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关键词： Resilience   Competences   Junior doctors   COVID-19  

摘要： BackgroundAt the onset of the COVID-19 pandemic, strict measures suspended face-to-face teaching at German universities, posing significant challenges for medical education. Practical, patient-centered training couldn't be fully replaced by online formats, leading to skill deficits and increased stress among students. To date, no study has examined the impact of COVID-19 on the resilience and the competence of medical graduates so far. This study aims to address this knowledge gap by investigating the pandemic impact on resilience, medical competence, communication skills, and research competence of medical *** study employed data from the "Bavarian Graduate Study of Medicine" (MediBAS), a cross-sectional evaluation survey conducted in cooperation with Bavarian universities and the Bavarian Institute for higher education research and planning. It targeted medical, dental, and veterinary graduates. The data were collected in two waves (2018/19 and 2022/23), with 1.114 human medicine graduates participating. The questionnaire assessed among others resilience, medical expertise, communication skills, and research competence. Statistical analysis involved descriptive statistics, correlation analysis, and Mann-Whitney-U tests due to non-normal data *** study analyzed self-assessed resilience, medical expertise, communication, and research skills of medical graduates from two waves. The findings demonstrated through descriptive statistics a decline in all competencies except research skills, which exhibited an increase. Correlation analysis revealed significant relationships between variables. Mann-Whitney-U tests revealed no significant differences between the waves in resilience (p =.079, r =.06), medical expertise (p =.117, r =.05), communication skills (p =.053, r =.07), or research competence (p =.106, r =.05).ConclusionThe study examined the impact of COVID-19 on medical graduates' resilience, medical expertise, communication ski

关键词： Machine learning   Computer science  

摘要： Government policies, generous funding and a pipeline of AI graduates have helped Chinese firms create advanced LLMs.

关键词： Students  

摘要： High-quality computer science (CS) instruction is essential for preparingstudents to thrive in an increasingly technology-driven world. This researchbrief presents findings from a six-year longitudinal study of CS enrollments inseven public high schools from the 2018-2019 through the 2023-2024 academicyears, drawing on the administrative data of over 15,000 students. Results showthat overall enrollment in CS courses rose modestly from 10% to 15% between the2018-2019 and 2022-2023 school years. Enrollment declined to 13% in 2023-2024,though the cause and persistence of this trend remains unknown. Additionalanalyses differentiate foundational and advanced CS courses as well as examineparticipation by sex and race, offering additional insight. As CS, artificialintelligence, and related fields become more important across our society, theyalso become a key component of a robust K-12 education. Analyzing andunderstanding these trends in CS enrollments is crucial to inform policy andinstruction that encourage students to participate and succeed in CS;thisresearch brief presents one such analysis. Copyright © 2025, The Authors. All rights reserved.

关键词： Codes (symbols)  

摘要： The increasing complexity of computer science research projects demands more effective tools for deploying code repositories. Large Language Models (LLMs), such as Anthropic Claude and Meta Llama, have demonstrated significant advancements across various fields of computer science research, including the automation of diverse software engineering tasks. To evaluate the effectiveness of LLMs in handling complex code development tasks of research projects, particularly for NLP/CV/AI/ML/DM topics, we introduce CSR-Bench, a benchmark for Computer Science Research projects. This benchmark assesses LLMs from various aspects including accuracy, efficiency, and deployment script quality, aiming to explore their potential in conducting computer science research autonomously. We also introduce a novel framework, CSR-Agents, that utilizes multiple LLM agents to automate the deployment of GitHub code repositories of computer science research projects. Specifically, by checking instructions from markdown files and interpreting repository structures, the model generates and iteratively improves bash commands that set up the experimental environments and deploy the code to conduct research tasks. Preliminary results from CSR-Bench indicate that LLM agents can significantly enhance the workflow of repository deployment, thereby boosting developer productivity and improving the management of developmental workflows. © 2025, CC BY-NC-ND.

关键词： Computer science   Machine learning  

摘要： The model produces cited, pages-long reports that might be helpful for generating literature reviews.

