智慧中药房建设的思路与举措

探索将人工智能应用在中药房的全程运行与管理之中,对智慧中药房的建设进行了深入研究:应用自动中药房机械手、药品条码化管理、研发设计智能药架、智能药柜及智能显示系统,运用信息化工具辅助审方,将大数据技术应用于电子叫号、智能收方、药物咨询、处方点评、患者教育各工作阶段。     

智能时代教育研究的认识论变革与方法论转变

文章对教育领域的"三个世界"及其智能虚拟映射进行了认识切割,在此基础上提出了三个新的智能虚拟世界:代表数字化教育事实和存在的世界一’、代表人工智能教育认识的世界二’、代表人工智能教育思想和知识库的世界三’。文章指出,这三个新的智能虚拟世界是教育领域的"三个世界"在人工智能环境下的智能虚拟映射,扩展了传统教育研究的本体论假设,进而导致认识论的全方位变革。此外,文章还从认识主体、研究对象、研究范式、推理思维、知识表征等五个方面的变化,阐明了教育研究的认识论变革所引发的方法论转变。文章的研究有助于理解智能时代教育的过程与本质,并为教育人工智能系统的设计、开发与应用提供理论依据。     

遗传算法教学辅助系统分析与设计

随着人工智能的不断发展,遗传算法(Genetic Algorithms,简称GA)作为一种人工智能算法有着很长的发展史,在工业,医疗等等许多方面都有着广泛的运用,但是因其依靠随机搜索,在演示教学上一直有其难度,这点在一定程度上影响了遗传算法的运用及推广,作者通过对遗传算法的研究和对软件系统的分析,达到了对算法的分步演示及可视化,改善了教学方法,提高了教学质量。     

Forget EPSSs: How You Can Marshal Mobile Geographic Information Systems (GISs) and Spatial Awareness for Performance Improvement

Mobile geolocation applications identify global coordinates of mobile devices and can be enriched with performance‐context data. This technology has potential to integrate job aids, learning bursts, and parts of manuals with work tools (such as checklists) at the point of performance to better support individual and team performance. Emerging uses of mobile geolocation allow human performance technologists to move from generic electronic performance support systems (EPSSs) to spatial support systems. These increase the potential for performers to access more context‐aware information at the time and space in which the actions occur. Mobile geolocation can also automatically send data about the performance to enterprise databases so that actions taken and the use of training or job aids at the point of performance can be tracked. This article explores how mobile geolocation functionality can be orchestrated to support performance, enrich enterprise databases, and aid human performance technologists.     

Artificial intelligence applications to high-technology training

Recent advances in artificial intelligence (AI) could be used to improve occupational instruction in complex subjects with sophisticated performance goals, such as those required for high-technology jobs. Educational devices incorporating AI would “understand”what, whom, andhow they were teaching and could therefore tailor content and method to the needs of an individual learner without being limited to a repertoire of prespecified responses. Intelligent Computer Assisted Instruction (ICAI) encompasses a spectrum of approaches, including Socratic tutoring systems, simulation environments with embedded coaches, and “empowering environments” which aid workers in using intelligent tools in complementary cognitive partnerships. This article focuses on (a) depicting how present training methods might change if intelligent instructional devices were incorporated, (b) delineating the current state of the art in the areas of research needed to produce such systems, and (c) indicating in which types of adult educational settings ICAI might be productive and cost effective.     

Performance support that adds value to everyday lives

At the beginning came the job aid. Now, we incline toward performance support tools (PSTs), sometimes fondly described as “job aids on steroids.” PSTs that support employee performance have been studied, but scant attention has been paid to the PSTs that add to people's everyday lives beyond work. We studied 30 diverse people, voluntary PST users, to gauge their opinions and attitudes about such widely available PSTs as MapQuest, VideoJug, eHow, WebMD, and Turbo Tax.     

国外人工智能教学应用研究综述

人工智能技术在教育教学中的应用日渐丰富,国内关于人机协同的研究多偏向于宏观理论探索,实践研究较少。鉴于此,研究以近三年三本具有国际影响力的期刊中人工智能教学应用相关文献为样本,以人工智能局部替代教学、赋能教学为焦点,分析国外人工智能教学应用研究现状。从中可以看出,当前国外研究者在探索认知特征、学习本质和教育规律的基础上,关注将机器学习、逻辑推理、自然语言理解等人工智能技术嵌入各类教学、学习、决策等工具、系统、平台中,支持构建体验学习情境、规范学习行为、评估学业水平和能力结构、制定个性化学习路径和内容等研究,旨在通过人机协同优化教学方式与路径,为学习者提供个性化学习服务。这些研究成果对开发人工智能教学产品、理解学习的本质、探索教学规律等提供了方法指导和可供借鉴的研究范式,但也存在人工智能教学应用研究狭窄化、碎片化、微观化等问题,后期还需从宏观、中观层面开展人工智能与教学的关系研究、人工智能教学应用关键技术研究、人工智能赋能教师的理论基础研究、人工智能与教学融合形态研究、人机协同背景下的教师人工智能教学应用素养研究等。     

