Computer-aided Instruction System Research Articles

Application of Knowledge Sharing Decision Model Based on Computer-Aided System in Student Education Management Platform

The knowledge-sharing, decision-making model can not only combine the two processes but also improve the teaching quality and students' learning achievements. However, the existing knowledge-sharing, decision-making model has many shortcomings. Therefore, for this article the authors applied the computer-aided instruction (CAI) system to the knowledge-sharing decision model and compared it with the traditional knowledge-sharing decision model. They compared and analyzed the application effects of the two processes in the student education management platform, and the experimental comparison was made from the perspective of curriculum and students. When the authors used the traditional knowledge-sharing decision model, the average score of the five people in the course A exam was 78.2. After they used the knowledge-sharing decision model based on the computer-aided instruction system, the average score of the five people in the course A exam was 85.4. Obviously, the knowledge-sharing, decision-making model based on the CAI system can effectively improve students' academic performances.

Construction of Computer Aided Instruction System for Indoor Design Based on VR 3D Modeling

Construction of Computer Aided Instruction System for Indoor Design Based on VR 3D Modeling

Construction of Computer Aided Instruction System for Art Design Based on Image Feature Recognition

Construction of Computer Aided Instruction System for Art Design Based on Image Feature Recognition

Entrepreneurship education-infiltrated computer-aided instruction system for college Music Majors using convolutional neural network.

The purpose is to improve the teaching and learning efficiency of college Innovation and Entrepreneurship Education (IEE). Firstly, from the perspective of aesthetic education, this work designs the teacher and student sides of the Computer-aided Instruction (CAI) system. Secondly, the CAI model is implemented based on the weight sharing and local perception of the Convolutional Neural Network (CNN). Finally, the performance of the CNN-based CAI model is tested. Meanwhile, it analyses students’ IEE experience under the proposed CAI model through a case study of Music Majors from Xi’an Conservatory of Music. The experimental data show that the CNN-based CAI model can respond quickly and stably when users access different functional modules, such as webpage browsing. The proposed CAI model increases students’ entrepreneurial interest, skills, and knowledge by 55.62, 57.32, and 72.12%, respectively. Students’ entrepreneurial practice ability has been improved by over 50.00%; such an increase in entrepreneurial practice ability has also shown individual differences. Thus, the proposed Music Majors-oriented IEE-infiltrated CAI model based on CNN improves students’ entrepreneurial practice ability and reflects the positive experience of Music Majors on IEE. The finding provides references for the step-by-step identification of the CNN-based CAI model and has certain guiding significance for analyzing the effect of college IEE.

Application of Computer-Aided Instruction (CAI) in the Physical Education: Survey Analysis of Chinese Universities.

With the advent of artificial intelligence, computer-aided instruction has developed into intelligent computer-aided instruction. Computer-aided instruction not only overcomes many weaknesses of traditional physical education teaching but also significantly increases the teaching effect and efficiency. This article first studies and analyzes the characteristics of computer-aided instruction systems. Then, we use statistical methods and logical analysis to randomly select two classes of undergraduate students as the experimental and control group, respectively. In the control group, the traditional teaching model was adopted, while the experimental group adopted the computer-aided teaching mode. The experimental group showed significant improvement in physical education as compared to the control group. The results of this study validated that the use of computer-assisted instruction is beneficial in the implementation of physical education programs, mostly in teaching concepts and principles of academic nature.

Application of Computer Mechanical Drawing Technology in Mechanical Engineering Manufacturing Parts Design

At present, many CAD software products can not fully meet the requirements of the national standard “technical drawing and mechanical drawing”, which greatly affects the quality and speed of engineering design. The purpose of this research is to develop a computer aided instruction system for mechanical drawing major of mechanical engineering department. This system is one of the attempts of the Department of mechanical engineering to develop a complete set of CAI system. A new multi-level structured manufacturing reuse model is proposed, which can obtain the abstract information, topological information and processing semantic information involved in manufacturing reuse. Firstly, machining features are identified from MBD model. Then, the clustering of coupled machining features is introduced to construct the structural elements whose granularity is larger than that of machining features. Finally, the MBD model is established through the hierarchical reorganization of machining features and the clustering of coupled machining features. The results show that the highest efficiency of JDBC is 31%, and the lowest portability of ASP is 20%.

