The use of CAI to enhance human interaction in the learning of deductive proof construction

It is unfortunate that most forms of CAI either decrease or replace student-teacher interaction and rarely promote student-student interaction in a deliberate fashion. The project described here, however, aims at improving human interaction in a deductive logic course via the use of a proof-checking computer program. This program supports analyses of student performance which guide in-class instruction on a real-time basis. It is a widely held belief that individualization promotes effectiveness in teaching and that CAI promotes individualization. Some questions are raised about these beliefs, and the conclusion drawn is that the prospects for a computer technology that enhances rather than diminishes human interaction should be more vigorously explored. Ultimately, the efforts reported here are intended to show that the use of computers in education need not constitute a form of separating teachers from their students, but rather can provide information concerning student needs and can supply opportunities for addressing those needs both within and outside the classroom.Marvin Croy is an associate professor of philosophy at the University of North Carolina at Charlotte. His current interests are in developing CAI that improves both in-class instruction and the quality of teacher-student interaction while simultaneously integrating teaching with research. This work was supported in part by a Curriculum and Instructional Development Grant funded by the Foundation of the University of North Carolina at Charlotte and by the State of North Carolina. An earlier version of this paper was read at the Eighth International Conference on Computers and the Humanities held at the University of South Carolina, April, 1987     

智能计算机辅助教学系统的实现研究

随着人工智能技术的引入,计算机辅助教学(CAI)发展成为智能计算机辅助教学(ICAI)。ICAI不但克服了传统CAI的许多弱点,而且大大地提高和改善了教学的效果和效率。本文首先对智能计算机辅助教学系统的特性和功能进行分析和研究,并在此基础上给出一种相应的实现框架。     

基于Web的《计算机文化基础》智学教学研究浅探

传统的计算机辅助教学(CAI)模式忽视学生的主体性和差异性,不能根据学生的各自特点实施因材施教。而智能计算机辅助教学系统(ICAI)坚持"以人为本、学生第一"的教育原则,尊重学生的个体差异性,实现因人施教、自适应性教学,充分发挥学生的主体作用。本文针对《计算机文化基础》教学中存在的不足,结合智能教学系统特点,研究并给出了一种基于Web的《计算机文化基础》的智能教学系统构造原型。     

ICAI的研究和发展概况

将ＡＩ技术引入到传统的ＣＡＩ中成为智能计算机辅助教学（ＩＣＡＩ）。它比一般的ＣＡＩ有明显的优越性，它的实现和发展取决于认知科学、计算机科学、教育学、心理学的共同发展。它代表了一种新的教学思想和教学方式，有可能使传统的课堂教学产生巨大的变革。木文对ＩＣＡＩ的基本概念及发展历史，ＩＣＡＩ与专家系统的关系，ＩＣＡＩ的形式、结构和特点及在我国的发展前景作了简要介绍。     

An experimental economics approach toward quantifying online privacy choices

The importance of personal privacy to Internet users has been extensively researched using a variety of survey techniques. The limitations of survey research are well-known and exist in part because there are no positive or negative consequences to responses provided by survey participants. Such limitations are the motivation for this work. Experimental economics is widely accepted by economists and others as an investigative technique that can provide measures of economic choice-making that are substantially more accurate than those provided by surveys. This paper describes our efforts at applying the techniques of experimental economics to provide a foundation for (a) estimating the values that consumers place on privacy and various forms of security (encryption, HIPAA, etc.) and for (b) quantifying user responses to changes in the Internet environment. The contribution of this study is a better understanding of individual decision-making in the context of benefits and costs of making private information available to Internet sites. Preliminary results from a series of pilot studies are consistent with optimizing behaviors, indicating that continued application of experimental economics techniques in the quantification of Internet user actions in privacy/security space will be illuminating. Our results show that Internet users place great value on security measures, both regulatory and technical, that make identity theft much less likely. Our Web-based experiments indicate that privacy- and security- enhancing protections are likely to be subject to moral hazard responses, as participants in our online experiments became more aggressive in their Internet usage with greater protection in place.

生成传统解答的初中物理智能ＣＡＩ系统——原理、结构与关键技术

初中物理智能ＣＡＩ系统是作者设计和开发的实现问题临场解答和生成传统解答的基于人工智能技术教育软件。本文讨论了系统的设计原理、结构和关键技术、并用实例展示了该软件的主要功能。     

ICAI模型系统在高教自考辅助教学中的应用与研究

ICAI是一个具有大量专门知识的、能进行逻辑推理和模拟真正专家解决复杂专业问题的程序系统,它是将人工智能理论和技术应用于CAI而形成的一种教学专家系统。主要讨论了基于Client?Server的智能计算机辅助教学(ICAI)的实现技术,并依此建立了一个用于高等教育自学考试辅助教学的ICAI系统。     

构建远程ICAI的研究

该文介绍了将远程网络教学与ＩＣＡＩ相结合并构建远程ＩＣＡＩ的研究工作,提出了一个基于远程网络的ＩＣＡＩ模型,以及验证该模型的实验系统中有关知识表示、智能综合集成、协同教学模式和在超文本中增加教学控制描述等问题的解决方法。     

