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关键词： 数据驱动   初中英语   “教学评”一体化   教学模式  

摘要： 在深化新时代教育评价改革背景下，为更好地适应个性化和精准化教学的需求，南宁市龙堤路初级中学创造性地构建了“1+5”数据驱动的“教学评”一体化应用模式，即以数据驱动为内核，分别对应学、教、考、管、评五个方面。以外研版八年级英语上册Unit 6 “I’m going to study computer science”为例，“1+5”数据驱动的“教学评”一体化应用模式具体实践如下：学方面，构建个性化的自主学习环境；教方面，创新教学模式，由经验教学向精准教学转变；考方面，建设优质校本资源库，创新资源应用服务体系；管方面，改变教学管理方式，提升教学管理能力；评方面，构建数字化多维评价方式。

关键词： Education   Data mining   Training   Computer science   Planning   Market research   Learning management systems   Interviews   Focusing   Conferences   Higher education   evaluation tool   computer science   data mining  

摘要： This work introduces an innovative teaching methodology based on microcompetences applied in a higher education context. The intervention involved creating a repository of practical case studies in the form of quizzes and integrating microcompetences into each course activity. The digital tool Sapiens was used to identify learning deficiencies and provide both collective and individualized feedback. The results indicate a significant increase in student participation and academic performance compared to previous years. Furthermore, students voluntarily used virtual teaching modalities to reinforce their knowledge, particularly in more complex areas. Data mining techniques identified performance patterns among students, highlighting the methodology's effectiveness in improving both transversal and specific competences. The study's findings underscore the importance of implementing microcompetency-based methodologies in higher education to enhance the quality of learning and continuous assessment. This approach not only facilitated a deeper understanding of course content but also promoted critical thinking, abstract reasoning, and interpersonal skills, preparing students for future academic and professional challenges. Additionally, the flexibility and adaptability of the digital tools used provided a seamless transition across different teaching modalities, such as in-person, hybrid, and online formats. Thus, the implementation of this innovative methodology has demonstrated its potential to significantly improve student engagement, participation, and academic success, thereby contributing to a more effective and comprehensive educational experience in higher education.

关键词： Python  

摘要： Computer science research has grown increasingly diverse, with authors investigating a broad spectrum of topics. This paper analyzes the self-reported research interests of the top 3,260 most cited computer science scholars, according to Google Scholar. By leveraging the scholarly Python library, we systematically retrieved and classified each researcher’s interests into predefined categories grounded in the Computer Science Ontology (CSO). Our results reveal a clear hierarchy of primary focus areas such as Artificial Intelligence, Software Engineering, Data Mining, and Computer Systems. We further examine how these interests are distributed, shedding light on which fields are emerging as popular, which are well-established, and which receive comparatively less attention. These findings provide an up-to-date snapshot of key research trends and lay the groundwork for guiding future studies in computer science. © 2024, CC BY.

关键词： Computer science education   Personalization game feature   Engagement   Flow  

摘要： Extensive studies have been conducted to examine the effectiveness of the personalized games on students' engagement and flow. However, engagement and flow were examined separately rather than concurrently in previous studies. In fact, engagement and flow are two interrelated entities and share similarities but the occurrence differs. How the interrelationship between engagement and flow impacts student learning in the personalized gaming environment has been seldomly investigated. Aiming to fill this gap, this study examined the impact of personalization on student engagement and flow concurrently within a gaming environment. The results showed that personalization had a significant impact on students' engagement, specifically students' focused attention. However, a significant difference in flow was not observed. Flow (primarily concentration, autotelic experience, and loss of self-consciousness) exhibited a strong correlation with engagement (primarily focused attention). The findings indicated that the personalization game feature could be used to engage students but needs to incorporate additional non-game features, such as instructional features, to promote the flow.

关键词： Sustainability   Solar stills   Computer science   Solar energy   XGBoost  

摘要： The increasing demand for clean water necessitates innovative approaches to optimize water productivity through renewable energy systems. This study harnessed computer science-based algorithm to forecast the productivity of hemispherical solar stills (HSS) enhanced by various sand beds, reflectors, and a vapor extraction fan using XGBoost analysis. Initially explored was the effect of different sand types and bed heights on HSS performance, with the findings indicating that black sand, especially at a height of 1 cm combined with reflectors and a fan, markedly improved efficiency and production. An economic analysis revealed a significant reduction in water treatment costs with the optimized system. The current work extends these experimental insights through XG-Boost to predict productivity, employing evaluation metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Coefficient of Variation of the Root Mean Squared Error (CVRMSE), and the determination coefficient (R2), with resulted values denoted as 0.43708%, 0.95879%, 0.2780%, 0.05290%, 12.2078%, and 0.88144% respectively. This approach significantly advances the predictability and efficiency of solar distillation systems by pressing global challenges of water scarcity and sustainability and the use of solar energy.

