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Students tend to avoid effective but effortful study strategies. One potential explanation could be that high-effort experiences may not give students an immediate feeling of learning, which may affect their perceptions of the strategy's effectiveness and their willingness to use it. In two experiments, we investigated the role of mental effort in students' considerations about a typically effortful and effective strategy (interleaved study) versus a typically less effortful and less effective strategy (blocked study), and investigated the effect of individual feedback about students' study experiences and learning outcomes on their considerations. Participants learned painting styles using both blocked and interleaved studying (within-subjects, Experiment 1, N = 150) or either blocked or interleaved studying (between-subjects, Experiment 2, N = 299), and reported their study experiences and considerations before, during, and after studying. Both experiments confirmed prior research that students reported higher effort investment and made lower judgments of learning during interleaved than during blocked studying. Furthermore, effort was negatively related to students' judgments of learning and (via these judgments) to the perceived effectiveness of the strategy and their willingness to use it. Interestingly, these relations were stronger in Experiment 1 than in Experiment 2, suggesting that effort might become a more influential cue when students can directly compare experiences with two strategies. Feedback positively affected students' considerations about interleaved studying, yet not to the extent that they considered it more effective and desirable than blocked studying. Our results provide evidence that students use effort as a cue for their study strategy decisions.

Vertical profiles of atmospheric pollutants, acquired by unmanned aerial vehicles (UAVs, known as drones), represent a new type of observation that can help to fill the existing observation gap in the planetary boundary layer. In this article, the first study of assimilating air pollutant observations from drones is presented to evaluate the impact on local air quality analysis. The study uses the high-resolution air quality model EURAD-IM (EURopean Air pollution Dispersion – Inverse Model), including the four-dimensional variational data assimilation system (4D-var), to perform the assimilation of ozone (O3) and nitrogen oxide (NO) vertical profiles. 4D-var takes advantage of the inverse technique and allows for simultaneous adjustments of initial values and emissions rates. The drone data was collected during the MesSBAR (Automatisierte luftgestützte Mes sung der S chadstoff B elastung in der erdnahen A tmosphäre in urbanen R äumen / Automated airborne measurement of air pollution levels in the near earth atmosphere in urban areas) field campaign, which was conducted on 22–23 September 2021 in Wesseling, Germany. The two-day analyses reveal that the 4D-var assimilation of high-resolution drone measurements has a beneficial impact on the representation of regional air quality in the model. On both days, a significant improvement in the vertical distribution of O3 and NO is noticed in the analysis compared to the reference simulation without data assimilation. Moreover, the validation against independent observations shows an overall improvement in the bias, root-mean-square error, and correlation for O3, NO, and NO2 (nitrogen dioxide) ground concentrations at the measurement site as well as in the surrounding region. Furthermore, the assimilation allows for the deduction of emission correction factors in the grid cells surrounding the measurement site, which significantly contribute to the observed improvement in the analysis. [ABSTRACT FROM AUTHOR]