Multiplayer Serious Games Supporting Programming Learning

Computational thinking (CT) is crucial in education for providing a multifaceted approach to problem-solving. However, challenges exist such as supporting teachers' knowledge of CT and students' desire to learn it, particularly for non-technical students. To combat these challenges, Computer Supported Collaborative Learning (CSCL) has been introduced in classrooms and implemented using a variety of technologies, including serious games, which have been adopted across several domains aiming to appeal to various demographics and skill levels. This research focuses on a Collaborative Multiplayer Serious Game (MSG) for CT skill training. The architecture is aimed at young students and is designed to aid in the learning of programming and the development of CT skills. The purpose of this research is to conduct an empirical study to assess the multiplayer game gameplay mechanics for collaborative CT learning. The proposed game leverages a card game structure and contains complex multi-team multi-player processes, allowing students to communicate and absorb sequential and conditional logics as well as graph routing in a 2D environment. A preliminary experiment was conducted with four fourth-graders and eight sixth-graders from a French school in Morocco who have varying levels of understanding of CT. Participants were split into three groups each with two teams and were required to complete a 16-question multiple-choice quiz before and after playing the same game to assess their initial structural programming logics and the effectiveness of the MSG. Questionnaires were collected along with an interview to gather feedback on their gaming experiences and the game’s role in teaching and learning. The results demonstrate that the proposed MSG had a favourable effect on the participants’ test scores as the scores of 4 of the teams increased and 1 remained the same. All students performed well on the sequential and conditional logics, which was significantly better than the achievement of the Bebras test of the graph routing. Furthermore, according to the participants, the game provides an appealing environment that allows players to immerse themselves in the game and the competitive aspect of the game adds to its appeal and helps develop teamwork, coordination, and communication skills

Concurrent and lagged effects of drought on grassland net primary productivity: a case study in Xinjiang, China

Xinjiang grasslands play a crucial role in regulating the regional carbon cycle and maintaining ecosystem stability, and grassland net primary productivity (NPP) is highly vulnerable to drought. Drought events are frequent in Xinjiang due to the impact of global warming. However, there is a lack of more systematic research results on how Xinjiang grassland NPP responds to drought and how its heterogeneity is characterized. In this study, the CASA (Carnegie Ames Stanford Application) model was used to simulate the 1982–2020 grassland NPP in Xinjiang, and the standardized Precipitation Evapotranspiration Index (SPEI) was calculated using meteorological station data to characterize drought. The spatial and temporal variability of NPP and drought in Xinjiang grasslands from 1982 to 2020 were analyzed by the Sen trend method and the Mann-Kendall test, and the response characteristics of NPP to drought in Xinjiang grasslands were investigated by the correlation analysis method. The results showed that (1) the overall trend of NPP in Xinjiang grassland was increasing, and its value was growing season > summer > spring > autumn. Mild drought occurred most frequently in the growing season and autumn, and moderate drought occurred most frequently in spring. (2) A total of 64.63% of grassland NPP had a mainly concurrent effect on drought, and these grasslands were primarily located in the northern region of Xinjiang. The concurrent effect of drought on NPP was strongest in plain grassland and weakest in alpine subalpine grassland. (3) The lagged effect is mainly in the southern grasslands, the NPP of alpine subalpine meadows, meadows, and alpine subalpine grasslands showed mainly a 1-month time lag effect to drought, and desert grassland NPP showed mainly a 3-month time lag effect to drought. This research can contribute to a reliable theoretical basis for regional sustainable development

Nutrient addition affects leaf N-P scaling relationship in Arabidopsis thaliana

Ambient nutrient changes influence the coupling of nitrogen (N) and phosphorus (P) in terrestrial ecosystems, but whether it could alter the scaling relationship of plant leaf N to P concentrations remains unclear. Moreover, knowledge about how multi-elemental stoichiometry responds to varying N and P availabilities remains limited. Here we conducted experimental manipulations using Arabidopsis thaliana, with five N and P addition levels and nine repeated experiments. We found that the scaling exponent of leaf N to P concentrations decreased with increasing N levels, but increased with increasing P levels. This suggests that high nutrient availability decreases the variability of its own concentration, but promotes the fluctuation in another tightly associated nutrient concentration in leaves among plant individuals. We call this as Nutrient Availability–Individual Variability Hypothesis. In addition, N and P supply exerted differential influences on the concentrations of multi-elements in leaves. Compared with the green-leaves, the senesced-leaves had higher variability of C, N, P, K and Mg concentrations but lower variability of Ca concentration under varying nutrient availabilities. This suggests that stage-dependent pattern of leaf stoichiometric homeostasis relies on the type of elements, and the elemental feature should be considered when choosing a more favorable tissue in plants for diagnosing the nutrient availability in ambient environments. These findings provide a novel mechanism for understanding the dynamic processes of population structure and functioning under global nutrient changes, which should be incorporated into modeling stoichiometric growth in terrestrial ecosystems. Furthermore, our study can advance the holistic understanding about plant eco-physiological response and adaption under global nutrient changes from the stoichiometric perspective of multiple elements beyond N and P

