Getting the most out of maths: How to coordinate mathematical modelling research to support a pandemic, lessons learnt from three initiatives that were part of the COVID-19 response in the UK.

In March 2020 mathematics became a key part of the scientific advice to the UK government on the pandemic response to COVID-19. Mathematical and statistical modelling provided critical information on the spread of the virus and the potential impact of different interventions. The unprecedented scale of the challenge led the epidemiological modelling community in the UK to be pushed to its limits. At the same time, mathematical modellers across the country were keen to use their knowledge and skills to support the COVID-19 modelling effort. However, this sudden great interest in epidemiological modelling needed to be coordinated to provide much-needed support, and to limit the burden on epidemiological modellers already very stretched for time. In this paper we describe three initiatives set up in the UK in spring 2020 to coordinate the mathematical sciences research community in supporting mathematical modelling of COVID-19. Each initiative had different primary aims and worked to maximise synergies between the various projects. We reflect on the lessons learnt, highlighting the key roles of pre-existing research collaborations and focal centres of coordination in contributing to the success of these initiatives. We conclude with recommendations about important ways in which the scientific research community could be better prepared for future pandemics. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

Behavioral, cognitive, emotional and social engagement in mathematics learning during COVID-19 pandemic.

A meaningful engagement of learners is critical in the quality teaching and learning of mathematics at school level. Learner engagement has been an ongoing issue in mathematics classrooms in Nepal and elsewhere. In this context, this study aimed to examine the level of engagement (behavioral, social, emotional, and cognitive activities) and their association with learning mathematics through the virtual mode of instruction during the pandemic. The cross-sectional online survey design was employed among 402 secondary-level mathematics teachers in Nepal. Descriptive statistics, correlation, and structural equation modeling were the major statistical techniques used in research. The findings indicate that the level of behavioral, social, emotional, and cognitive engagement of students was found to be high in the online mode of instruction. Additionally, cognitive engagement has significant highest impact on social, behavior, and emotional engagement.

Online-Offline Teaching for Bio-Pharmaceutical Students During the COVID-19 Pandemic: The Case Study of Advanced Mathematics in Application-Oriented Universities of China.

Background: With the development of the COVID-19 pandemic, the importance of online teaching is becoming more and more prominent, especially for the basic advanced mathematics majoring in bio-pharmaceutical in colleges. However, the only online teaching model loses efficiency when facing the undergraduates in application-oriented universities. Purpose: How to improve the teaching quality of advanced mathematics has always been a concern because the mathematical abilities of students in application-oriented universities are not ideal. In this article, we develop a blending online-offline teaching model that combined online teaching and offline outcome-based education (OBE), as an alternative to traditional offline education. Methodology: The comparative analysis experiment is carried out to the two classes of undergraduates. The control group and the experimental group are, respectively, the 2020 class students and the 2021 class students majoring in bio-pharmaceutical. The experimental group students receive the combined teaching method, while the control group students receive the traditional offline education. Results: (1) From the comparative analysis, we can find that the students under the online-offline teaching model are more differentiated than those under the traditional offline education model. (2) The online-offline teaching model equipped with "case study + knowledge point + applications" process has achieved a good teaching effect in the author's university. Conclusion: The proposed teaching model can well stimulate students' interest in advanced mathematics learning and resonate with students through actual cases, thereby arousing students' autonomous learning drive and allowing them to apply what they have learned to professional fields.

Theoretical and numerical analysis of COVID-19 pandemic model with non-local and non-singular kernels.

The global consequences of Coronavirus (COVID-19) have been evident by several hundreds of demises of human beings; hence such plagues are significantly imperative to predict. For this purpose, the mathematical formulation has been proved to be one of the best tools for the assessment of present circumstances and future predictions. In this article, we propose a fractional epidemic model of coronavirus (COVID-19) with vaccination effects. An arbitrary order model of COVID-19 is analyzed through three different fractional operators namely, Caputo, Atangana-Baleanu-Caputo (ABC), and Caputo-Fabrizio (CF), respectively. The fractional dynamics are composed of the interaction among the human population and the external environmental factors of infected peoples. It gives an extra description of the situation of the epidemic. Both the classical and modern approaches have been tested for the proposed model. The qualitative analysis has been checked through the Banach fixed point theory in the sense of a fractional operator. The stability concept of Hyers-Ulam idea is derived. The Newton interpolation scheme is applied for numerical solutions and by assigning values to different parameters. The numerical works in this research verified the analytical results. Finally, some important conclusions are drawn that might provide further basis for in-depth studies of such epidemics.

Preventing soft skill decay among early-career women in STEM during COVID-19: Evidence from a longitudinal intervention.

