A Distance Learning System for Teaching the Writing of Chinese Characters Over the Internet

This chapter proposes an intelligent tutoring system (ITS) for teaching students to write Chinese characters over the Internet. Since each Chinese character is like a picture, knowing the correct stroke orders can enable a person to write characters more easily. Accordingly, primary schools in Taiwan teach the correct orders in which strokes should be made when writing Chinese characters. In the proposed system, students can use a pen (or drag the mouse) to write Chinese characters on a digital board through a browser such as Microsoft Internet Explorer. For realizing the situation of student’s writing behavior, a neuron-based student model was designed to learn the writing style of each student. When a wrong stroke order is used, a short animated cartoon is displayed to show the error to the student, and the reason for the error will be explained. An intelligent tutoring module selects a Chinese character that is similar to the character written with the wrong stroke order, to teach the student again. Several databases and rule-bases are used to store important information such as the correct stroke orders and the structure of each Chinese character, the screen positions of each stroke, the writing behavior of each student, the rules of inference by which training characters are selected, and the error codes (types). This system has been in development since 1996, and includes 2734 Chinese characters (taught in primary schools). It has been used in elementary schools, and by thousands of students. Educational research reveals that over 82% of primary school students had some problems in using the correct stroke orders when writing Chinese characters, and the improvement exhibited by the experimental group was significant (F = 25.331, p < .005). The proposed system has been verified as being of high value in teaching students to write Chinese characters.

Using Ontology as Scaffolding for Authoring Teaching Materials

The purpose of this study is to conduct teachers to author a teaching material by using visualized domain ontology as scaffolding. Based on a content repository management system (CRMS), mathematics ontology to support teachers for authoring teaching materials is developed. Although the domain ontology of mathematics at secondary school level in Taiwan provides structured vocabularies for describing domain content, those teachers who want to create a knowledge-rich description of domain knowledge, such as required by the “Semantic Web,” use ontology that turns out to provide only part of knowledge required. In this chapter, we examine problems related to capturing the learning resources or learning objects (LOs) on a CRMS. To construct ontology for a subset of mathematics course descriptions, the representation requirements by resource description framework/resource description framework schema (RDF/RDFS) was implemented. Furthermore, a visualized online authoring tool (VOAT) is designed for authoring teaching materials on the Web. Finally, discussion and future research are addressed.

Concept Effect Model

With the recent rapid progress of network technology, researchers have attempted to adopt artificial intelligence and use computer networks to develop adaptive hypermedia systems. The idea of adaptive hypermedia is to adapt the course content for a particular learner based on the profile or records of the learner. Meanwhile, researchers have also attempted to develop more effective programs to evaluate the student learning problems, so that the adaptive hypermedia systems can adapt displayed information and dynamically support navigation accordingly. 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. Concept effect model is an effective approach to coping with this problem. In this Chapter, the model and its relevant work are introduced.

Bluetooth Scatternet Using an Ad Hoc Bridge Node Routing Protocal for Outdoor Distance Education

In recent years, the prevalence of Internet and wireless technology has promoted mobile communications as a major research area. For the future distance education purposes (Instructional Technology Council), to be able to access the course materials anytime and everywhere will become a key issue. Especially when students are out of classroom and are within a museum or a field investigation process, using Ad Hoc mechanism to access the real time brief or introduction can definitely improve their learning interests greatly. One of the topics is IEEE802.11, which includes the wireless LAN and mobile ad hoc network (MANET) infrastructure (Perkins, 2000). MANET has no fixed infrastructure, but capable of dynamic changing network architectures, such as PDAs, cellular phones, and mobile computers. Bluetooth (The Official Bluetooth SIG) possesses a smaller radio range, low power, and low costs. The Bluetooth Scatternet is a specific case of MANET (IETF MANET Working Group). In this chapter, we propose a bridge node routing protocol (BNRP) based on a revised distributed topology construction protocol (DTCP), which a shortcut mechanism is added into it for better performance. The BNRP uses bridge nodes to preserve effective transmissions and achieve better Bluetooth Scatternet performance, and it can apply for outdoor distance education environment anytime and everywhere.

A Survey of Distance Education Challenges and Technologies

Distance education, e-learning, and virtual university are similar terms for a trend of modern education. It is an integration of information technologies, computer hardware systems, and communication tools to support educational professionals in remote teaching. This chapter presents an overview of distance education from the perspective of policy, people, and technology. A number of questions frequently asked in distance learning panel discussions are presented, with the suggested answers from the authors. The survey presented in this chapter includes communication, intelligent, and educational technologies of distance education. Readers of this chapter are academic researchers and engineers who are interested in new research issues of distance education, as well as educators and general participants who are seeking for new solutions.