Multi-writer composite registers

Summary Acomposite register is an array-like shared data object that is partitioned into a number of components. An operation of such a register either writes a value to a single component, or reads the values of all components. A composite register reduces to an ordinary atomic register when there is only one component. In this paper, we show that a composite register with multiple writers per component can be implemented in a wait-free manner from a composite register with a single writer per component. It has been previously shown that registers of the latter kind can be implemented from atomic registers without waiting. Thus, our results establish that any composite register can be implemented in a wait-free manner from atomic registers. We show that our construction has comparable space compexity and better time complexity than other constructions that have been presented in the literature. James H. Anderson received the B.S. degree in Computer Science from Michigan State University in 1982, the M.S. degree in Computer Science from Purdue University in 1983, and the Ph.D. degree in Computer Sciences from the University of Texas at Austin in 1990. He recently joined the Computer Science Department at the University of North Carolina at Chapel Hill, where he is now an Assistant Professor. Prior to joining the University of North Carolina, he was an Assistant Professor of Computer Science for three years at the University of Maryland at College Park. Professor Anderson's main research interests are within the area of concurrent and distributed computing. His current interests primarily involve the implementation of resilient and scalable synchronization mechanisms.Preliminary version was presented at the Ninth Annual ACM Symposium on Principles of Distributed Computing [2]Much of the work described herein was completed while the author was with the University of Texas at Austin and the University of Maryland at College Park. This work was supported at the University of Texas by ONR Contract N00014-89-J-1913, and at the University of Maryland by NSF Contract CCR 9109497 and by an award from the University of Maryland General Research Board     

ICAI软件生存周期模型初探

该文在分析智能型计算机辅助教学(ICAI)软件开发特点,总结现有软件生存周期模型优缺点的基础上,提出了一种适合于ICAI软件开发的智能模型。并将该模型应用于《GIS设计》课程的ICAI设计中。     

智能教学系统中认知型学生模型的建立

在智能教学以学为主的学习模式中,学生模型是提供真正智能化指导的基础,该文提出在基于网络的智能教学系统中建立认知型学生模型的一种方法,介绍基于这种认知型学生模型的一个基于网络的小学数学智能教学系统,并对该系统的实验结果进行分析。     

Student models: the genetic graph approach

In this paper we examine the student model component of an intelligent computer-assisted instruction (ICAI) system. First, we briefly discuss the desirable capabilities of the student model and then describe, in detail, one approach to student modelling which is based on Goldstein's genetic graph. We expand Goldstein's definition and test it's feasibility in new domains, since his original domain was a limited, straightforward adventure game. In addition to modelling two diverse domains, subtraction and ballet, we also discuss the role of certain ICAI components in generating and maintaining the genetic graph.     

基于ICAI模型的电子家教系统设计

本文介绍了一种自行设计的ICAI模型为核心并实现网站原型的电子家教系统,以自己开发CAI资源网站的实例阐述了电子家教的原理、一体化结构、多媒体教学网络教育技术和设计过程,并对电子家教的发展趋势作出了展望。     

Knowledge as a Social Medium

The increasing popularity and access to computer networks such as the Internet has introduced a new form of interaction among individuals, and brought about the social dimension to intelligent systems that are embedded into group and community settings. Knowledge is now seen as an asset not only of an individual but also of groups; research fields such as organisational memory, knowledge management and community ware are beginning to emerge. This paper surveys recent approaches, discusses whether social knowledge is a tangible notion, and examines the role of social knowledge in the context of group and community oriented systems with new challenges it offers. Keiichi Nakata, Ph.D.: He is a research scientist at the Institute for Applied Information Technology (FIT) at GMD. He is currently a member of the “Social Web” research programme at GMD, with a particular interest in the investigation of social development of knowledge that belongs to communities, and its application to support social interactions. Prior to the current appointment, he has held lectureships at the University of Wales and Oxford Brookes University in UK. His academic background is BEng and MEng degrees in nuclear engineering from the University of Tokyo and PhD in AI from the University of Edinburgh.     

Teaching strategies and tactics in intelligent computer aided instruction

The teaching strategies for CAI systems are implicitly expressed in a branching network compared with those for ICAI systems which are represented explicitly and held separately from other components in the system such as the subject knowledge base. As such, they are open to investigation and criticism. In this paper I examine current perspectives on teaching strategies and critically review them. It has been suggested that teaching strategies are excessively ad hoc and the remedy lies in the construction of better theories of learning. I argue that other measures, e.g. utilising teaching models and providing systematic teaching strategies and tactics based on them would be more beneficial. A proposed solution to the teaching strategy problem is presented and related to the long-term objective to provide better theories of learning.     

An interdisciplinary laboratory for manufacturing education

Due to its nature of the field of manufacturing automation, education in this area is likely to be more effective in an interdisciplinary mode. Under this hypothesis, the School of Engineering at North Carolina A&T State University, has recently developed two courses and several laboratories for manufacturing engineering education. This paper will present the development and use of a Computer-Integrated-Manufacturing cell.     

基于关联规则的ICAI系统中矫正学习路径规划

教学系统的学习路径规划是其智能化的重要标志。该文针对学习结果中未达到学习目标要求的缺陷知识点,运用数据挖掘的情况Apriori算法,在大型知识库中发现并运用缺陷知识点之间的相关性,给出了矫正学习路径的智能规划算法,提高ICAI系统的因材施教 能力。     

基于Web和数据挖掘技术的智能教学系统

随着ICAI系统本身和网络的应用与发展,现有的ICAI系统已不能充分发挥其智能性,无法实现对潜在的大量聚集的信息进行发现和利用,造成了资源的极大浪费,为此构建了一个基于Web和数据挖掘技术的智能教学系统的实用模型,并分析和讨论了实现的基本原理和关键技术。从而实现了学生和教师间的个性化教学,优化了系统的性能。