Understanding the role of metakaolin towards mitigating the shrinkage behavior of alkali-activated slag

This research investigates the mechanism of metakaolin for mitigating the autogenous and drying shrinkages of alkali-activated slag with regard to the activator parameters, including concentration and modulus. The results indicate that the incorporation of metakaolin can decrease the initial viscosity and setting time. Increasing activator concentration can promote the reaction process and shorten the setting time. An increase in the metakaolin content induces a decrease in compressive strength due to reduced formation of reaction products. However, increasing activator dosage and modulus can improve the compressive strength of alkali-activated slag containing 30% metakaolin. The inclusion of metakaolin can mitigate the autogenous and drying shrinkage of alkali-activated slag by coarsening the pore structure. On the other hand, increases in activator concentration and modulus result in an increase in magnitude of the autogenous and drying shrinkage of alkali-activated slag containing metakaolin. The influence of the activator modulus on the shrinkage behavior of alkali-activated slag-metakaolin binary system should be further investigated

Phosphorus accumulates faster than nitrogen globally in freshwater ecosystems under anthropogenic impacts

Combined effects of cumulative nutrient inputs and biogeochemical processes that occur in freshwater under anthropogenic eutrophication could lead to myriad shifts in nitrogen (N):phosphorus (P) stoichiometry in global freshwater ecosystems, but this is not yet well-assessed. Here we evaluated the characteristics of N and P stoichiometries in bodies of freshwater and their herbaceous macrophytes across human-impact levels, regions and periods. Freshwater and its macrophytes had higher N and P concentrations and lower N : P ratios in heavily than lightly human-impacted environments, further evidenced by spatiotemporal comparisons across eutrophication gradients. N and P concentrations in freshwater ecosystems were positively correlated and N : P was negatively correlated with population density in China. These results indicate a faster accumulation of P than N in human-impacted freshwater ecosystems, which could have large effects on the trophic webs and biogeochemical cycles of estuaries and coastal areas by freshwater loadings, and reinforce the importance of rehabilitating these ecosystems

High speed self-testing quantum random number generation without detection loophole

Quantum mechanics provides means of generating genuine randomness that is impossible with deterministic classical processes. Remarkably, the unpredictability of randomness can be certified in a self-testing manner that is independent of implementation devices. Here, we present an experimental demonstration of self-testing quantum random number generation based on an detection-loophole free Bell test with entangled photons. In the randomness analysis, without the assumption of independent identical distribution, we consider the worst case scenario that the adversary launches the most powerful attacks against quantum adversary. After considering statistical fluctuations and applying an 80 Gb $\times$ 45.6 Mb Toeplitz matrix hashing, we achieve a final random bit rate of 114 bits/s, with a failure probability less than $10^{-5}$. Such self-testing random number generators mark a critical step towards realistic applications in cryptography and fundamental physics tests.Comment: 34 pages, 10 figure

Field demonstration of distributed quantum sensing without post-selection

Distributed quantum sensing can provide quantum-enhanced sensitivity beyond the shot-noise limit (SNL) for sensing spatially distributed parameters. To date, distributed quantum sensing experiments have been mostly accomplished in laboratory environments without a real space separation for the sensors. In addition, the post-selection is normally assumed to demonstrate the sensitivity advantage over the SNL. Here, we demonstrate distributed quantum sensing in field and show the unconditional violation (without post-selection) of SNL up to 0.916 dB for the field distance of 240 m. The achievement is based on a loophole free Bell test setup with entangled photon pairs at the averaged heralding efficiency of 73.88%. Moreover, to test quantum sensing in real life, we demonstrate the experiment for long distances (with 10-km fiber) together with the sensing of a completely random and unknown parameter. The results represent an important step towards a practical quantum sensing network for widespread applications.Comment: 8 pages, 5 figure