A Chinese Interactive Feedback System for a Virtual Campus

Considering the popularity of the Internet, an automatic interactive feedback system for E-learning websites is becoming increasingly desirable. However, computers still have problems understanding natural languages, especially the Chinese language, firstly because the Chinese language has no space to segment lexical entries (its segmentation method is more difficult than that of English) and secondly because of the lack of a complete grammar in the Chinese language, making parsing more difficult and complicated. Building an automated Chinese feedback system for special application domains could solve these problems. This paper proposes an interactive feedback mechanism in a virtual campus that can parse, understand and respond to Chinese sentences. This mechanism utilizes a specific lexical database according to the particular application. In this way, a virtual campus website can implement a special application domain that chooses the proper response in a user friendly, accurate and timely manner.

Distance-Learning for Advanced Military Education

Distance learning in advanced military education can assist officers around the world to become more skilled and qualified for future challenges. Through well-chosen technology, the efficiency of distancelearning can be improved significantly. In this paper we present the architecture of Advanced Military Education – Distance Learning (AME-DL) prototype for advanced military distance-learning, it combines advanced e-learning tool, simulation technology, and Web technology to provide a set of military learning and training subjects that can be accessed easily anywhere, anytime through a Web browser. The major goal of AME-DL is to provide a common standard framework for military training program, and the major contribution for such a prototype is to reduce training cost while providing high quality learning experience.

Enhanced Speech-Enabled Tools for Intelligent and Mobile E-Learning Applications

Web-based learning is rapidly becoming the preferred way to quickly, efficiently, and economically create and deliver training or educational content through various communication media. This chapter presents systems that use speech technology to emulate the one-on-one interaction a student can get from a virtual instructor. A Web-based learning tool, the Learn IN Context (LINC+) system, designed and used in a real mixed-mode learning context for a computer (C++ language) programming course taught at the Université de Moncton (Canada) is described here. It integrates an Internet Voice Searching and Navigating (IVSN) system that helps learners to search and navigate both the web and their desktop environment through voice commands and dictation. LINC+ also incorporates an Automatic User Profile Building and Training (AUPB&T) module that allows users to increase speech recognition performance without having to go through the long and fastidious manual training process. New Automated Service Agents based on the Artificial Intelligence Markup Language (AIML) are used to provide naturalness to the dialogs between users and machines. The portability of the e-learning system across a mobile platform is also investigated. The findings show that when the learning material is delivered in the form of a collaborative and voice-enabled presentation, the majority of learners seem to be satisfied with this new media, and confirm that it does not negatively affect their cognitive load.

A Computer-Assisted Approach to Conducting Cooperative Learning Process

Cooperative learning has been proven to be helpful in enhancing the learning performance of students. The goal of a cooperative learning group is to maximize all members’ learning, which is accomplished via promoting each other’s success, through assisting, sharing, mentoring, explaining, and encouragement. To achieve the goal of cooperative learning, it is very important to organize well-structured cooperative learning groups, in which all group members have the ability to help each other during the learning process. In this article, a concept-based approach is proposed to organize cooperative learning groups, such that, for a given course each concept is precisely understood by at least one of the students in each group. An experiment on a computer science course has been conducted in order to evaluate the efficacy of this new approach. From the experimental results, we conclude that the novel approach is helpful in enhancing student learning efficacy.

A Methodology for Developing Learning Objects for Web Course Delivery

This article presents a methodology for developing learning objects for web-based courses using the IMS Learning Design (IMS LD) specification. We first investigated the IMS LD specification, determining how to use it with online courses and the student delivery model, and then applied this to a Unit of Learning (UOL) for online computer science courses. We developed an editor and runtime environment to apply the IMS LD to a UOL. We then explored the prospect for advancement of the basic IMS LD UOL. Finally, we discussed how to construct ontology-based software agents to use with the learning objects created with the IMS LD Units of Learning.

