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  1. Free, publicly-accessible full text available July 7, 2023
  2. Dorn, Brian ; Vahrenhold, Jan (Ed.)
    Background and Context Lopez and Lister first presented evidence for a skill hierarchy of code reading, tracing, and writing for introductory programming students. Further support for this hierarchy could help computer science educators sequence course content to best build student programming skill. Objective This study aims to replicate a slightly simplified hierarchy of skills in CS1 using a larger body of students (600+ vs. 38) in a non-major introductory Python course with computer-based exams. We also explore the validity of other possible hierarchies. Method We collected student score data on 4 kinds of exam questions. Structural equation modeling was used to derive the hierarchy for each exam. Findings We find multiple best-fitting structural models. The original hierarchy does not appear among the “best” candidates, but similar models do. We also determined that our methods provide us with correlations between skills and do not answer a more fundamental question: what is the ideal teaching order for these skills? Implications This modeling work is valuable for understanding the possible correlations between fundamental code-related skills. However, analyzing student performance on these skills at a moment in time is not sufficient to determine teaching order. We present possible study designs for exploring this moremore »actionable research question.« less
    Free, publicly-accessible full text available June 1, 2023
  3. Abstract

    During thequadrature period(2010 December–2011 August) the STEREO-A and B satellites were approximately at right angles to the SOHO satellite. This alignment was particularly advantageous for determining the coronal mass ejection (CME) properties, since the closer a CME propagates to the plane of sky, the smaller the measurement inaccuracies are. Our primary goal was to study dimmings and their relationship to CMEs and flares during this time. We identified 53 coronal dimmings using STEREO/EUVI 195 Å observations, and linked 42 of the dimmings to CMEs (observed with SOHO/LASCO/C2) and 23 to flares. Each dimming in the catalog was processed with the Coronal Dimming Tracker which detects transient dark regions in extreme ultraviolet images directly, without the use of difference images. This approach allowed us to observefootpoint dimmings: the regions of mass depletion at the footpoints of erupting magnetic flux rope structures. Our results show that the CME mass has a linear, moderate correlation with dimming total EUV intensity change, and a monotonic, moderate correlation with dimming area. These results suggest that the more the dimming intensity drops and the larger the erupting region is, the more plasma is evacuated. We also found a strong correlation between the flare duration andmore »the total change in EUV intensity. The correlation between dimming properties showed that larger dimmings tend to be brighter; they go through more intensity loss and generally live longer—supporting the hypothesis that larger transient open regions release more plasma and take longer to close down and refill with plasma.

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  4. Abstract Background

    Grades in college and university STEM courses are an important determinant of student persistence in STEM fields. Recent studies have used the grade offset/grade penalty method to explore why students have lower grades in STEM courses than their GPAs would predict. The results of these studies are in doubt; however, as they use GPA as a reliable measure of academic performance, which is a disputed assumption. Using a predictive model of student performance, it is possible to produce a more accurate measure of academic performance than the observed GPA and discover if STEM courses are graded more stringently, and under which circumstances.


    A weighted logistic model of GPA better predicts academic performance than the observed GPA. Using this calibrated GPA it is found that the grade offset method predicts that STEM courses, departments, and programs grade significantly more stringently than non-STEM courses. The average grade difference between STEM and non-STEM course grades and GPAs is around four tenths of a grade point. An exception is general education courses offered by STEM departments, which are graded with the same leniency as non-STEM courses. Grade offset calculations that use the observed GPA systematically underestimate the negative offset in STEM grading relativemore »to calculations that use the calibrated GPA. The calibrated GPA is much more highly correlated with standardized tests such as the ACT (r = 0.49) than the observed GPA is (r = 0.25).


    Observed GPA is a systematically biased measure of academic performance, and should not be used as a basis for determining the presence of grading inequity. Logistic models of GPA provide a more reliable measure of academic performance. When comparing otherwise academically similar students, we find that STEM students have substantially lower grades and GPAs, and that this is the consequence of harder (more stringent) grading in STEM courses.

