Judy C. R. Tseng

A two-tier test approach to developing location-aware mobile learning systems for natural science courses

The advancement of wireless and mobile technologies has enabled students to learn in an environment that combines learning resources from both the real world and the digital world. Although such an approach has been recognized as being innovative and important, several problems have been revealed in practical learning activities. One major problem is owing to the lack of proper learning strategies or tools for assisting the students to acquire knowledge in such a complex learning scenario. Students might feel excited or engaged when using the mobile devices to learn in the real context; nevertheless, their learning achievements could be disappointing. To deal with this problem, this study presents a mobile learning system that employs Radio Frequency Identification (RFID) technology to detect and examine real-world learning behaviors of students. This study also utilizes each students responses from a two-tier test (i.e., multiple-choice questions in a two-level format) to provide personalized learning guidance (called two-tier test guiding, T^3G). The experimental results from a natural science course of an elementary school show that this innovative approach is able to improve the learning achievements of students as well as enhance their learning motivation.

Development of an adaptive learning system with two sources of personalization information

Previous research of adaptive learning mainly focused on improving student learning achievements based only on single-source of personalization information, such as learning style, cognitive style or learning achievement. In this paper, an innovative adaptive learning approach is proposed by basing upon two main sources of personalization information, that is, learning behavior and personal learning style. To determine the initial learning styles of the students, the [Keefe, J. W. (1987). Learning Styles: Theory and Practice. Reston, VA: National Association of Secondary School Principals.] questionnaire is employed in our approach. To more precisely reflect the learning behaviors of each student, the interactions and learning results of each student are analyzed when adjusting the subject materials. Based on the innovative approach, an adaptive learning system has been developed; moreover, an experiment was conducted to evaluate the performance of our approach. By analyzing the results from three groups of students using different adaptive learning approaches, it can be found that the innovative approach is helpful in improving both the learning achievement and learning efficiency of individual students.

An adaptive navigation support system for conducting context-aware ubiquitous learning in museums

In context-aware ubiquitous learning, students are guided to learn in the real world with personalized supports from the learning system. As the learning resources are realistic objects in the real world, certain physical constraints, such as the limitation of stream of people who visit the same learning object, the time for moving from one object to another, and the environmental parameters, need to be taken into account. Moreover, the values of these context-dependent parameters are likely to change swiftly during the learning process, which makes it a challenging and important issue to find a navigation support mechanism for suggesting learning paths for individual students in real time. In this paper, the navigation support problem for context-aware ubiquitous learning is formulated and two navigation support algorithms are proposed by taking learning efficacy and navigation efficiency into consideration. From the simulation results of learning in a butterfly museum setting, it is concluded that the innovative approach is helpful to the students to more effectively and efficiently utilize the learning resources and achieve better learning efficacy.

Development of a Ubiquitous Learning Platform Based on a Real-Time Help-Seeking Mechanism.

The popularity of mobile devices has encouraged the advance of ubiquitous learning, in which students are situated in a real-world learning environment with support from the digital world via the use of mobile, wireless communications, or even sensing technologies. Most of the ubiquitous learning systems are implemented with high-cost sensing devices for detecting the locations or behaviours of learners; moreover, these systems mainly focus on providing learning guidance or learning materials, while facilities for supporting mutual help among students are usually ignored. In this study, we propose a context-aware ubiquitous learning platform (CULP) which uses low-cost cell phones with embedded cameras and Internet service to support ubiquitous learning. CULP is able to provide instant support for learners in the ubiquitous learning activity; that is, learners can receive help from the right people via the hints given by the learning system when they encounter problems during their learning activities. The experimental results of a Personal Computer-Assembling course show that, with the assistance of the new learning platform, both the learning efficiency and the learning achievement of the students were significantly improved. [ABSTRACT FROM AUTHOR]

A Group-Decision Approach for Evaluating Educational Web Sites.

With the advent of network technologies, many educational web sites have been developed to assist students in the learning of subjects on computer networks. However, without proper aid, students may have difficulty in selecting appropriate web sites, that are of benefit to them; hence, studying, evaluating and recommending educational web sites has become an important and challenging issue. In this paper, a group-decision approach is proposed for evaluating educational web sites. Several soft computing technologies have been employed in the approach, including fuzzy theory, grey system and group decision method. A computer-assisted web site evaluation system, EWSE (Educational Web Site Evaluator), has been developed, based on an experimental approach, which is capable of selecting the proper criteria for an individual web site and achieves greater accuracy when evaluating results. # 2003 Elsevier Ltd. All rights reserved.

