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In the United States, national and state standardized assessments have become a metric for measuring student learning and high-quality learning environments. As the COVID- 19 pandemic offered a multitude of learning modalities (e.g., hybrid, socially distanced face-to-face instruction, virtual environment), it becomes critical to examine how this learning disruption influenced elementary mathematic performance. This study tested for differences in mathematics performance on fourth grade standardized tests before and during COVID-19 in a case study of a rural Ohio school district using the Measure of Academic Progress (MAP) mathematics test. A two-way ANOVA showed that fourth- grade MAP mathematics scores were statistically similar for the 2019 pre-COVID cohort (n = 31) and 2020 COVID-19 cohort (n = 82), and by gender group, between Fall 2019 and Fall 2020. Implications for rural students’ academic performance in virtual learning environments are discussed. 

The Delphi method has been adapted to inform item refinements in educational and psychological assessment development. An explanatory sequential mixed methods design using Delphi is a common approach to gain experts' insight into why items might have exhibited differential item functioning (DIF) for a sub-group, indicating potential item bias. Use of Delphi before quantitative field testing to screen for potential sources leading to item bias is lacking in the literature. An exploratory sequential design is illustrated as an additional approach using a Delphi technique in Phase I and Rasch DIF analyses in Phase II. We introduce the 2 × 2 Concordance Integration Typology as a systematic way to examine agreement and disagreement across the qualitative and quantitative findings using a concordance joint display table. A worked example from the development of the Problem-Solving Measures Grades 6–8 Computer Adaptive Tests supported using an exploratory sequential design to inform item refinement. The 2 × 2 Concordance Integration Typology (a) crystallized instances where additional refinements were potentially needed and (b) provided for evaluating the distribution of bias across the set of items as a whole. Implications are discussed for advancing data integration techniques and using mixed methods to improve instrument development. 

This study presents qualitative findings from a larger instrument validation study. Undergraduates and subject matter experts (SMEs) were pivotal in early-stage development of a survey focusing on the four domains of Validation Theory (academic-in-class, academic-out-of-class, interpersonal-in-class, interpersonal-out-of-class). An iterative approach allowed for a more rigorously constructed survey refined through multiple phases. The research team met regularly to determine how feedback from undergraduates and SMEs could improve items and if certain populations were potentially being excluded. To date, the research team has expanded on the original 47 items up to 51 to address feedback provided by SMEs and undergraduate participants. Numerous item wording revisions have been made. Support for content, response process, and consequential validity evidence is strong. 

Existing literature has established that interpersonal and academic validating experiences help provide college students with the necessary personal and scholastic skillsets to thrive in higher education (e.g., Coronella, 2018; Ekal et al., 2011). This intrinsic mixed methods case study explores the extent to which undergraduate students perceived academic and interpersonal validation within a science, technology, engineering, and mathematics (STEM) pipeline program (CMSP) can empower students and influence their attitudes towards their learning environment. 

In the United States, national and state standardized assessments have become a metric for measuring student learning and high-quality learning environments. As the COVID- 19 pandemic offered a multitude of learning modalities (e.g., hybrid, socially distanced face-to-face instruction, virtual environment), it becomes critical to examine how this learning disruption influenced elementary mathematic performance. This study tested for differences in mathematics performance on fourth grade standardized tests before and during COVID-19 in a case study of a rural Ohio school district using the Measure of Academic Progress (MAP) mathematics test. A two-way ANOVA showed that fourth- grade MAP mathematics scores were statistically similar for the 2019 pre-COVID cohort (n = 31) and 2020 COVID-19 cohort (n = 82), and by gender group, between Fall 2019 and Fall 2020. Implications for rural students’ academic performance in virtual learning environments are discussed. 

In the United States, national and state standardized assessments have become a metric for measuring student learning and high-quality learning environments. As the COVID- 19 pandemic offered a multitude of learning modalities (e.g., hybrid, socially distanced face-to-face instruction, virtual environment), it becomes critical to examine how this learning disruption influenced elementary mathematic performance. This study tested for differences in mathematics performance on fourth grade standardized tests before and during COVID-19 in a case study of a rural Ohio school district using the Measure of Academic Progress (MAP) mathematics test. A two-way ANOVA showed that fourth- grade MAP mathematics scores were statistically similar for the 2019 pre-COVID cohort (n = 31) and 2020 COVID-19 cohort (n = 82), and by gender group, between Fall 2019 and Fall 2020. Implications for rural students’ academic performance in virtual learning environments are discussed. 

The COVID-19 pandemic has ravaged onward over the last year and has greatly impacted student learning. An average student is predicted to fall behind approximately seven months academically; however, this learning gap predicts Latinx and Black students will fall behind by 9 and 10 months, respectively (Seiden, 2020). Moreover, the shift to online instruction impacted students’ ability to learn as they encountered new stressors, anxiety, illness, and the pandemic’s psychological effects (Middleton, 2020). Despite the unprecedented circumstances that students were precipitously thrust into, state testing and assessments continue. Assessments during the pandemic are likely to produce invalid results due to “test pollution,” which refers to the systemic “increase or decrease in test scores unrelated to the content domain” (Middleton, 2020, p. 2). Considering the global pandemic, test pollution is prominent and worth exploring as it is uncertain whether state testing can identify the impact COVID is having on student learning. 

ABSTRACT We report on detailed multiwavelength observations and analysis of the very bright and long GRB 210619B, detected by the Atmosphere-Space Interactions Monitor installed on the International Space Station and the Gamma-ray Burst Monitor (GBM) on-board the Fermi mission. Our main goal is to understand the radiation mechanisms and jet composition of GRB 210619B. With a measured redshift of z = 1.937, we find that GRB 210619B falls within the 10 most luminous bursts observed by Fermi so far. The energy-resolved prompt emission light curve of GRB 210619B exhibits an extremely bright hard emission pulse followed by softer/longer emission pulses. The low-energy photon index (αpt) values obtained using the time-resolved spectral analysis of the burst suggest a transition between the thermal (during harder pulse) to non-thermal (during softer pulse) outflow. We examine the correlation between spectral parameters and find that both peak energy and αpt exhibit the flux tracking pattern. The late time broad-band photometric data set can be explained within the framework of the external forward shock model with νm < νc < νx (where νm, νc, and νx are the synchrotron peak, cooling-break, and X-ray frequencies, respectively) spectral regime supporting a rarely observed hard electron energy index (p < 2). We find moderate values of host extinction of E(B − V) = 0.14 ± 0.01 mag for the small magellanic cloud extinction law. In addition, we also report late-time optical observations with the 10.4 m Gran Telescopio de Canarias placing deep upper limits for the host galaxy (z = 1.937), favouring a faint, dwarf host for the burst. 

This chapter describes two mechanical expansion microscopy methods with accompanying step-by-step protocols. The first method, mechanically resolved expansion microscopy, uses non-uniform expansion of partially digested samples to provide the imaging contrast that resolves local mechanical properties. Examining bacterial cell wall with this method, we are able to distinguish bacterial species in mixed populations based on their distinct cell wall rigidity and detect cell wall damage caused by various physiological and chemical perturbations. The second method is mechanically locked expansion microscopy, in which we use a mechanically stable gel network to prevent the original polyacrylate network from shrinking in ionic buffers. This method allows us to use anti-photobleaching buffers in expansion microscopy, enabling detection of novel ultra-structures under the optical diffraction limit through super-resolution single molecule localization microscopy on bacterial cells and whole-mount immunofluorescence imaging in thick animal tissues. We also discuss potential applications and assess future directions.