As the workforce shifts to being predominantly hybrid and remote, how can companies help employees-particularly early-career women in science, technology, engineering, and mathematics (STEM) fields-develop greater confidence in their soft skills, shown to improve organizational retention? We evaluate the effects of an online longitudinal intervention to develop soft skills among early-career women employees at a North American biotechnology company during the height of the COVID-19 pandemic. Controlling for baseline levels collected immediately prior to nationwide lockdowns, we find that a 6-month online intervention increased early-career women's assessments of their soft skills at work by an average of 9% (P < 0.001), compared with a decrease of about 3.5% for a matched control group (P < 0.05), resulting in an average treatment effect of nearly 13% on the treated group. Furthermore, we find evidence that the intervention led to an increase in manager-assessed performance for early-career women relative to employees not in the intervention, and that overall, increased self-assessments of soft skill competencies were associated with greater odds of retention. Results show how employee soft skill development was affected by the pandemic and provide insights for a feasible and cost-effective method to train and engage a hybrid or fully remote workforce.

Managing technostress in the STEM world.

The rapid evolution of technological advancements in the science, technology, engineering, and mathematics (STEM) fields is enabling ever faster progress. However, the rapid pace of change can also lead to elevated stress for STEM workers. Here, we provide strategies for coping with and limiting technostress amongst researchers and other STEM professionals.

A virtual adaptation of the taped problems intervention for increasing math fact fluency.

In response to restrictions on visitors within school buildings during the COVID-19 pandemic, the evidence-based math fact fluency procedure known as the taped problems intervention was adapted for use in a virtual setting. The present study used a multiple-probe across participants design to evaluate the effects of the adapted intervention on the subtraction fact fluency of three elementary school students with varying degrees of math difficulties. Researchers also measured whether fluency gains would generalize to subtraction fact family problems that were not targeted within the study procedures. Visual analysis of results indicated math fluency improvements across all students, regardless of initial performance level, but no evidence of generalization effects for any participant. Additionally, to further investigate intervention effects, two effect size measures were calculated (WC-SMD and NAP) and each participant's rate of improvement was measured in two ways. Slopes (digits correct per minute [DCM] gains per session) of baseline and intervention phases were compared, and DCM gains per intervention time were investigated. Discussion focuses on implications for providing academic interventions in virtual learning environments, the importance of direct instruction for subtraction fact fluency, as well as future directions for researchers. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

A Year into the Pandemic: An Update on Women in Science, Technology, Engineering, Math, and Medicine.

The coronavirus pandemic revealed long-standing, unaddressed fissures in our systems, including dramatic gender inequities in science, technology, engineering, mathematics, and medicine (STEMM) fields. Women have disproportionately carried the burden of childcare and other caregiving responsibilities during the pandemic, and there are strong indications that the pandemic will likely exacerbate preexisting disparities in the pipeline of women in STEMM and in leadership positions. Based on a literature review, our own experiences, and the experiences of our colleagues, we review promising strategies that have been implemented by funding bodies, journals, professional societies, and colleges/universities as well as additional strategies that might be helpful for these entities to implement to move forward with policies in place that address gender inequities and rebuild our institutional systems better. At this moment in time, institutions should collect data on metrics such as recruitment, retention, tenure/promotion, funding, professional society membership, awards/honors, and scientific publishing. These data will be essential in determining the impact of policies on women in STEMM to ensure they are having the intended effect as well as what future actions might be necessary in an iterative process.

Virtual Vanderbilt Summer Science Academy highlighted the opportunity to impact early STEMM students career knowledge through narrative.

Due to COVID-19 precautions, the Vanderbilt University summer biomedical undergraduate research program, the Vanderbilt Summer Science Academy (VSSA), rapidly transitioned from offering an in-person training program to a virtual seminar format. Our program typically supports undergraduate development through research and/or clinical experience, meeting with individuals pursuing postgraduate training, and providing career development advice. Evidence supports the idea that summer programs transform undergraduates by clarifying their interest in research and encouraging those who haven't previously considered graduate studies. We were interested in exploring whether a virtual, synchronous program would increase participants' scientific identity and clarify postgraduate career planning. Rather than create a virtual research exposure, our 5-week "Virtual VSSA" program aimed to simulate the casual connections that would naturally be made with post-undergraduate trainees during a traditional summer program. In seminars, presenters discussed 1) their academic journey, explaining their motivations, goals, and reasons for pursuing a career in science as well as 2) a professional story that illustrated their training. Seminars included Vanderbilt University and Medical School faculty, M.D., MD/Ph.D., as well as Ph.D. students from diverse scientific and personal backgrounds. In addition, weekly informational sessions provided an overview of the nature of each degree program along with admissions advice. Through pre-and post-program surveys, we found that students who registered for this experience already strongly identified with the STEMM community (Science, Technology, Engineering, Mathematics, and Medicine). However, participation in the Virtual VSSA increased their sense of belonging. We also uncovered a gap in participants' understanding of postgraduate pathways prior to participation and found that our program significantly increased their self-reported understanding of postgraduate programs. It also increased their understanding of why someone would pursue a Ph.D. or Ph.D./MD versus M.D. These changes did not uniformly impact participants' planned career paths. Overall, by providing personal, tangible stories of M.D., MD/Ph.D., and Ph.D. training, the Virtual VSSA program offered seminars that positively impacted students' sense of belonging with and connection to the STEMM disciplines.

