lower classes. Judicial and criminal records from Mendoza, however, showed a decrease in crime after the earthquake, as well as rates of theft and robbery similar to those before the catastrophe, contradicting popular accounts of pervasive lawlessness

Using Critical Integrative Argumentation to Assess Socioscientific Argumentation Across Decision-Making Contexts

Socioscientific issues (SSI) are often used to facilitate students’ engagement in multiple scientific practices such as decision-making and argumentation, both of which are goals of STEM literacy, science literacy, and integrated STEM education. Literature often emphasizes scientific argumentation over socioscientific argumentation, which involves considering social factors in addition to scientific frameworks. Analyzing students’ socioscientific arguments may reveal how students construct such arguments and evaluate pedagogical tools supporting these skills. In this study, we examined students’ socioscientific arguments regarding three SSI on pre- and post-assessments in the context of a course emphasizing SSI-based structured decision-making. We employed critical integrative argumentation (CIA) as a theoretical and analytical framework, which integrates arguments and counterarguments with stronger arguments characterized by identifying and refuting counterarguments. We hypothesized that engaging in structured decision-making, in which students integrate multidisciplinary perspectives and consider tradeoffs of various solutions based upon valued criteria, may facilitate students’ development of integrated socioscientific arguments. Findings suggest that students’ arguments vary among SSI contexts and may relate to students’ identities and perspectives regarding the SSI. We conclude that engaging in structured decision-making regarding personally relevant SSI may foster more integrated argumentation skills, which are critical to engaging in information-laden democratic societies

Developing and evaluating a pollination systems knowledge assessment in a multidisciplinary course

Background: Although pollinators play an integral role in human well-being, their continued global decline reflects the need to provide and evaluate general pollinator knowledge to promote their conservation. Enhancing learners’ understanding of the complexity inherent in pollination systems within the science classroom may help them make more informed decisions regarding pollinator conservation actions. By measuring conceptual understanding of pollination systems, science educators can identify learners’ knowledge needs and inform their teaching in science classrooms. Based on previously developed theoretical frameworks describing pollination systems knowledge, we created and evaluated a new instrument to assess pollination systems and conservation actions knowledge. The Pollination Systems Knowledge Assessment (PSKA) is a multiple-true–false instrument containing 18 question stems and 70 accompanying T–F items encompassing three organizational components of pollination knowledge regarding (1) plant structures, (2) pollinator structures and behaviors, and (3) pollination systems function and pollinator conservation. Results: We refined the PSKA based on expert discussions, think-aloud interviews, and pilot testing before and after presenting a wild pollinator conservation unit within a postsecondary science literacy course. The PSKA elucidated learners’ misconceptions and revealed discriminating items from the three organizational components of pollination systems knowledge. Conclusions: The PSKA may aid educators in exploring learners’ conceptual understanding, identifying areas of misconceptions, and refining educational programming aimed at improving learners’ pollination systems knowledge

Changes in students’ mental models from computational modeling of gene regulatory networks

Background: Computational modeling is an increasingly common practice for disciplinary experts and therefore necessitates integration into science curricula. Computational models afford an opportunity for students to investigate the dynamics of biological systems, but there is significant gap in our knowledge of how these activities impact student knowledge of the structures, relationships, and dynamics of the system. We investigated how a computational modeling activity affected introductory biology students’ mental models of a prokaryotic gene regulatory system (lac operon) by analyzing conceptual models created before and after the activity. Results: Students’ pre-lesson conceptual models consisted of provided, system-general structures (e.g., activator, repressor) connected with predominantly incorrect relationships, representing an incomplete mental model of gene regulation. Students’ post-lesson conceptual models included more context-specific structures (e.g., cAMP, lac repressor) and increased in total number of structures and relationships. Student conceptual models also included higher quality relationships among structures, indicating they learned about these context-specific structures through integration with their expanding mental model rather than in isolation. Conclusions: Student mental models meshed structures in a manner indicative of knowledge accretion while they were productively re-constructing their understanding of gene regulation. Conceptual models can inform instructors about how students are relating system structures and whether students are developing more sophisticated models of system-general and system-specific dynamics

Highly protein-loaded melt extrudates produced by small-scale ram and twin-screw extrusion - evaluation of extrusion process design on protein stability by experimental and numerical approaches

Understanding of generation, extent and location of thermomechanical stress in small-scale (< 3 g) ram and twin-screw melt-extrusion is crucial for mechanistic correlations to the stability of protein particles (lysozyme and BSA) in PEG-matrices. The aim of the study was to apply and correlate experimental and numerical approaches (1D and 3D) for the evaluation of extrusion process design on protein stability. The simulation of thermomechanical stress during extrusion raised the expectation of protein degradation and protein particle grinding during extrusion, especially when TSE was used. This was confirmed by experimental data on protein stability. Ram extrusion had the lowest impact on protein unfolding temperatures, whereas TSE showed significantly reduced unfolding temperatures, especially in combination with kneading elements containing screws. In TSE, the mechanical stress in the screws always exceeded the shear stress in the die, while mechanical stress within ram extrusion was generated in the die, only. As both extruder designs revealed homogeneously distributed protein particles over the cross section of the extrudates for all protein-loads (20–60%), the dispersive power of TSE revealed not to be decisive. Consequently, the ram extruder would be favored for the production of stable protein-loaded extrudates in small scale