Using a User-Interactive QA System for Personalized E-Learning

A personalized e-learning framework based on a user-interactive question-answering (QA) system is proposed, in which a user-modeling approach is used to capture personal information of students and a personalized answer extraction algorithm is proposed for personalized automatic answering. In our approach, a topic ontology (or concept hierarchy) of course content defined by an instructor is used for the system to generate the corresponding structure of boards for holding relevant questions. Students can interactively post questions, and also browse, select, and answer others’ questions in their interested boards. A knowledge base is accumulated using historical question/answer (Q/A) pairs for knowledge reuse. The students’ log data are used to build an association space to compute the interest and authority of the students for each board and each topic. The personal information of students can help instructors design suitable teaching materials to enhance instruction efficiency, be used to implement the personalized automatic answering and distribute unsolved questions to relevant students to enhance the learning efficiency. The experiment results show the efficacy of our user-modeling approach.

Quasi-Facial Communication for Online Learning Using 3D Modeling Techniques

Online interaction with 3D facial animation is an alternative way of face-to-face communication for distance education. 3D facial modeling is essential for virtual educational environments establishment. This article presents a novel 3D facial modeling solution that facilitates quasi-facial communication for online learning. Our algorithm builds 3D facial models from a single image, with support of a 3D face database. First from the image, we extract a set of feature points, which are then used to automatically estimate the head pose parameters using the 3D mean face in our database as a reference model. After the pose recovery, a similarity measurement function is proposed to locate the neighborhood for the given image in the 3D face database. The scope of neighborhood can be determined adaptively using our cross-validation algorithm. Furthermore, the individual 3D shape is synthesized by neighborhood interpolation. Texture mapping is achieved based on feature points. The experimental results show that our algorithm can robustly produce 3D facial models from images captured in various scenarios to enhance the lifelikeness in distant learning.

Multipoint Multimedia Conferencing System for Efficient and Effective Remote Collaboration

A multipoint, multimedia conferencing system called FocusShare is described. It uses IPv6/IPv4 multicasting for real-time collaboration, enabling video, audio, and group-awareness and attention-sharing information to be shared. Multiple telepointers provide group-awareness information and make it easy to share attention and intention. In addition to pointing with the telepointers, users can add graphical annotations to video streams and share them with one another. The system also supports attention-sharing using video processing techniques. FocusShare is a modularly designed suite consisting of several simple tools, along with tools for remotely controlling them. The modular design and flexible management functions enable the system to be easily adapted to various situations entailing different numbers of displays with different resolutions at multiple sites. The remote control tools enable the chairperson or conference organizer to simultaneously change the settings for a set of tools distributed at multiple sites. Evaluation showed that the implemented attention-sharing techniques are useful: FocusShare was more positively evaluated than conventional video conferencing systems.

Collaborative E-Learning Using Semantic Course Blog

Collaborative e-learning delivers many enhancements to e-learning technology; it enables students to collaborate with each other and improves their learning efficiency. Semantic blog combines semantic Web and blog technology that users can import, export, view, navigate, and query the blog. We developed a semantic course blog for collaborative e-learning. Using our semantic course blog, instructors can import the lecture course. Students can team up for projects, ask questions, mutually discuss problems, take the comments, support answers, and query the blog information. This semantic course blog provided a platform for collaborative e-learning framework. In this chapter, we described some collaborative e-learning and semantic blog technology, and then we introduced functions, implementation and how collaborative e-learning appears in semantic course blog.

Toward Development of Distance Learning Environment in the Grid

In recent years, with the rapid development of communication and network technologies, distance learning has been popularized and it became one of the most well-known teaching methods, due to its practicability. Over the Internet, learners are free to access new knowledge without restrictions on time or location. However, current distance learning systems still present restrictions, such as support to interconnection of learning systems available in scalable, open, dynamic, and heterogeneous environments. In this chapter, we introduce a distance learning platform based on grid technology to support learning in distributed environments, where open source and freely available learning systems can share and exchange their learning and training contents. We have envisioned such distance learning platform in heterogeneous environment using grid technology. A prototype is designed and implemented, to demonstrate its effectiveness and friendly interaction between learner and learner resources used.