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Game-based learning shows great potential as a tool for enhancing students’ computational thinking abilities. However, these approaches in K-12 settings frequently emphasize the teaching of specific computing concepts and programming skills. This approach often overlooks the broader goal of developing students’ computational thinking competency—a set of skills that can be applied across various subjects and aligns with curriculum standards. To address this need, the current study investigated how game-based learning influenced middle school students’ learning performance. One hundred sixty-nine students participated in the study, playing the game over a period of 4 weeks. We observed evidence that the gaming experience significantly influenced the development of computational thinking competency, self-efficacy toward computational thinking, and interest in STEM career after gameplay. 

The current in-situ, descriptive case study demonstrated how we involved in-service teachers as informants in designing an educational game to enhance middle school students’ computational thinking through participatory design. Data were collected from eight in-service teachers at middle schools through individual interviews, focus groups, and field notes. The study results indicated that in-service teachers made 82% of contributions to the Learning facet, followed by 14% of the Gameplay facet, at the early stage of conceptualization. Additionally, participants provided insights on intrinsically embedding content in game design processes by offering valuable and relevant pedagogical content knowledge, including knowledge of content and students, knowledge of content and teaching, and knowledge of content and curriculum. 

For atmospheric turbulence, multiplying an estimate of the convection velocity with the integral time scale is useful for estimating the integral length scale. Velocity scales that have been used to estimate the convection velocity include the local mean velocity, the ratio of $$e$$-folding length and time scales, and the ratio of a prescribed spatial separation and the time lag at which the space-time autocorrelation peaks. A knowledge gap is the lack of evaluation of these velocity scales directly against the convection velocity, especially for canopy flows where previous studies have reported somewhat inconsistent results. The objective of this work is to assess the ability of each candidate velocity scale to estimate the convection velocity in canopy flows. Firstly, large-eddy simulation (LES) results of neutral canopy flows are used to compare these velocity scales to directly quantified convection velocity. When the direction of interest roughly aligns with the mean pressure gradient force (specifically, for an angle of $$7.5^\circ$$ or smaller), all candidate velocity scales other than the local mean wind component approximate the convection velocity fairly well. When the direction of interest departs from the mean pressure gradient force for more than $$15^\circ$$, the ability of each velocity scale to approximate the convection velocity changes substantially. Secondly, data collected during the Canopy Horizontal Array Turbulence Study (CHATS) are used as an example of interpreting estimates of the convection velocity in the field with the guidance from LES findings. Because observational periods are never perfectly neutral, the guidance does not involve direct comparison between observed and simulated velocity scales, but focuses on uncertainties of velocity scale estimates and potential caution needed when using these estimates. 

Horizontal convective rolls (HCRs) are elongated, counter-rotating, mixed-layer circulations in the atmospheric boundary layer (ABL). Accurately quantifying their orientation and cross-roll wavelength is essential for evaluating simulations against observations, examining theoretical models, and improving ABL parameterizations. This study evaluates and combines statistical methods for estimating HCR properties from large-eddy simulation (LES) results. Three statistical methods are considered: i) the primary mode of two-dimensional (2D) Fourier analysis, ii) the volume flux ratio (VFR), which is a simplified version of the mass flux ratio (MFR), and iii) the autocorrelation contours, with a new automated process developed. These methods are applied to two LES cases: i) updraft bands with known orientation and cross-roll wavelength enforced by heterogeneous surface heating, and ii) classic narrow-mode HCRs over a homogeneous surface. Results recommend using the VFR to obtain HCR orientation and then taking this orientation estimate as input to the new automated process of analyzing autocorrelation contours to obtain cross-roll wavelength. This combination of VFR and autocorrelation contours can be readily adopted for analyzing field observations like radar scans. If a consistent wavelength is obtained using the primary mode of 2D Fourier analysis, then the orientation suggested by the 2D Fourier analysis can be compared to that obtained using VFR for cross-validation purposes. 