Math matters: A novel, brief educational intervention decreases whole number bias when reasoning about COVID-19.

At the onset of the coronavirus disease (COVID-19) global pandemic, our interdisciplinary team hypothesized that a mathematical misconception-whole number bias (WNB)-contributed to beliefs that COVID-19 was less fatal than the flu. We created a brief online educational intervention for adults, leveraging evidence-based cognitive science research, to promote accurate understanding of rational numbers related to COVID-19. Participants from a Qualtrics panel (N = 1,297; 75% White) were randomly assigned to an intervention or control condition, solved health-related math problems, and subsequently completed 10 days of daily diaries in which health cognitions and affect were assessed. Participants who engaged with the intervention, relative to those in the control condition, were more accurate and less likely to explicitly mention WNB errors in their strategy reports as they solved COVID-19-related math problems. Math anxiety was positively associated with risk perceptions, worry, and negative affect immediately after the intervention and across the daily diaries. These results extend the benefits of worked examples in a practically relevant domain. Ameliorating WNB errors could not only help people think more accurately about COVID-19 statistics expressed as rational numbers, but also about novel future health crises, or any other context that involves information expressed as rational numbers. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Cognitive Enhancement Through Mathematical Problem-Solving.

Nowadays, modern lifestyle along with the ever-growing technological and scientific advancement, especially in developed countries, has led to a significant increase of the middle age and elderly population. As a consequence, a substantial rise in neurodegenerative diseases has been reported, such as mild cognitive impairment, Alzheimer's disease, and other types of dementia. The aim of this paper is to study the impact of mathematical problem-solving on cognitive enhancement of adults. Moreover, the possible applicability of mathematical problem-solving as part of a treatment in cases of adults suffering from different levels of cognitive decline due to neurodegenerative diseases has been taken into consideration. For the needs of this study, a qualitative research was conducted in a sample of 16 participants, in order to confirm the effect of the mathematical problem-solving process on their cognition and its reinforcement, as stated by the participants. The results of this research, as interpreted, indicate a positive effect of mathematical problem-solving on adult cognition and on cognitive processes in general. Nonetheless, there are certain limitations to this research, deriving from its nature, while others derive from the measures enforced during the SARS-CoV-2 outbreak. Therefore, this chapter suggests that a more thorough quantitative research should be conducted in order to specifically measure the magnitude, as well as the time span of the impact of mathematical problem-solving on adult cognitive enhancement. Moreover, it is proposed that future studies should concentrate on the usefulness of mathematical problem-solving as a component in both invasive and noninvasive cognitive treatments used to cure or alleviate the aforementioned cognitive impairments.

Are gritty students academically engaged in math and science?

This research examines the cross-cultural differences on triarchic model of grit (TMG) dimensions (i.e., perseverance of effort, consistency of interests, and adaptability to situations) and the associations of grit with academic engagement in Math and Science among secondary school students in one secondary school in Hong Kong (n = 101; M age = 12.44; SD = .60), nine secondary schools in Philippines (n = 575; Mage = 14.66; SD = .83), and two secondary schools in mainland China (n = 710; Mage = 13.39; SD = .56). Result of structural equation modeling via maximum likelihood estimation approach demonstrated that although all TMG dimensions were related to higher engagement in Math and Science, adaptability served as the strongest predictor of these outcomes even after controlling for the participants' cultural settings and conscientiousness. Consistency served as the weakest correlate of engagement outcomes. Conscientiousness, settings, and TMG dimensions explained 46% and 50% of the variance in Math and Science academic engagement respectively. These results provide additional evidence regarding the generalizability of TMG in non-Western societies. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Turning the Tide for Academic Women in STEM: A Postpandemic Vision for Supporting Female Scientists.