关键词： Applied sciences   Computer science   Software engineering  

摘要： Volumetric layouts of data are becoming increasingly common in a number of fields. Visualizing these data often requires downloading a large suite of dedicated tools with a significant learning curve. This process can be overwhelming for students or new researchers looking to quickly visualize and showcase a volumetric dataset. QuickVol was developed as a system to allow for rapid viewing of volumetric data without requiring extra setup. Built on WebGL, our system can run on any modern web browser, including mobile browsers, and can work completely offline. Additionally, an experimental immersive hand-tracking feature is included, which allows for hands-free manipulation of the imported volume, along with a showcase mode for viewing with a virtual reality headset.

关键词： Biological sciences   Computer science   Natural sciences  

摘要： The Bruton tyrosine kinase inhibitor ibrutinib is an effective treatment for patients with chronic lymphocytic leukemia (CLL). While it rapidly reduces lymph node and spleen size, it initially increases the number of lymphocytes in the blood due to cell redistribution. A previously published mathematical model described and quantified those cell kinetics. Here, we propose an alternative mechanistic model that outperforms the previous model in 26 of 29 patients. Our model introduces constant subcompartments for healthy lymphocytes and benign tissue and treats spleen and lymph nodes as separate compartments. This three-compartment model (comprising blood, spleen, and lymph nodes) performed significantly better in patients without a mutation in the IGHV gene, indicating a diverse response to ibrutinib for cells residing in lymph nodes and spleen. Additionally, high ZAP-70 expression was linked to less cell death in the spleen. Overall, our study enhances understanding of CLL genetics and patient response to ibrutinib and provides a framework applicable to the study of similar drugs.

关键词： Computer science   Engineering   Energy systems  

摘要： Global warming concerns have led to emission regulations and various incentives for low-carbon technologies. Energy system models, which are used to examine how investments affect our ability to meet energy demand, are typically based on two assumptions: key parameters are assumed to be known deterministically and a multi-period energy transition plan is determined at one point in time. We argue that for a systematic generation and analysis of energy transition pathways, these assumptions should be relaxed and, accordingly, we propose methods to achieve that. First, we use stochastic programming (SP) to account for uncertainty in key parameters. Second, we pair SP with a sequential decision-making approach that represents how decisions can be updated as uncertainties unfold. Third, we use simulation-based methods to evaluate the quality of energy transitions. Importantly, we find that accounting for uncertainty, proactively and through feedback, yields pathways with diverse technology portfolios that are resilient to uncertainty.

关键词： Applied sciences   Computer science   Engineering  

摘要： Advancements in noninvasive surface and internal imaging techniques, along with computational methods, have revolutionized 3D visualization of organismal morphology-enhancing research, medical anatomical analysis, and facilitating the preservation and digital archiving of scientific specimens. We introduce the SmARTR pipeline (Small Animal Realistic Three-dimensional Rendering), a comprehensive workflow integrating wet lab procedures, 3D data acquisition, and processing to produce photorealistic scientific data through 3D cinematic rendering. This versatile pipeline supports multiscale visualizations-from tissue-level to whole-organism details across diverse living organisms-and is adaptable to various imaging sources. Its modular design and customizable rendering scenarios, enabled by the global illumination modeling and programming modules available in the free MeVisLab software and seamlessly integrated into detailed SmARTR networks, make it a powerful tool for 3D data analysis. Accessible to a broad audience, the SmARTR pipeline serves as a valuable resource across multiple life science research fields and for education, diagnosis, outreach, and artistic endeavors.

关键词： Computer science   Computational mathematics   Artificial intelligence  

摘要： Neighborhood rough set (NRS) have been successfully applied to attribute reduction (AR). However, most current methods of AR based on NRS are supervised or semi-supervised. This limits their ability to process data without decision information. When granulating data samples, NRS considers only the number of samples within the neighborhood radius. It does not consider distribution information between samples, which can result in the loss of original data information. To address the aforementioned issue, we propose an unsupervised attribute reduction (UAR) strategy based on variable precision weighted neighborhood dependency (VPWND) (UAR_VPWND). We compare algorithm UAR_VPWND to existing classical UAR algorithms using public datasets. The experimental results show that algorithm UAR_VPWND can select fewer attributes to maintain or improve the performance of clustering learning algorithms.