During the early months of the COVID-19 pandemic, there was an unusually high submission rate of scholarly articles. Given that most academics were forced to work from home, the competing demands for familial duties may have penalized the scientific productivity of women. To test this hypothesis, we looked at submitted manuscripts and peer review activities for all Elsevier journals between February and May 2018-2020, including data on over 5 million authors and referees. Results showed that during the first wave of the pandemic, women submitted proportionally fewer manuscripts than men. This deficit was especially pronounced among more junior cohorts of women academics. The rate of the peer-review invitation acceptance showed a less pronounced gender pattern with women taking on a greater service responsibility for journals, except for health & medicine, the field where the impact of COVID-19 research has been more prominent. Our findings suggest that the first wave of the pandemic has created potentially cumulative advantages for men.

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Science, Technology, Engineering, and Mathematics (STEM) are key disciplines towards tackling the challenges related to the Sustainable Development Goals. However, evidence shows that women are enrolling in these disciplines in a smaller percentage than men, especially in Engineering related fields. As stated by the United Nations Women section, increasing the number of women studying and working in STEM fields is fundamental towards achieving better solutions to the global challenges, since the potential for innovation is larger. In this paper, we present the Girls4STEM project, which started in 2019 at the Escola Tècnica Superior d’Enginyeria de la Universitat de València, Spain. This project works towards breaking the stereotypes linked to STEM fields, addressing both boys and girls aged from 6 to 18, but especially trying to open the range of career options for young girls through interaction with female STEM experts. The goal is to spark girls’ interest in STEM disciplines from childhood, so that they become more self-confident in these areas. To achieve this goal, the project is built over three main actions: the Girls4STEM Family Talks, where students, families, and teachers participate; the Girls4STEM Professional Talks, where the target is a general audience; and the Initial Training Seminars for teachers. Short-term results are here presented, showing that aspects related to self-perception and perception from others (family, teachers) play a significant role. Moreover, these results also indicate that there may not be a general understanding of which disciplines are included in STEM.

Peer review is often criticized for being flawed, subjective and biased, but research into peer review has been hindered by a lack of access to peer review reports. Here we report the results of a study in which text-analysis software was used to determine the linguistic characteristics of 472,449 peer review reports. A range of characteristics (including analytical tone, authenticity, clout, three measures of sentiment, and morality) were studied as a function of reviewer recommendation, area of research, type of peer review and reviewer gender. We found that reviewer recommendation had the biggest impact on the linguistic characteristics of reports, and that area of research, type of peer review and reviewer gender had little or no impact. The lack of influence of research area, type of review or reviewer gender on the linguistic characteristics is a sign of the robustness of peer review.

Numerous studies have addressed the relationship between performance in mathematics problem-solving and reading comprehension in students of all educational levels. This work presents a new proposal to measure the complexity of arithmetic word problems through the student reading comprehension of the problem statement and the use of learning analytics. The procedure to quantify this reading comprehension comprises two phases: (a) the division of the statement into propositions and (b) the computation of the time dedicated to read each proposition through a technological environment that records the interactions of the students while solving the problem. We validated our approach by selecting a collection of problems containing mathematical concepts related to fractions and their different meanings, such as fractional numbers over a natural number, basic mathematical operations with a natural whole or fractional whole and the fraction as an operator. The main results indicate that a student’s reading time is an excellent proxy to determine the complexity of both propositions and the complete statement. Finally, we used this time to build a logistic regression model that predicts the success of students in solving arithmetic word problems.