Research on the Construction of a New System of Computer Based Whole Brain Physical Education Teaching and Training Method

With the introduction of artificial intelligence technology, the traditional teaching methods are no longer used in physical education. The traditional means are not competitive and can not mobilize the enthusiasm of students. However, the new computer-aided teaching has not been recognized by most physical education teachers. There are still great problems in this aspect. Computer aided instruction (CAI) has developed into intelligent computer aided instruction (ICAI). ICAI not only overcomes the weakness of traditional CAI, but also greatly improves the effect and efficiency of physical education. In this paper, the characteristics and functions of CAI system are analyzed, and a corresponding implementation framework is given.

A Probe into the Integration of Computer Technology and the Development of Aerobics with the Goal of “Two in One”

With the rapid development of computer technology, the application of computer technology in every corner of people’s production and life has become a general trend. At present, in order to achieve national fitness, improve the physical quality of the Chinese people and strengthen their physique, China is paying more and more attention to aerobics. As computer technology can effectively improve the shortcomings of traditional aerobics training methods, it is very necessary to apply computer technology in the development of aerobics. This study discusses the development process and characteristics of Chinese aerobics, the basic information of computer-aided instruction system and the way of applying computer technology in aerobics training, which provides a boost for realizing the goal of “two in one”.

Research on the realization of intelligent computer in assistant teaching

<p>The combination of artificial intelligence and computer-aided instruction (CAI) makes up for the original shortage and also improves the teaching quality of teachers and the learning efficiency of students. Based on the characteristics of the intelligent computer-aided instruction system, this paper analyzes the realization principle of the system, hoping to be helpful.</p>

Research on Intelligent Computer Aided Instruction System

This paper first outline the present conditions of Intelligent Computer Aided Instruction, then elaborate the contents of Intelligent Computer Aided Instruction system, and finally discuss the future development direction of the Intelligent Computer Aided Instruction system.

Design and Implement of Computer Aided Instruction System for Statistical Quality Control Based on Artificial Intelligence Technology

In order to design and implement a computer aided instruction system; the application of the artificial intelligence technology is studied in depth using statistical quality control as example. Firstly the statistical quality control teaching was analyzed. And then the design ideas of the computer aided instruction system are put forward. And then the structure of the expert teaching system is designed. And then the interacting ways of the expert system was analyzed. Finally the application of the expert teaching system was summarized.

The Design and Implementation of Plane Geometry's Computer Aided Instruction System Based on JXTA

The Design and Implementation of Plane Geometry's Computer Aided Instruction System Based on JXTA

Innovative Pathways to the Next Level of e-Learning

Debates about the future of e-learning have reached fever pitch in recent years as governments across the globe have increased investment in information and communication technologies (ICTs) in schools, universities, libraries, households and other locations where e-learning can take place. This paper aims to clarify the key issues of that debate, which started with computer-aided instruction systems in the 1960s, in order to offer a better understanding of the 'next level' of e-learning and how that might be reached. It does this by mining the discussion and other knowledge drawn from a policy forum organized by the Oxford Internet Institute (OII). After an Introduction that provides a more detailed overview of the main themes and conclusions summarized here, this paper explores the five key issues outlined above. In the final two sections, the authors suggest an analytical framework to help understand the issues raised and conclude with an examination of the main policy aspects of this analysis.

Java-based distance learning environment for electronic instruments

Computer-assisted instruction has been used to assist both teachers and students. Recently, the rapid emergence of the World Wide Web (WWW) and its associated tools have provided educators with an opportunity to incorporate this technology into their courses. The undergraduate students in the Mechanical Engineering Department utilize electronic instruments or mechanical instruments frequently. They learn how to use these instruments primarily through a teacher's oral instructions and demonstration. In this paper, the authors developed a computer-aided instruction (CAI) system consisting of four modules: information module, instrument module, examination module, and frequently asked question (FAQ) module. These four modules were arranged to implement a CAI system for electronic instruments. This system is used to teach students how to use oscilloscopes, function generators, and logic analyzers. The CAI system can be used for distance learning.

