勘查技术与工程专业Matlab语言教学研究与实践

Matlab语言因其强大的数值与符号计算功能、简单的语法和友好的界面,一直以来都是勘查技术与工程专业学生进行专业课学习、实习及实践的首选工具。作者总结自己近年来利用人工智能技术解决地震勘探实际问题的案例,并基于智慧课堂所提供的软硬件平台,对Matlab语言课程进行了教学改革与实践,提升了教学效果。     

Artificial intelligence and education in China

ABSTRACT

This paper examines the political economy of artificial intelligence (AI) and education in China, through an analysis of government policy and private sector enterprise. While media and policy discourse often portray China’s AI development in terms of a unified national strategy, and a burgeoning geopolitical contestation for future global dominance, this analysis will suggest a more nuanced internal complexity, involving differing regional networks and international corporate activity. The first section considers two key policy documents published by the central Chinese government, which are shown to implicate educational institutions as influential actors in national and regional strategies for AI development, with a significant role in plans to train domestic expertise. The second section outlines three prominent private education companies: New Oriental Group, Tomorrow Advancing Life (TAL), and Squirrel AI. These companies are selected to represent important aspects of China’s development of educational AI applications, including the influence of a well-established private education sector, and a growing interest in international corporate activity. The paper concludes with the suggestion that while central government policy reserves a significant role for education in the national AI strategy, the private sector is utilising favourable political conditions to rapidly develop educational applications and markets.     

未来学校的内涵、表现形态及其建设机制

未来学校是在新一轮工业革命背景下发生的学校系统性变革,是基于未来人才培养需求与人工智能技术深度融合创新而形成的处于持续动态发展进程中的新型态育人场域。未来学校的表现形态在于虚实交融的泛在学校时空、人机环境融合的学校结构性系统以及基于学习者自适性学习的学校教育服务形态。未来学校的建设机制包括智慧教育理念的价值传导机制、学校自适应创新发展机制以及人工智能技术的学校教育应用机制,从而为未来学校的建设提供有效的理念指引、内在动力与技术支撑。     

人工湿地污水处理技术

人工湿地作为一种节能、经济、简易和有效的生态化污水处理技术，近几年来在我国一些城市应用较为广泛。本文从人工湿地的基本组成、机理谈起，结合一些实例比较说明了人工湿地的特点。并针对其近些年在应用中常出现的问题提出了部分解决措施。     

智能机器人及其教学应用:创新意蕴与现实挑战

第三次人工智能浪潮的到来,掀起了人类历史上最具颠覆性的智能化革命,深刻地改变了技术与人的关系。以人工智能(AI)为驱动力的智能机器人技术,正逐步进入学校与课堂,赋能教学创新,催生了整合智能机器人的新型教学与学习生态系统。基于此,从智能机器人的内涵出发,梳理智能机器人的发展特征与教学功能;结合智能机器人的教学应用典型案例,审视智能机器人作为教学赋能之要素。通过计算与连接工具,探讨智能机器人助力精准教学、实践创新能力培养,开展智慧学伴、智能测评、大数据教学过程管理、人机协同"双师课堂"等方面的教学应用;从教学系统变革层面出发,以智能机器人为增强要素,促进教育系统的协同与治理;支持教师数字素养提升,补偿性教育技术应用,教学管理智能化,助力学校教育"智"理等;同时,结合现实提出智能机器人在教学应用中面临的五大挑战,以期为智能时代智能机器人的教育应用与发展,提供参考与思路。     

论互文性理论对电影《人工智能》叙事艺术的阐释

2001年,由斯蒂芬.斯皮尔伯格编剧并执导的电影《人工智能》上映后引起巨大的反响,该电影改编自英国作家布赖恩.W.奥尔迪斯于1969年发表的短篇小说《永恒的夏天：寻求母爱的人工智能男孩》。互文性理论是由法国符号学家朱丽娅·克里斯蒂娃提出的,后被众多学者补充发展,这一理论的提出为理解文本提供了一个新的视角。     

Clinically applicable artificial intelligence algorithm for the diagnosis,evaluation, and monitoring of acute retinal necrosis

The prompt detection and proper evaluation of necrotic retinal region are especially important for the diagnosis and treatment of acute retinal necrosis(ARN). The potential application of artificial intelligence(AI) algorithms in these areas of clinical research has not been reported previously. The present study aims to create a computational algorithm for the automated detection and evaluation of retinal necrosis from retinal fundus photographs. A total of 149 wide-angle fundus photographs from40 eyes of 32 ARN patients were collected, and the U-Net method was used to construct the AI algorithm. Thereby, a novel algorithm based on deep machine learning in detection and evaluation of retinal necrosis was constructed for the first time. This algorithm had an area under the receiver operating curve of 0.92, with 86% sensitivity and 88% specificity in the detection of retinal necrosis. For the purpose of retinal necrosis evaluation, necrotic areas calculated by the AI algorithm were significantly positively correlated with viral load in aqueous humor samples(R2=0.7444, P0.0001) and therapeutic response of ARN(R2=0.999, P0.0001). Therefore, our AI algorithm has a potential application in the clinical aided diagnosis of ARN, evaluation of ARN severity, and treatment response monitoring.     

When artificial intelligence meets educational leaders’ data-informed decision-making: A cautionary tale

Artificial intelligence (AI) refers to a type of algorithms or computerized systems that resemble human mental processes of decision making. Drawing upon multidisciplinary literature that intersects AI, decision making, educational leadership, and policymaking, this position paper aims to examine promising applications and potential perils of AI in educational leaders’ data-informed decision making (DIDM). Endowed with ever-growing computational power and real-time data, highly scalable AI can increase efficiency and accuracy in leaders’ DIDM. However, misusing AI can have perilous effects on education stakeholders. Many lurking biases in current AI could be amplified. Of more concern, the moral values (e.g., fairness, equity, honesty, and doing no harm) we uphold might clash with using AI to make data-informed decisions. Further, missteps on the issues about data security and privacy could have a life-long impact on stakeholders. The article concludes with recommendations for educational leaders to leverage AI potential and minimize its negative consequences.     

人工智能教育的情感文明:何以必要与何以可为

人工智能教育作为信息时代的教育理念和教育形态,呈现出蓬勃发展之势,其高度发达的技术文明呼唤相应的情感文明予以平衡。人工智能教育的情感文明是指人工智能教育系统在情感层面达臻开明与进步的合理状态,由此形成富有育人价值的情感境界。情感文明作为促进人工智能教育变革创新的精神力量,能够彰显人工智能教育的情本文化,落实人工智能教育的成人之学,完善人工智能教育的实践逻辑。建设人工智能教育情感文明需要提升人工智能教育场域的情感温度、合理遵循人工智能教育的情感规则、培育人工智能教育主体的情感修养,以及有效运用人工智能教育的情感资源,厚植人工智能教育的情感底蕴,走向技术文明与情感文明和谐共生的育人境界。     

人工智能赋能课堂教学评价改革与技术实现的框架构建

作为强大技术推动力的人工智能正引发着一场技术革命,推动社会步入智能时代。开展人工智能下的课堂教学评价,能够辅助智慧评价的高效开展、关注情感信息的动态变化、还原真实课堂的精准采集、实现师生成长的轨迹追踪。通过对象层、数据层、技术层和应用层四个层面的系统架构,搭建人工智能下课堂教学评价的实践路径,指向课堂语言分析、课堂行为分析、课堂情感分析与课堂教学评价体系四大应用场景。未来人工智能下课堂教学评价的深度发展与广泛应用还需探索专业化的评价指标构建、加强个性化的教师行为反馈、着眼发展性的未来教育挑战。