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关键词： Visual languages  

摘要： The recent integration of visual capabilities into Large Language Models (LLMs) has the potential to play a pivotal role in science and technology education, where visual elements such as diagrams, charts, and tables are commonly used to improve the learning experience. This study investigates the performance of ChatGPT-4 Vision, OpenAI’s most advanced visual model at the time the study was conducted, on the Bachelor in Computer Science section of Brazil’s 2021 National Undergraduate Exam (ENADE). By presenting the model with the exam’s open and multiple-choice questions in their original image format and allowing for reassessment in response to differing answer keys, we were able to evaluate the model’s reasoning and self-reflecting capabilities in a large-scale academic assessment involving textual and visual content. ChatGPT-4 Vision significantly outperformed the average exam participant, positioning itself within the top 10 best score percentile. While it excelled in questions that incorporated visual elements, it also encountered challenges with question interpretation, logical reasoning, and visual acuity. A positive correlation between the model’s performance in multiple-choice questions and the performance distribution of the human participants suggests multimodal LLMs can provide a useful tool for question testing and refinement. However, the involvement of an independent expert panel to review cases of disagreement between the model and the answer key revealed some poorly constructed questions containing vague or ambiguous statements, calling attention to the critical need for improved question design in future exams. Our findings suggest that while ChatGPT-4 Vision shows promise in multimodal academic evaluations, human oversight remains crucial for verifying the model’s accuracy and ensuring the fairness of high-stakes educational exams. The paper’s research materials are publicly available at https://***/nabormendonca/gpt-4v-enade-cs-2021. © 202

关键词： Benchmarking  

摘要： Computer Science (CS) stands as a testament to the intricacies of human intelligence, profoundly advancing the development of artificial intelligence and modern society. However, the current community of large language models (LLMs) overly focuses on benchmarks for analyzing specific foundational skills (e.g. mathematics and code generation), neglecting an all-round evaluation of the computer science field. To bridge this gap, we introduce CS-Bench, the first bilingual (Chinese-English) benchmark dedicated to evaluating the performance of LLMs in computer science. CS-Bench comprises approximately 5K meticulously curated test samples, covering 26 subfields across 4 key areas of computer science, encompassing various task forms and divisions of knowledge and reasoning. Utilizing CS-Bench, we conduct a comprehensive evaluation of over 30 mainstream LLMs, revealing the relationship between CS performance and model scales. We also quantitatively analyze the reasons for failures in existing LLMs and highlight directions for improvements, including knowledge supplementation and CS-specific reasoning. Further cross-capability experiments show a high correlation between LLMs' capabilities in computer science and their abilities in mathematics and coding. Moreover, expert LLMs specialized in mathematics and coding also demonstrate strong performances in several CS subfields. Looking ahead, we envision CS-Bench serving as a cornerstone for LLM applications in the CS field and paving new avenues in assessing LLMs' diverse reasoning capabilities. The CS-Bench data and evaluation code are available at https://***/csbench/csbench. Copyright © 2024, The Authors. All rights reserved.

关键词： Machine Learning   Big Data   Computer Science   Internet Of Things   Digital Signal Processing   Postdoctoral Fellow   Forward Error Correction   Science Degree   Decoder Architecture   Department Of Computer Science   IEEE Transactions  

摘要： Jia Wu received the PhD degree in computer science from the University of Technology Sydney, Ultimo, NSW, Australia. He is currently an ARC DECRA fellow with the Department of Computing, Macquarie University, Sydney, Australia. Prior to that, he was with the center for Artificial Intelligence, University of Technology Sydney. His current research interests include data mining and machine learning.

关键词： E-learning  

摘要： Skills in the field of computer science (CS) are increasingly in demand. Often traditional teaching approaches are not sufficient to teach complex computational concepts. Interactive and digital learning experiences have been shown as valuable tools to support learners in understanding. However, the missing social interaction affects the quality of the learning experience. Adding collaborative and competitive elements can make the virtual learning environment even more social, engaging, and motivating for learners. In this paper, we explore the potential of collaborative and competitive elements in an interactive virtual laboratory environment with a focus on computer science education. In an AB study with 35 CS students, we investigated the effectiveness of collaborative and competitive elements in a virtual laboratory using interactive visualizations of sorting algorithms. © 2024, CC BY.