Privacy and Security in E-Learning

For a variety of advantages, universities and other organizations are resorting to e-learning to provide instruction online. While many advances have been made in the mechanics of providing online instruction, the needs for privacy and security have to-date been largely ignored. This chapter examines privacy and security issues associated with e-learning. It presents the basic principles behind privacy practices and legislation. It investigates the more popular e-learning standards to determine their provisions and limitations for privacy and security. Privacy requirements for e-learning systems are explored with respect to the “privacy principles.” The capabilities of a number of existing privacy enhancing technologies, including methods for network privacy, policy-based privacy/security management, and trust systems, are reviewed and assessed.

A Virtual Laboratory for Digital Signal Processing

This work designs and implements a virtual digital signal processing laboratory, VDSPL. VDSPL consists of four parts: mobile agent execution environments, mobile agents, DSP development software, and DSP experimental platforms. The network capability of VDSPL is created by using mobile agent and wrapper techniques without modifying the source code of the original programs. VDSPL provides human-human and human-computer interaction for students and teachers, and it can also lighten the loading of teachers, increase the learning result of students, and improve the usage of network bandwidth. A prototype of VDSPL has been implemented by using the IBM Aglet system and Java Native Interface for DSP experimental platforms. Also, experimental results demonstrate that our system has received many positive feedbacks from both students and teachers.

Open Multi-Agent Systems for Collaborative Web-Based Learning

Web-based learning plays an important role in modern teaching environment. Many Web based tools are becoming available on this huge marketplace. Agent technology contributes substantially to this achievement. One of the fundamental problems facing both students and education services providers is how to locate and integrate these valuable services in such a dynamic environment. In this chapter, I present mediator-based architecture to build open multi-agent applications for e-learning. An agent services description language is presented to enable services advertising and collaboration. The language exploits ontology of service domain, and provides the flexibility for developers to plug in any suitable constraint languages. Multiple matchmaking strategies based on agent service ontology are given to help agents finding appropriate service providers. The series of strategies consider various features of service providers, the nature of requirements, and more importantly the relationships among services.

An XML-Based Approach to Multimedia Engineering for Distance Learning

Multimedia software engineering (MSE) is a new frontier for both software engineering (SE) and visual languages (VL). In fact, multimedia software engineering can be considered as the discipline for systematic specification, design, substitution, and verification of visual patterns. Visual languages contribute to MSE such concepts as: Visual notation for software specification, design, and verification flow charts, ER diagrams, Petri nets, UML visualization, visual programming languages, etc. Multimedia software engineering and software engineering are like two sides of the same coin. On the one hand, we can apply software engineering principles to the design of multimedia systems. On the other hand, we can apply multimedia technologies to the software engineering practice. In this chapter, we concentrate on the first of these possibilities. One of the promising application areas for multimedia software engineering is distance learning. One aim of this chapter is to demonstrate how it is possible to design and to implement complex multimedia software systems for distance learning using a tele-action object transformer based on XML technology applying a component-based multimedia software engineering approach. The chapter shows a complete process of dataflow transformation that represents TAO in different ways (text, TAOML, etc.) and at different levels of abstraction. The transformation process is a reversible one. A component-based tool architecture is also discussed. We also show the first experiments conducted jointly using the TAOML_T tool. The use of an XML-based approach in the distance learning field has other advantages as well. It facilitates reuse of the teaching resources produced in preceding decades by universities, schools, research institutions, and companies by using metadata. The evolution of the technologies and methodologies underlying the Internet has provided the means to transport this material. On the other hand, standards for representing multimedia distance learning materials are currently evolving. Such standards are necessary in order to allow a representation which is independent of hardware and software platforms so that this material can be examined, for example, in a Web browser or so that it may be reused in whole or in part in other chapters of a book or sections of a course distinct from that for which it was originally developed. Initial experiments in reuse of distance learning carried out at the University of Naples, Kent State University, and Cleveland State University are described. The authors have also developed a collaboration environment through which the resources can be visualized and exchanged.

Interactive E-Learning

This chapter introduces the concept of improving student memory retention using a distance learning tool by establishing the student’s communication preference and learning style before the student uses the module contents. It argues that incorporating a distance learning tool with an intelligent/interactive tutoring system using various components (psychometric tests, communication preference, learning styles, mapping learning/teaching styles, neurolinguistic programming language patterns, subliminal text messaging, motivational factors, novice/expert factor, student model, and the way we learn) combined in WISDeM to create a human-computer interactive interface distance learning tool does indeed enhance memory retention. The authors show that WISDeM’s initial evaluation indicates that a student’s retained knowledge has been improved from a mean average of 63.57% to 71.09% — moving the student from a B to an A.