人工智能与教育深度融合发展:逻辑、困境与策略

人工智能与教育深度融合发展的目的在于通过高智能性的技术来不断提升教育的科学性和民主化。人工智能与教育深度融合发展的操作原理是通过技术、数据和算法的重组,推动教育走向智能化,具体表现为支持智能教育关键技术的高智能化(技术)、教育资源的整合与教育大数据的形成(数据)和教育供给的科学化(算法+服务)。就目前而言,人工智能与教育深度融合发展还存在技术基础不稳、教育数据缺陷、算法能力不足等现实问题。为此,要想实现人工智能与教育的深度融合发展,教育应尽早谋划,重新思考人工智能时代教育将如何存在,并从技术基础(改善技术的成熟度,重新思考技术世界中的教育)、数据驱动(加快教育数据资源的整合力度,提高教育数据单元质量)和算法服务(创新教育资源的有效供给方式)三个层面协同推进。     

INTELLIGENT DISCOVERY SYSTEMS (IDS)

In the literature on Intelligent Computer‐Aided Instruction (ICAI), and more widely, in that on artificial intelligence in education, we can distinguish, as a general rule, between intelligent tutoring systems and learning environments (also called micro‐worlds). In this article, we have attempted to merge these two approaches so as to produce a synthesis which we propose calling intelligent discovery systems.     

Participant or spectator? Comprehending the willingness of faculty to use intelligent tutoring systems in the artificial intelligence era

The advancement of technology, especially the development and application of artificial intelligence, has deeply affected the education sector and brought opportunities for pedagogical adaptation. Intelligent tutoring systems, a major application of artificial intelligence in education, have drawn extensive concerns. However, in reality, the penetration rate of intelligent tutoring systems and the enthusiasm of faculty to use are still relatively low. This research examined the determinants of the willingness of faculty to use intelligent tutoring systems. Innovation diffusion theory was the theoretical basis of this research and it was adapted by incorporating perceived trust and experience. To gather data, a cross-sectional questionnaire survey was performed and structural equation modeling was employed to analyze the data. The findings indicated that relative advantage, compatibility, perceived trust and experience are the contributing determinants of the willingness of faculty to use intelligent tutoring systems, while complexity has no significant effect. Meanwhile, complexity is significantly negatively affected by experience and compatibility. Relative advantage is significantly positively affected by perceived trust but not by complexity. Based on the research findings, relevant recommendations for encouraging faculty to use intelligent tutoring systems were proposed.     

智能课堂助手：人工智能背景下的教学工具

智能课堂助手是人工智能发展的产物,其采用自然语言处理、情感分析技术与学生自然交互,实现趣味性学习、个性化教学。从大学课堂情境、学具、教具、资源4个方面的教育价值进行分析,提出智能课堂助手与学生自然语言交互的课堂教学架构,并实现课堂教学具体应用。研究发现,智能课堂助手对学生的课堂参与度有积极影响,智能课堂助手正向影响学生课堂情感状态,正向情绪高于负向情绪,课堂不良行为大幅降低。     

Predicting Achievement Goals in Two Different Academic Contexts: A longitudinal study

The relative contribution is examined of epistemological beliefs and implicit theories of intelligence to students' adoption of mastery, performance‐approach and performance‐avoidance goals in two different academic contexts, business administration and teacher education, in the short as well as the long term. The results showed that epistemological beliefs about the speed of knowledge acquisition predicted achievement goals. Students who believed that learning occurs quickly or not at all were less likely to adopt mastery goals and more likely to adopt performance‐avoidance goals. In addition, students who believed in stable and given knowledge were less likely to adopt mastery goals. Differences in predictive patterns across the two contexts concerned the prediction of performance‐approach goals and gender differences in goal adoption. Epistemological beliefs played a more important role in goal adoption than implicit theories of intelligence.     

人工智能驱动的高校智慧教学空间融合研究

人工智能驱动的高校智慧教学融合了高校教学与人工智能技术的优势,已成为大数据环境下现代高校教学改革与发展的重要现实课题之一。本研究基于人工智能驱动的视角,审视其内嵌于高校智慧教学空间的融合实践可能性,试图构建一种将方法、技术、资源融为一体的“三维空间设计（物理空间、虚拟空间、数据联通空间）”。为此,面向不同主体（教师、学生和教学过程）来刻画人工智能驱动的智慧教学应用图景,以期理顺智慧教学空间融合的实践面向逻辑,旨在进一步助推高校智慧教学的高质量发展。     

A Study of the Correlation Between the Backgrounds of Medical School Students and Their Scores on Examinations

There are individual differences and characteristics in the growth of intelligence and intellectual capacity among students. These differences are reflected not only in terms of their various conditions of and capacities for learning, or their learning methods, but also in terms of the individual personal traits of the students and their identity with the "types" of learning. Therefore, studying the factors that influence the growth and development of students' intelligence and intellectual capacity holds a major significance for the task of improving the educational process and promoting the cultivation of talents for society's use. For the purpose of explaining the correlation between the various backgrounds of students and the development of their knowledge and mental capabilities, we will examine the test scores of the graduates of our medical institute from 1982 to 1984. During these years, these students sat for the general professional qualifying examination in comprehensive and clinical medicine. On the basis of these data, we attempt to draw some conclusions about the correlation between the various backgrounds of the students and the test scores they attained in the general examination. We will use these data to examine the factors that influence the development and growth of students' knowledge and intelligence.     