关键词： 国防教育   新媒体   国家安全   人才培养  

摘要： 高校国防教育对维护国家安全起到关键作用,通过深度融合新媒体技术与实践教学,将国防教育融入学生活动和计算机专业课程中,可以提升大学生对国家安全的认识和责任感。利用赛创结合的研究方法,在创新创业竞赛中嵌入国防教育元素,以激发大学生积极参与并强化其国家安全意识和社会责任感。本文通过对国防教育融入计算机专业人才培养模式的探索,为培养兼具国家安全意识和社会实践能力的学生提供了新的思路和借鉴。

关键词： 互动仪式链   短视频   叙事策略   “和女儿分享日常”  

摘要： 目的:近年来,“电子父母”成为互联网上的热点话题,如抖音平台上的“和女儿分享日常”以及小红书上的“小琳妈妈”等,都以父母的第一视角出发,与网友分享日常,还会满脸笑容地跟孩子打招呼、聊生活,几乎每句话都以“孩子”“闺女”“儿子”开头,因此,其被网友暖心地称为“电子父母”。特别是抖音账号“和女儿分享日常”,作为一个拥有超高热度的短视频创作者,在网络平台迅速走红,仅3个月时间就涨粉100万,其创作的日常家庭生活短视频在极短时间内便获得了大量关注。文章主要研究网络上流行的“电子父母”类短视频账号,分析其视频内容的叙事策略。方法:从互动仪式链视角出发,以“和女儿分享日常”账号的视频为研究对象,采用文本分析法对“电子父母”类短视频的标题、内容、形式、播放量、点赞数、转发量等进行叙事分析,从叙事主题、叙事方式以及叙事内容方面深入挖掘其叙事策略及存在的问题。结果:“和女儿分享日常”账号的内容创作者通过亲和力强的叙事策略,如采用热点化和碎片化的叙事主题、丰富且多元的叙事内容、生活自我呈现型的叙事方式,引发用户的情感共鸣,构建了一个完整的互动仪式链,缩短了屏幕内外的距离,让受众感受到了温馨的家庭氛围与互动的乐趣。然而,这种叙事方式也面临潜在的挑战,如过度商业化、广告植入以及可能面临的热度降低、同质化危机等。结论:基于互动仪式链理论理解“电子父母”类短视频的走红,不仅能揭示当代年轻人身上遗留的童年伤痕,还能为家庭亲密关系的构建提供新的视角。数字化时代,用户在享受“电子父母”类短视频带来的乐趣的同时,也应形成批判性思维,理性消费内容,在亲子关系的数字化表达中寻找真正有益于家庭和谐的元素。

关键词： 水产技术推广   模式变革   养殖试验   网箱养殖   水产养殖   健康养殖模式   大宗淡水鱼   联动  

摘要： 近几年来,水产技术推广人员在上海地区开展了多种箱塘联动大宗淡水鱼绿色健康养殖模式的探索和实践,即将传统的池塘“开放式散养”模式变革为池塘内“网箱圈养”大宗淡水鱼绿色健康养殖模式。本文介绍一种基于池塘种草,同时在池塘中开展草鱼网箱养殖、青鱼网箱养殖的健康养殖试验,供广大水产养殖从业人员参考。

关键词： 计算机辅助设计   设施农业科学与工程   温室工程   辅助设计软件  

摘要： 计算机辅助设计是设施农业科学与工程专业的一门选修课程。为满足培养现代设施农业所需的多学科交叉融合的复合应用型人才的要求,本文分析计算机辅助设计课程在教学连续性、教学内容、教学教材和教学方式等方面的现状,结合培养设施农业设计施工管理人员的需求,通过衔接理论与实践教学、建立温室工程图案例库、增加学科前沿的辅助设计软件和改革创新教学方法4个方面,对设施农业科学与工程专业的计算机辅助设计课程教学进行改革与探索。旨在提升人才培养质量,为相关专业教学提供参考。