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  5. Free, publicly-accessible full text available March 1, 2023
  6. We present a scalable methodology to verify stochastic hybrid systems for inequality linear temporal logic (iLTL) or inequality metric interval temporal logic (iMITL). Using the Mori–Zwanzig reduction method, we construct a finite-state Markov chain reduction of a given stochastic hybrid system and prove that this reduced Markov chain is approximately equivalent to the original system in a distributional sense. Approximate equivalence of the stochastic hybrid system and its Markov chain reduction means that analyzing the Markov chain with respect to a suitably strengthened property allows us to conclude whether the original stochastic hybrid system meets its temporal logic specifications. Based on this, we propose the first statistical model checking algorithms to verify stochastic hybrid systems against correctness properties, expressed in iLTL or iMITL. The scalability of the proposed algorithms is demonstrated by a case study.
  7. This full research paper explores students’ attitudes toward second-chance testing and how second-chance testing influences students’ behavior. Second-chance testing refers to giving students the opportunity to take a second instance of each exam for some sort of grade replacement. Previous work has demonstrated that second-chance testing can lead to improved student outcomes in courses, but how to best structure second-chance testing to maximize its benefits remains an open question. We complement previous work by interviewing a diverse group of 23 students that have taken courses that use second-chance testing. From the interviews, we sought to gain insight into students’ views and use of second-chance testing. We found that second-chance testing was almost universally viewed positively by the students and was frequently cited as helping to reduce test takers’ anxiety and boost their confidence. Overall, we find that the majority of students prepare for second-chance exams in desirable ways, but we also note ways in which second-chance testing can potentially lead to undesirable behaviors including procrastination, over-reliance on memorization, and attempts to game the system. We identified emergent themes pertaining to various facets of second-chance test-taking, including: 1) concerns about the time commitment required for second-chance exams; 2) a belief thatmore »second-chance exams promoted fairness; and 3) how second-chance testing incentivized learning. This paper will provide instructors and other stakeholders with detailed insights into students’ behavior regarding second-chance testing, enabling instructors to develop better policies and avoid unintended consequences.« less
  8. Abstract. A flexible treatment for gas- and aerosol-phase chemical processes has been developed for models of diverse scale, from box models up to global models. At the core of this novel framework is an “abstracted aerosol representation” that allows a given chemical mechanism to be solved in atmospheric models with different aerosol representations (e.g., sectional, modal, or particle-resolved). This is accomplished by treating aerosols as a collection of condensed phases that are implemented according to the aerosol representation of the host model. The framework also allows multiple chemical processes (e.g., gas- and aerosol-phase chemical reactions, emissions, deposition, photolysis, and mass transfer) to be solved simultaneously as a single system. The flexibility of the model is achieved by (1) using an object-oriented design that facilitates extensibility to new types of chemical processes and to new ways of representing aerosol systems, (2) runtime model configuration using JSON input files that permits making changes to any part of the chemical mechanism without recompiling the model (this widely used, human-readable format allows entire gas- and aerosol-phase chemical mechanisms to be described with as much complexity as necessary), and (3) automated comprehensive testing that ensures stability of the code as new functionality is introduced.Together, these design choices enablemore »users to build a customized multiphase mechanism without having to handle preprocessors, solvers, or compilers. Removing these hurdles makes this type of modeling accessible to a much wider community, including modelers, experimentalists, and educators.This new treatment compiles as a stand-alone library and has been deployed in the particle-resolved PartMC model and in the Multiscale Online AtmospheRe CHemistry (MONARCH) chemical weather prediction system for use at regional and global scales. Results from the initial deployment to box models of different complexity and MONARCH will be discussed, along with future extension to more complex gas–aerosol systems and the integration of GPU-based solvers.« less
  9. In this paper, we study a computerized exam system that allows students to attempt the same question multiple times. This system permits students either to receive feedback on their submitted answer immediately or to defer the feedback and grade questions in bulk. An analysis of student behavior in three courses across two semesters found similar student behaviors across courses and student groups. We found that only a small minority of students used the deferred feedback option. A clustering analysis that considered both when students chose to receive feedback and either to immediately retry incorrect problems or to attempt other unfinished problems identified four main student strategies. These strategies were correlated to statistically significant differences in exam scores, but it was not clear if some strategies improved outcomes or if stronger students tended to prefer certain strategies.