人工智能在金融领域的应用现状及未来需求分析

人工智能技术的不断进步促进了金融领域的规范化、智能化和模型化发展,在金融服务、金融监管、金融分析等邻域得到了广泛应用。现阶段人工智能技术在金融领域的应用还较为初级,通过研究人工智能技术在金融领域的应用现状和影响,分析未来金融领域人工智能技术的应用需求和前景,对促进真正的“智能金融”发展具有一定的意义。     

Three reflections on assessing safety training needs: A case study

Needs assessment plays an important role in training and human performance improvement efforts, but the literature contains little research on this topic. This study extended previous research on the Performance Analysis for Training (PAT) model of needs assessment by examining its implementation to determine environmental and occupational health and safety training needs in a government agency. Using case study methodology and the lens of responsive evaluation, this study resulted in three perspectives about the actual needs assessment implementation. The three professionals' distinct areas of expertise (evaluation, health and safety, human resource development) informed the case in unique ways. The results can be used to improve the PAT model and also to give human resource development and performance improvement professionals insights about nuances of needs assessment practice.     

关于“人工智能”技术发展的思考

从人工智能的产生开始简单阐述了人工智能这门学科的发展历史以及未来前景,并通过人工智能与人脑智能的比较,近一步阐明该学科的理论基础及其发展。     

国际人工智能教育研究的进展及其对专业人才培养的启示

通过科学知识图谱分析方法,对Scopus数据库中近二十年8660篇的国际人工智能教育研究文献进行深入分析,主要聚焦于国际人工智能教育研究的发展态势和知识结构。结果显示:驱动人工智能研究的主要是政策、经济投入与国际合作;而人工智能教育研究的知识结构间的关系主要涉及机器学习/教育、智能导学系统和人类学习/教育,它们在根本上体现了智能主体(人与机器)间的关系,并凸显数字化学徒制的特征。进而启发人工智能教育专业人才培养:一是要重视政策、经济投入和国际合作等外部动因;二是要紧扣智能主体视域下人机关系及其四种主客体结构的核心内容;三是要加强技术伦理教育。此外,还要应对可能的风险。     

人工智能时代学生主体性的相关问题探讨

为探讨人工智能时代学生主体性可能遭遇的危险,文章围绕“学生是谁”、“何种角色”和“如何存在”这三个问题,分别追问了人工智能时代学生的主体属性、反思了人工智能时代学生的主体地位、分析了人工智能时代学生主体权利的实现程度,研究结果表明:人工智能时代学生存在被物化的可能,学生可能再次成为学校教育中的被塑造者,学生的主体权利可能会被隐蔽式剥夺。为消除这些潜在的危险,文章明确了人工智能时代巩固学生主体性需要解决的关键问题并对其进行了探讨,以推动人工智能时代学生的全面发展,并为人工智能在教育中的应用提供一定的理论参照。     

教育人工智能(eAI):人本人工智能的新范式

人工智能是未来教育创新发展的重要推动力,遵循人本主义理念并形成人本人工智能教育新应用,将有力促成一种新型的研究与应用范式——教育人工智能(educational Artificial Intelligence,eAI)的形成。eAI注重以人为本的协作教育理念,在智能技术的支持下,以人和机器的交互、协作为研究对象,理解教育活动并揭示其发生的规律,从而促进人和机器智慧的共同成长。因此,在以人为本理念的引领下,eAI必将是人本人工智能的持续动力和新的研究范式,也是未来教育创新发展的新诉求。文章深度融合人本人工智能与教育,开展eAI的理论探究。首先,从人工智能、人在回路和奇点生态三方面阐释了人本人工智能的内涵,并解析eAI创新所需要的支持智能、增强智能和人机协同智能的一体化联动。在此基础上,剖析eAI的核心要素,构建了人本人工智能引领下eAI的研究框架,以人在旁路、人在回路和人在领路模式贯穿三大智能(支持智能、增强智能和人机协同智能)来透析eAI生态。最后,从基于混合智能的eAI环境、面向协同增智的eAI技术、底线思维引领下的eAI实践理性、面向设计思维的eAI创变力量、基于和谐共生的教育伦理等方面探寻了人本人工智能视域下eAI新范式,以期为构建人本人工智能视角下人机协同的eAI新生态提供设计思路和实践指导。