关键词： Computer crime  

摘要： Computer science research sometimes brushes with the law, from red-team exercises that probe the boundaries of authentication mechanisms, to AI research processing copyrighted material, to platform research measuring the behavior of algorithms and users. U.S.-based computer security research is no stranger to the Computer Fraud and Abuse Act (CFAA) and the Digital Millennium Copyright Act (DMCA) in a relationship that is still evolving through case law, research practices, changing policies, and legislation. Amid the landscape computer scientists, lawyers, and policymakers have learned to navigate, anti-fraud laws are a surprisingly under-examined challenge for computer science research. Fraud brings separate issues that are not addressed by the methods for navigating CFAA, DMCA, and Terms of Service that are more familiar in the computer security literature. Although anti-fraud laws have been discussed to a limited extent in older research on phishing attacks, modern computer science researchers are left with little guidance when it comes to navigating issues of deception outside the context of pure laboratory research. In this paper, we analyze and taxonomize the anti-fraud and deception issues that arise in several areas of computer science research. We find that, despite the lack of attention to these issues in the legal and computer science literature, issues of misrepresented identity or false information that could implicate anti-fraud laws are actually relevant to many methodologies used in computer science research, including penetration testing, web scraping, user studies, sock puppets, social engineering, auditing AI or socio-technical systems, and attacks on artificial intelligence. We especially highlight the importance of anti-fraud laws in two particular research fields that are of great policy importance in the current moment: attacking or auditing AI systems, and research involving legal identification. Finally, guided by principles in research ethi

关键词： Education   Informatics   Gender   Computer science   Information systems  

摘要： Purpose Digital transformation is a key factor in the competitiveness of modern businesses. However, the shortage of IT specialists poses a significant challenge. The significant underrepresentation of women in IT-related programmes in higher education further increases the skills shortage and reduces diversity and creativity. Against this background, this study aims to investigate the gender-specific factors influencing the decision to pursue IT-related degrees in the context of business informatics (B-Inf) in Germany to understand why few young women choose this field of study. Design/methodology/approach A quantitative survey was conducted with 186 undergraduate students in Germany. The survey examined the perceptions and priorities of both male and female students when choosing their field of study. Findings The results reveal that women place greater emphasis on job security and societal impact when selecting their field of study, whereas men tend to prioritise interest in technology, personal development and enjoyment of IT-related work. Originality/value Although previous research has focused on computer science programmes, little attention has been paid specifically to B-Inf programmes, which are a distinct discipline combining computer science and business administration. This study contributes new insights into the gender-specific preferences influencing the choice of B-Inf degrees, offering practical implications for increasing female participation and addressing the IT skills gap.

关键词： 产教融合   课程改革   人才培养  

摘要： 探讨在产教融合背景下高等职业院校中改革计算机专业课程教学的策略。分析产教融合为计算机教育带来的新机遇和挑战,指出当前教学中存在的问题,并提出优化教学内容、改变教学方式、加强教师团队建设、改革评价体系以及改善实验条件等一系列教学改革策略。通过这些方法的实施,促使该课程培养体系更贴近行业需求,为社会培养出适应产业发展需求的人才。

关键词： 校企合作   研创双驱   课程改革   项目化教学   职业教育  

摘要： 在经济和产业结构升级背景下,对高素质技能型人才的需求激增,而现有教育模式未能充分满足企业实际需求,导致毕业生就业难题。研究响应国家政策,以武汉职业技术学院人工智能学院用户界面设计课程为案例,通过问卷调查的方式了解计算机类专业课程与实际工作需求脱节、实践性不足、教学方法单一等问题。针对这些问题提出一系列校企合作下的课程改革策略,包括实训课程升级、毕业设计研发、跟岗学习经验积累、课程内容重构、项目化教学实施、信息技术融合教学,以及岗位能力导向评价体系构建。研究结果表明,校企联动模式能有效缩小教育与行业需求间的差距,丰富课程内容,提升教学质量,并激发学生的创新能力,对推动职业教育改革具有重要意义。