This flux-tower observational campaign occurred in Utqiagvik, AK. A 12-m tower was installed in February 2022 to collect turbulence data at a total of five heights (0.5 m, 1.5 m, 2.5 m, 3.5 m, and 7.5 m). At each height, a Campbell Scientific CSAT3B sonic anemometer was operated to measure three velocity components and virtual temperature at 50 Hz, and an R. M. Young temperature and relative sensor was operated to measure air temperature and relative humidity at 1 Hz. The effective data collection was during March--April 2022, until the tower was taken down in April 2022. This was the first dataset of Arctic turbulence collected at 50 Hz, a frequency substantially higher than previous measurements at 10 Hz and 20 Hz. Given the strongly stable conditions in the Arctic, increasing the sampling frequency to 50 Hz was critical to resolve near-surface turbulence within or at least close to the inertial subrange. 

This study explored how participants practice computational thinking (CT) concepts and skills while playing the game. Regarding 11 learning standards from the Computer Science Teacher Association (CSTA), researchers designed gameplay tasks in Minecraft and a supplemental platform called Minecraft Factory Planner (MFP). Data was collected through the cognitive walkthrough with a think-aloud method and semi-structured retrospective interview. The results showed that different game tasks triggered gameplay actions that allowed the practice of different CT skills. 

Large-eddy simulation (LES) runs are performed to understand the influence of a one-dimensional (1D) surface heating heterogeneity on organized vertical motions within and above the atmospheric boundary layer (ABL). Two knowledge gaps are of particular interest: i) how do updrafts develop in the low free troposphere, and ii) what parameters control the updraft location and strength within the ABL? LES runs are performed for a shear-influenced, unstable ABL driven by geostrophic winds of the same magnitude but in various directions relative to a prescribed 1D surface-heat-flux heterogeneity. Quasi-steady-state LES results are phase-averaged over time and the horizontal dimension perpendicular to the surface-heat-flux gradient to quantify secondary circulations. Regarding the first knowledge gap, results show that organized vertical motions in the low free troposphere can be modeled as two-dimensional (2D) stationary gravity waves, whose amplitudes depend on ABL updraft strength and instability development within the free troposphere. Regarding the second knowledge gap, results show that organized updrafts within the ABL may form either above relatively warm surfaces or downwind of warm-to-cool transitions. These different locations are well explained by both the relative contributions to secondary circulations from phase-averaged horizontal and vertical velocity fluctuations and the relative importance of horizontal advection and turbulent transport in the phase-averaged internal energy fluctuation equation. The main balances associated with each updraft location are used to propose empirical models of updraft strength, and it is shown that the presence of sufficiently strong organized vertical motions can cause a non-negligible reduction in near-surface eddy viscosity. 

Understanding the interactions between turbulent and non-turbulent motions has been a persistent challenge faced by the community studying stably stratified turbulent flows. For flows with high Reynolds number, high Rossby number, and stable stratifications, non-turbulent motions share a common characteristic to involve physical mechanisms acting against instability development. Because turbulence is generated through energy cascade via instability development, the presence of non-turbulent motions is expected to modify the energy distribution across scales compared to that of solely turbulent motions. The objective of this work is to identify statistical signals of non-turbulent motions caused by stable stratification. The need to resolve energy-containing motions in both space and time requires high-frequency time series of velocity fluctuations collected using arrays of sonic anemometers. The analysis is performed using data from the Canopy Horizontal Array Turbulence Study (CHATS), during which a total of 31 sonic anemometers were deployed on a horizontal array and on a 30-m tower. Compared to other field campaigns which were also equipped with arrays of sonic anemometers, CHATS took an important advantage of already published nighttime canopy-scale waves derived from aerosol backscatter lidar images. After precluding complexities caused by nonstationarity and horizontal heterogeneity, signals of non-turbulent motions caused by stable stratification are identified from spatial autocorrelations of time-block-averaged velocity fluctuations. These signals agree with existing understanding of turbulent canopy flows and two-dimensional Kelvin-Helmholtz instability development, which predicts a critical wavelength at which motions shift from free instability growth to internal gravity waves. The estimates of critical wavelengths and buoyancy periods agree well with the overall properties of nighttime canopy-scale waves derived from lidar images. 

The current in-situ, descriptive case study explored in-service teachers’ contributions and perspectives in the participatory design of an educational game for enhancing middle school students’ computational thinking skills. The informant design technique was adopted, involving specific stakeholders at the stage of conceptualization. Data were collected from 8 in-service teachers at 9 middle schools through observation, a series of individual interviews, and focus-group interviews. The study results indicated that in-service teachers made contributions to the content design at the stage of conceptualization.