A modified high-pressure, stopped-flow apparatus has been developed to enable kinetic experiments to be monitored spectrophotometrically to 200 MPa, with efficient mixing of the reactant solutions. This apparatus is compact, relatively inexpensive to construct, and the solutions are only exposed to inert materials, such as Kel-F, Teflon, quartz (low-pressure windows), and glass or Viton. The drive-syringe pistons are propelled by a step motor housed on top of the stopped-flow unit inside the pressure vessel, resulting in a dead time for the system of ∼10 ms at 25 °C.

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.

The construction of a compact, transportable, and multipurpose high-pressure unit consisting of a pressure generating system and a four-window optical UV–VIS high-pressure cell for spectroscopic measurements at pressures up to 200 MPa is described. The pressure generating system can be operated with a wide range of liquids suitable as pressurizing medium. The optical cell can be used for spectroscopic and kinetic (flash photolysis and laser induced T-jump) measurements.

Humans adjust their behavior after they have committed an error, but it is unclear whether and how error commissions influence voluntary task choices. In the present article, we review different accounts on effects of errors in the previous trial (transient error effects) and overall error probabilities (sustained error effects) on behavioral adaptation. Based on this review, we derived five statistical models of how errors might influence voluntary task choices. We analyzed the data of three experiments in which participants voluntarily selected one of two tasks before each trial whereby task difficulty, and concomitantly error probability, increased successively for the selected/performed tasks. Model comparison suggested that choice behavior was best explained by a combination of error probability of the performed task, error probability of the alternative task, and whether the previous response was correct or incorrect. The results revealed that participants were most likely to switch tasks in situations where the error probability of the performed task was high, the error probability of the alternative task was low, and after an error on the previous trial. We conclude that task selection processes are influenced by transient and sustained error effects. Public Significance StatementHumans are constantly faced with the decision to keep engaged with their current task or to do something else. This research project asked to what extent errors influence this voluntary decision. Results provide evidence that the decision to switch to an alternative task depends not only on the accuracy of the previous trial, but also on the overall error history (i.e., the error probability) of the performed task, and the alternative task. These results extend a large body of literature on error processing in single tasking to situations with multiple tasks available.

Decades of research produced inconsistent findings on whether study time can lead to achievement gains in mathematics. Data generated by more than six thousand students from three different countries who solved more than 1.1 million problem sets using a dedicated mathematics software are analyzed regarding the effect of study time on students’ achievements in mathematics. Results showed that more study time led to higher performance scores in mathematics. Further analyses revealed that low-performing students in the first school year (2017-2018) who increased their study time in the following year (2018-2019) revealed greatest gains in performance in the same school year (2018-2019) and even in the year after (2019-2020). Finally, results replicated previous observations of robust performance scores within students over the three school years, with performance scores in 2017-2018 predicting those of 2018-2019 which predicted those of 2019-2020. These results support the idea that students, in particular low-performing students, can boost their academic abilities to upper levels when increasing their study time.