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Author(s):  
Christina M. Krause ◽  
Pietro Di Martino ◽  
Judit N. Moschkovich

AbstractHow can school mathematics prepare citizens for a democratic society? Answers to this question are not static; they change as society and its problems change. The SARS-CoV-2 pandemic with its corresponding disease COVID-19 presents such a problem: what is needed to navigate this complex situation that involves, among other things, mathematics? Using the essay genre, we use three narratives from three countries—Italy, the USA (California), and Germany—to reflect on the goals of teaching mathematics during this crisis and examine aspects of each country’s standards for mathematics education. These three stories are framed by the authors’ backgrounds, experiences, interests, their country’s situation, and response to the pandemic. We first present the three narratives and then examine common issues across them that might provide insights beyond this current crisis, for preparing students to become active citizens. In particular, we focus on three issues: (1) developing a positive mindset toward mathematics to engage with and reflect on real-world problems, (2) improving interdisciplinary connections to the sciences to better understand how science professional practices and insights are similar or different from everyday practices, and (3) considering interpersonal and collective matters beyond the individual.


Author(s):  
Layla Fattah ◽  
Janice Gabrilove ◽  
Holly Oemke ◽  
Joseph Borrello ◽  
Turner Baker ◽  
...  

2021 ◽  
Vol 1 (1) ◽  
pp. 52-54
Author(s):  
Sambardhan Dabadi ◽  
Raju Raj Dhungel

Biomedical engineering is the blend of engineering and medical science, professional with a combination of knowledge of various engineering discipline to improve health care and quality of life. While biomedical engineering formally came up as major course in 1950s, the course started in Nepal just a decade back with its importance being acknowledged and biomedical engineers have been recruited by various institutes. Accounting for artificial intelligence, robotic surgery, 3-d printing, which are believed to be the future of medical science, it is necessary to strengthen the biomedical engineering. This article aims to highlight the overview as well as opportunities and challenges of biomedical engineering in Nepal.


2021 ◽  
Vol 30 (1) ◽  
pp. 55-61
Author(s):  
Eric P. Scibek ◽  
Matthew F. Moran ◽  
Susan L. Edmond

Context: The deep squat (DS) test is a component of the functional movement screen, which is used to assess the quality of fundamental movement patterns; however, the accuracy of the DS has not been studied. The DS is a complex, total body movement pattern with evaluation required at several points along the kinematic chain. Objective: To assess the accuracy of DS scoring by an athletic trainer, physical therapist, and exercise science professional via a comparative analysis with kinematic data (KD) and to identify scoring criteria that would improve agreement between raters and KD scores. Design: Cross-sectional study. Setting: Motion analysis laboratory. Participants: A rater from each of 3 movement science disciplines rated the DS of 23 male college athletes (20.3 [1.2] y; 70.5 [3.5] kg). Interventions: Subjects were outfitted with reflective markers and asked to perform the DS. The DS performance was scored by 3 raters and kinematic analysis. Subsequently, the optimal set of criteria that minimized the difference between mode rater score and KD was determined via a Nelder–Mead simplex optimization routine. Main Outcome Measures: Intraclass correlation coefficients (ICCs) were calculated using SPSS (version 23; IBM, Armonk, NY) to determine tester agreement with the KD score and between the mode score and KD score. Results: Agreement was poor for the athletic trainer (ICC = .387), physical therapist (ICC = .298), exercise science professional (ICC = .378), and raters’ DS scores when compared with the KD. Agreement was poor for the mode score when compared with KD prior to optimization and good following optimization (ICC = .830), thereby allowing identification of specific scoring errors. Conclusions: Agreement for DS scores is poor when compared with KD; however, it may be improved with optimization of DS scoring criteria.


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