ABSTRACT
To facilitate people using mathematical reasoning to compare risks associated with the COVID-19 pandemic, the National Science Foundation (NSF) funded the COViD-TASER (Creation of Visualizations of Data: The Application of STEM Education Research) research team to create the COVID-19 Relative Risk Tool (RRT). The RRT uses an interactive bar chart to display COVID-19 infection and vaccination risks alongside more familiar risks like driving, contracting breast cancer, playing soccer, and skydiving. To involve students, the authors developed and tested elementary, middle, and high school lesson plans that use the RRT. Each lesson is aligned with the Common Core State Standards for Mathematics (CCSSM, NGA Center and CCSSO 2010) for both content and mathematical practice, and each plan pursues two goals: (1) making comparisons of relative size of quantities, and (2) interpreting these relative sizes to understand COVID-19 data. For teachers who wish to incorporate more real-world contexts in the mathematics classroom and are unsure of how to start, the authors hope that their structured, pretested lessons plans provide a starting place for to help students make connections between the classroom and their everyday lives.
ABSTRACT
The present research aimed to reveal how the COVID-19 pandemic influenced the mathematical reasoning of primary school students through mediation analysis. It was designed as ex post facto research. The research sample consisted of two cohorts. Cohort 1 included 415 primary school children who received face-to-face instruction by attending school for six months until COVID-19 emerged. Cohort 2 included 964 children who were taught curricular skills through distance education due to COVID-19 and school closures. In total, 1,379 primary school children were recruited into the research sample. Data were collected through a mathematical reasoning test by sending items from the instrument via Google Docs. The data were analysed with mediation analysis. Results demonstrated that the school closures due to the COVID-19 pandemic negatively influenced mathematical reasoning skills. Findings are discussed in the light of human interaction and Cattell's intelligence theory.
ABSTRACT
This article describes the development and assessment of RaspyLab which is a low-cost Remote Laboratory (RL) to learn and teach programming with Raspberry Pi and Python language. The RL is composed of 16 stations or nodes that contain hardware components such as display LCD, robotic arm, temperature sensor, among others, and two modes of programming (graphical and text-based) for the students to experiment with their designed algorithms. The concept of the RL was conceived as a pedagogical tool to support the students of Engineering and Computer Science (CS) in an online learning format, given the context of the COVID-19 pandemic. The laboratory has been used by ([Formula Omitted]) CS students during the second semester of 2020 in the subject of mathematical logic through the methodology of Problem-Based Learning (PBL). To evaluate preliminary the laboratory, it was used a survey with 3 open-ended questions and 12 closed-ended questions on a Likert scale according to the Technology Acceptance Model (TAM). The outcomes show a good reception of the laboratory, an enhancement of the students’ learning regarding the concepts addressed in the course, and an interest of the students for the laboratory to be included in other subjects of the curricula.