A conceptual map model for developing intelligent tutoring systems

With the recent rapid progress of computer technology, researchers have attempted to adopt artificial intelligence and use computer networks to develop computer-aided instruction systems. Meanwhile, researchers have also attempted to develop more effective programs to test and enhance the learning performance of students. However, conventional testing systems simply give students a score, and do not give them the opportunity to learn how to improve their learning performance. Students would benefit more if the test results could be analyzed and hence advice could be provided accordingly. This study proposes a conceptual map model, which provides learning suggestions by analyzing the subject materials and test results. A testing and diagnostic system is also implemented on computer networks based on the novel approach. Experimental results have demonstrated that the novel approach benefits students and deserves further investigation.

An overview of technological resources used in rehabilitation research with people with severe/profound and multiple disabilities

Purpose: This paper provides an outline of technological resources used in rehabilitation research with persons with severe/profound and multiple disabilities, and discusses the practicality of such resources. Method: Research articles published during the last 8 years (1993-2000) are considered. With regard to each of the technological resources used in the articles (i.e. microswitches, speech output devices, computer-aided instruction systems, audio recording systems, orientation systems, mobile robot, and SIBIS), accessibility, cost and implementation issues are examined. Results and Conclusions: Some technological resources are easily accessible and affordable (i.e. microswitches, speech output devices, audio-recording systems and SIBIS). Other resources are still at the prototype level (i.e. computer-aided instruction systems, orientation systems and robot) and are much more complex and costly. In spite of this, the latter resources might still have an important role in daily contexts.

3-4 機械材料・加工学学習用CAI教材の開発と有効性(技術教育(2))

3-4 機械材料・加工学学習用CAI教材の開発と有効性(技術教育(2))

A cross-national CAI tool to support learning operations decision-making and market analysis

THIS PAPER DESCRIBES THE DEVELOPMENT of a Computer-Aided Instruction (CAI) tool for learning management decision-making using advanced and traditional Computer Information Systems (CIS) technologies. Professors from Russia and the United States developed this tool, which differs substantially from earlier CAI systems in several ways: 1. It is cross-nationally useful since it has been used in Russia and the United States with the respective language modules integrated into the same tool, therefore, accommodating language differences; 2. It focuses on management decision-making learning as well as technical skills learning; 3. It integrates competitive (free) market and economic (controlled market) concepts and analysis; 4. It is able to measure not only results accurately but also, by increasing before and after tutorial answers, measure the impact of the system on the user’s ability to correctly reply to questions; and 5. It combines traditional computer technologies with artificial intelligence/expert system technologies.

A multi-agent architecture for teaching dermatology.

This work proposes the integration of computer-aided instruction systems in the curricula of medical education, and describes an intelligent tutoring system used for teaching Dermatology. The Dermatology Tutor uses a self-organized society of autonomous software agents which have different capabilities or roles. The society contains tutor, medical and information agents which participate in the tutoring process and collaborate through deliberation in order to achieve a tutoring task. The agents are built according to a BDI architecture, which implements the mental attitudes of beliefs (B), desires (D) and intentions (I). Each medical agent is a specialist in a medical field, while a tutoring agent, which implements a widely accepted dermatology teaching process, coordinates the overall operation of the system. Depending on the subject that is to be taught during any session, the tutoring agent forms teams of medical agents, which in turn use search agents to retrieve information. Although the presented multi-agent architecture is dedicated to teaching dermatology (since the tutor agent is specialized in Dermatology), it can be extended to other domains also with the incorporation of other tutor agents.

CAI-System Utilization in the Re-education of Older Drivers' Hazard Perception.

One important factor determining the road safety of older drivers is the degree of accuracy in self-assessment of ability. In particular, exaggerated degree of self-confidence can contribute to unsafe behavior. The author conducted an experimental re-education program for older drivers in conjunction with the renewal of their driver’s licenses. The aim of the program was to offer older drivers an opportunity to reevaluate their own safety in driving, especially their hazard-perceptual ability on the road. Before and after the education program with the use of a CAI (Computer Aided Instruction) system, the participants were asked to evaluate their ability and identify their problem areas in hazard erception. The analysis examines the effect of the education program on participants’ driving behavior by noting changes in the assessment of their own level of safety.