Diagnosing student learning problems based on historical assessment records

In the past decade, researchers have attempted to develop computer‐assisted learning and testing systems to help students improve their learning performance. Conventional testing systems simply provide students with a score, and do not offer sufficient information in order to improve their learning performance. It would be of more benefit to students if the test results could be critically analysed and hence learning suggestions could be offered accordingly. This study proposes an algorithm for diagnosing students’ learning problems and provides personalised learning suggestions for Science and Mathematics courses. An intelligent tutoring, evaluation and diagnosis system has been implemented based on the novel approach. Experimental results on a Mathematics course have demonstrated the feasibility of this approach in enhancing students’ learning performance, making it highly promising for further study.

An auto-scoring mechanism for evaluating problem-solving ability in a web-based learning environment

The rapid development of computer and network technologies has attracted researchers to investigate strategies for and the effects of applying information technologies in learning activities; simultaneously, learning environments have been developed to record the learning portfolios of students seeking web information for problem-solving. Although previous research has demonstrated the benefits of applying information technologies to learning activities, the difficulties in doing so have also been revealed. One of the major difficulties is the lack of a mechanism to assist teachers in evaluating the problem-solving ability of the students, such that constructive suggestions can be given to the students, and tutoring strategies can be improved accordingly. To cope with this problem, in this paper, an auto-scoring mechanism is developed to analyze the various information searching abilities of individual students. Indicators of information searching ability (ISA) are proposed based on the famous Big6 model and are adopted in our auto-scoring mechanism. Moreover, two experiments have been conducted to demonstrate the effectiveness of this innovative approach. The experimental results show high correlation between the scores of the auto-scoring mechanism and the manual scoring. Moreover, the feedbacks from 158 teachers also show that the innovative approach is highly accepted by the teachers.

Development of an automatic customer service system on the internet

Most existing network-based customer services heavily rely on manpower in replying e-mails or on-line requests from customers, which not only increases the service cost, but also delay the time for responding the service requests. To cope with these problems, this paper proposes a customer service system, which can automatically handle customer requests by analyzing the contents of the requests and finding the most feasible answers from the frequently asked question (FAQ) database. In the situation that a customer is not satisfied with the reply, the system will forward the request to the appropriate service personnel for further processing. An assistance mechanism has been developed to help the service personnel in finding potential answers from existing FAQ data or creating more appropriate answers. Experimental results on practical applications showed that over 87.3% of users were satisfied with the replies given by the system; therefore, we conclude that the system can significantly reduce the service cost and provide more efficient and effective customer service.

I-WAP: an intelligent WAP site management system

The popularity regarding wireless communications is such that more and more WAP sites have been developed with wireless markup language (WML). Meanwhile, to translate hypertext markup language (HTML) pages into proper WML ones becomes imperative since it is difficult for WAP users to read most contents designed for PC users via their mobile phone screens. However, for those sites that have been maintained with hypertext markup language (HTML), considerable time and manpower costs will be incurred to rebuild them with WML. In this paper, we propose an intelligent WAP site management system to cope with these problems. With the help of the intelligent management system, the original contents of HTML Web sites can be automatically translated to proper WAP content in an efficient way. As a consequence, the costs associated with maintaining WAP sites could be significantly reduced. The management system also allows the system manager to define the relevance of numerals and keywords for removing unimportant or meaningless contents. The original contents will be reduced and reorganized to fit the size of mobile phone screens, thus reducing the communication cost and enhancing readability. Numerical results gained through various experiments have evinced the effective performance of the WAP management system.

A hybrid linear text segmentation algorithm using hierarchical agglomerative clustering and discrete particle swarm optimization

Linear text segmentation plays an important role in many natural language processing tasks. Many algorithms have been proposed and shown to improve the performance of linear text segmentation. However, the previous studies often suffer from either lower segmentation accuracy or higher computational complexity. Moreover, parameter setting is another critical problem in some algorithms. Although manual assignment is an approach to solve this problem, it may increase the users burden, and the parameters provided may not always be suitable to reflect the real metadata of a text. In this paper, a hybrid algorithm, TSHAC-DPSO, is proposed to tackle these problems. A novel linear Text Segmentation algorithm based on Hierarchical Agglomerative Clustering TSHAC is proposed to rapidly generate a satisfactory solution without an auxiliary knowledge base, parameter setting, or user involvement; then an efficient evolutional algorithm, Discrete Particle Swarm Optimization DPSO, is adopted to generate the global optimal solution by refining the solution created by TSHAC. TSHAC-DPSO fully utilizes the merits of both algorithms which not only improve the accuracy of linear text segmentation, but also make the execution more efficient and flexible. The experimental results show that TSHAC-DPSO provides comparable segmentation accuracy with several well-known linear text segmentation algorithms.