The "leaky pipeline" of women in science, technology, engineering, and mathematics (STEM), which is especially acute for academic mothers, continues to be problematic as women face continuous cycles of barriers and obstacles to advancing further in their fields. The severity and prevalence of the COVID-19 pandemic both highlighted and exacerbated the unique challenges faced by female graduate students, postdocs, research staff, and principal investigators because of lockdowns, quarantines, school closures, lack of external childcare, and heightened family responsibilities, on top of professional responsibilities. This perspective provides recommendations of specific policies and practices that combat stigmas faced by women in STEM and can help them retain their careers. We discuss actions that can be taken to support women within academic institutions, journals, government/federal centers, university-level departments, and individual research groups. These recommendations are based on prior initiatives that have been successful in having a positive impact on gender equity─a central tenet of our postpandemic vision for the STEM workforce.

Primary school mathematics during the COVID-19 pandemic: No evidence of learning gaps in adaptive practicing results.

BACKGROUND: The COVID-19 pandemic induced many governments to close schools for months. Evidence so far suggests that learning has suffered as a result. Here, it is investigated whether forms of computer-assisted learning mitigated the decrements in learning observed during the lockdown. METHOD: Performance of 53,656 primary school students who used adaptive practicing software for mathematics was compared to performance of similar students in the preceding year. RESULTS: During the lockdown progress was faster than it had been the year before, contradicting results reported so far. These enhanced gains were correlated with increased use, and remained after the lockdown ended. This was the case for all grades but more so for lower grades and for weak students, but less so for students in schools with disadvantaged populations. CONCLUSIONS: These results suggest that adaptive practicing software may mitigate, or even reverse, the negative effects of school closures on mathematics learning.

Citizen Debates in Social Networks about Didactic Resources for Mathematics.

Citizens are increasingly turning to social media to open up debates on issues of utmost importance, such as health or education. When analyzing citizens' social media interactions on COVID-19, research has underlined the importance of sharing and spreading information based on scientific evidence rather than on fake news. However, whether and how citizens' interactions in the field of education, particularly in mathematics, are based on scientific evidence remains underexplored. To contribute to filling this gap, this article presents an analysis of citizen debates in social networks about didactic resources for mathematics. Through social media analytics, 136,964 posts were extracted from Reddit, Instagram, Twitter and Facebook, of which 1755 were analyzed. Results show that out of the 213 posts of citizen debates on didactic resources for mathematics, only two contained scientific evidence and eight claimed to contain scientific evidence. These findings highlight the importance of promoting actions to encourage citizen debates around didactic resources for mathematics based on scientific evidence.

An integrated model for interdisciplinary graduate education: Computation and mathematics for biological networks.

The current challenges at the forefront of data-enabled science and engineering require interdisciplinary solutions. Yet most traditional doctoral programs are not structured to support successful interdisciplinary research. Here we describe the design of and students' experiences in the COMBINE (Computation and Mathematics for Biological Networks) interdisciplinary graduate program at the University of Maryland. COMBINE focuses on the development and application of network science methods to biological systems for students from three primary domains: life sciences, computational/engineering sciences, and mathematical/physical sciences. The program integrates three established models (T-shaped, pi-shaped and shield-shaped) for interdisciplinary training. The program components largely fall into three categories: (1) core coursework that provides content expertise, communication, and technical skills, (2) discipline-bridging elective courses in the two COMBINE domains that complement the student's home domain, (3) broadening activities such as workshops, symposiums, and formal peer-mentoring groups. Beyond these components, the program builds community through both formal and informal networking and social events. In addition to the interactions with other program participants, students engage with faculty in several ways beyond the conventional adviser framework, such as the requirement to select a second out-of-field advisor, listening to guest speakers, and networking with faculty through workshops. We collected data through post-program surveys, interviews and focus groups with students, alumni and faculty advisors. Overall, COMBINE students and alumni reported feeling that the program components supported their growth in the three program objectives of Network Science & Interdisciplinarity, Communication, and Career Preparation, but also recommended ways to improve the program. The value of the program can be seen not only through the student reports, but also through the students' research products in network science which include multiple publications and presentations. We believe that COMBINE offers an effective model for integrated interdisciplinary training that can be readily applied in other fields.

Academic performance of K-12 students in an online-learning environment for mathematics increased during the shutdown of schools in wake of the COVID-19 pandemic.

The shutdown of schools in response to the rapid spread of COVID-19 poses risks to the education of young children, including a widening education gap. In the present article, we investigate how school closures in 2020 influenced the performance of German students in a curriculum-based online learning software for mathematics. We analyzed data from more than 2,500 K-12 students who computed over 124,000 mathematical problem sets before and during the shutdown, and found that students' performance increased during the shutdown of schools in 2020 relative to the year before. Our analyses also revealed that low-achieving students showed greater improvements in performance than high-achieving students, suggesting a narrowing gap in performance between low- and high-achieving students. We conclude that online learning environments may be effective in preventing educational losses associated with current and future shutdowns of schools.