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Computational modeling of scientific systems is a powerful approach for fostering science and computational thinking (CT) proficiencies. However, the role of programming activities for this synergistic learning remains unclear. This paper examines alternative ways to engage with computational models (CM) beyond programming. Students participated in an integrated Science, Engineering, and Computational Modeling unit through one of three distinct instructional versions: Construct a CM, Interpret-and-Evaluate a CM, and Explore-and-Evaluate a simulation. Analyzing 188 student responses to a science+CT embedded assessment task, we investigate how science proficiency and instructional versions related to pseudocode interpretation and debugging performances. We found that students in the Explore-and-Evaluate a simulation outperformed students in the programming-based versions on the CT assessment items. Additionally, science proficiency strongly predicted students’ CT performance, unlike prior programming experience. These results highlight the promise of diverse approaches for fostering CT practices with implications for STEM+C instruction and assessment design. 

Context.Rotation is an important phenomenon influencing stellar structure and evolution, however, it has not been adequately modelled thus far. Therefore, accurate estimates of internal rotation rates are valuable for constraining stellar evolution models. Aims.We aim to assess the accuracy of asteroseismic estimates of internal rotation rates and how they depend on the fundamental stellar parameters. Methods.We applied the recently developed extended-multiplicative optimally localised averages (eMOLA) inversion method, to infer localised estimates of internal rotation rates of synthetic observations of red giants. We searched for suitable reference stellar models, following a grid-based approach, and we assessed the robustness of the resulting inferences with respect to the choice of reference model. Results.We find that matching the mixed-mode pattern between the observation and the reference model is an important criterion for selecting suitable reference models. We propose (i) selecting a set of reference models based on the correlation between the observed rotational splittings and the mode-trapping parameter; (ii) computing the rotation rates for all these models; and (iii) using the average value obtained across the whole set as the estimate of the internal rotation rates. We find that the effect of a near surface perturbation in the synthetic observations on the rotation rates estimated based on the correlation between the observed rotational splittings and the mode-trapping parameter is negligible. Conclusions.We conclude that when using an ensemble of reference models that are selected by matching the mixed-mode pattern, the input rotation rates can be recovered across a range of fundamental stellar parameters such as mass, mixing-length parameter, and composition. Further, red giant rotation rates determined in this way are also independent of any near-surface perturbation of the stellar structure. 

K-12 Computer Science (CS) education is developing rapidly but still lacks a comprehensive measure for CS teachers’ pedagogical content knowledge (PCK). We respond to this need by describing the design of a CS-PCK instrument for ‘Algorithms and Programming’ that measures three broad constructs: (a) teachers’ understanding of standards and standards alignment, (b) teachers’ formative assessment practices, and (c) teachers’ self-efficacy for teaching and assessing CS. 

Background: While the nasopharynx is initially the dominant upper airway infection site for SARS-CoV-2, the physiologic mechanism launching the infection at the lower airway is still not well-understood. Based on the rapidity of infection progression to the lungs, it has been hypothesized that the nasopharynx may be acting as the primary seeding zone for subsequent contamination of the lower airway via aspiration of virus-laden boluses of nasopharyngeal fluids. Methodology: To examine the plausibility of the aspiration-driven mechanism, we have computationally tracked the inhalation process in three anatomic airway reconstructions and have quantified the nasopharyngeal liquid volume transmitted to the lower airspace during each aspiration. Results: Extending the numerical trends on aspiration volume to earlier records on aspiration frequencies indicates a total aspirated nasopharyngeal liquid volume of 0.3 – 0.76 ml/day. Subsequently, for mean sputum viral load, our modeling projects that the number of virions reaching the lower airway will range over 2.1×106 – 5.3×106 /day; for peak viral load, the corresponding number hovers between 7.1×108 – 1.8×109. Conclusions: The virion transmission findings fill in a key piece of the mechanistic puzzle on the systemic progression of SARS-CoV-2, and subjectively point to health conditions like dysphagia, with proclivity to increased aspiration, as some of the potential underlying risk factors for aggressive lung infections.