Hsuan-Pu Chang

Using RFID technology to develop an attendance system and avoid traffic congestion around kindergartens

This paper aims at developing applications based on active RFID and wireless GSM message to construct an active student attendance system that sends the message to parents cellular phone informing whether their children are safely arrive in classroom at morning. Meanwhile, the system is also used to relieve the traffic congestion around kindergartens especially while the parents are driving cars to pick up their children after class at rush or on rainy days. Finally, the encountered problems are summarized to discuss according to our developing experience.

The hard SCORM LMS: reading SCORM courseware on hardcopy textbooks

The sharable content object reference model (SCORM) includes a representation of distance learning contents and a behavior definition of how users should interact with the contents. Usually, SCORM-compliant systems are developed based on Web browsers or Java program. We developed a system which allows users to read SCORM-compliant course materials on hardcopy papers while an OCR-like pen device is used as an interaction mechanism. A computer, a PDA, or a cellular phone can be used in conjunction with the pen device for multimedia presentations. Our project is called the hard SCORM. Therefore, users can read textbooks in a traditional manner while behavior of reading is incorporated with the SCORM specification.

Adaptive pocket SCORM reader

Pocket devices are dominated in size which makes them the perfect platform for mobile learning. Several researches propose how distance education can be realized on pocket devices. We demonstrate the implementation of the adaptive pocket SCORM (scalable content object reference model) reader. Our proposed pocket SCORM reader is able to load SCORM compatible courseware. Furthermore, we introduce our ideal pocket SCORM architecture. With the proposed architecture, we hope to realize SCORM compliant mobile learning.

A cognition assessment authoring system for e-learning

With the rapidly development of distance learning and the XML (Extensible Markup Language) technology, metadata becomes an important item in an e-learning system. Today, many distance learning standards such as SCORM, AICC CMI, IEEE LTSC learning object meta-data (LOM), and IMS learning resource metadata XML binding specification, use metadata to tag learning materials, shareable content objects, and learning resources. However, most metadata is used to define learning materials and test problems. Few metadata is dedicated for assessment in learning. We propose an assessment metadata model for e-learning operations. With the support from the assessment metadata, we can collect information at the question cognition level, item difficulty index, item discrimination index, questionnaire style, and question style. The assessment analysis model provides individual questions, summary of test results, and analytical suggestions. The suggestions and results can tell teachers why a question is not suitable and how to correct it. Teachers can see the analysis of test result and fix problematic questions. With the cognition level analysis, teachers can avoid missing items in teaching. The mechanism developed also suggests an e-learning system, with adaptive learning content and individualized tests, as well as good advice for the teachers.

Reading SCORM compliant multimedia courses using heterogeneous pervasive devices

The Sharable Content Object Reference Model (SCORM) provides some important representation for distance learning content and the learning behavior. In general, SCORM-Compliant learning content can be viewed via the Web browsers. In this paper, we built an environment which allows people to read SCORM-Compliant course materials on hardcopy papers with a pen-like OCR device. A computer, a PDA, or a cellular phone can be used in conjunction with the pen device for multimedia presentations. Our project is called the Hard SCORM. Consequently, users can read textbooks in a traditional manner while behavior of reading is incorporated with the SCORM specification.

A Semiautomatic Content Adaptation Authoring Tool for Mobile Learning

A lot of studies about automatic content adaptation have been done and are proposed to overcome the drawbacks of browsing regular content with handheld devices such as pocket PCs and smartphones. But we argue that the total automatic adaptation algorithm designed by an engineer to transform Web Page presentation is still appropriate to be applied on educational content. Therefore, this paper proposes a learning content adaptation tool that provides different adaptation templates to help the author automatically and efficiently reproduce high-quality learning content for specific handhelds. Furthermore, the author will not only be able to preview the adaptation result before publishing the course but also be able to adjust the template parameters manually to affect the process if they are not satisfied with the current result. Finally the new adapted content can be packaged with original content as a multi-version learning course.

A Learning Content Adaptation Tool with Templates for Different Handhelds

A large number of excellent digital learning materials have been created and distributed for e- learning. These contents are mostly designed for reading on regular PCs that have big screens, powerful computing, large storage and wide bandwidth compared to handheld devices. Therefore, a lot of studies about automatic content adaptation have been done and are proposed to overcome the drawbacks of browsing regular content with handheld devices such as pocket PCs and smartphones. But we argue that the total automatic adaptation algorithm designed by an engineer to transform Web Page presentation is still appropriate to be applied on educational content. We believe the quality of the result can not be assured and supervised by educators, and educational essence may be damaged during the real time adaptation process. This paper proposes a content adaptation tool that provides different adaptation templates to help the author automatically and efficiently reproduce high-quality learning content for specific handhelds. Furthermore, the author will not only be able to preview the adaptation result before publishing the course but also be able to adjust the template parameters manually to affect the process if they are not satisfied with the current result.

SCORM sequencing testing for sequencing control mode

In SCORM 2004 defines the sequencing information that describes how SCORM-conformant content may be sequenced to the learner through a set of learner or system-initiated navigation events. It provides users the ability to prescribe the intend learning sequencing strategy by themselves, but quit many completed definitions and lacking the testing mechanism for these authored sequencing information results in usual developers probably design the unreasonable or careless settings of SCORM sequencing. The detecting mechanism focuses on detecting improper setting of sequencing control mode elements applied to learning activities. An assistant truth table derived from the definitions of sequencing control mode elements and experiments verified with latest ADL runtime environment will be introduced.

A learning sequencing prediction system for ubiquitous learning based on SCORM sequencing and navigation

This paper proposes a learning sequencing prediction system which applies the caching concept to improve the efficiency for ubiquitous learning and overcome the problems encountered in the usage of mobile devices as learning platforms. Two of the main problems are considered. First, the impermanent network environment due to insufficient coverage or wireless link failure leads to the continuous interruptions during learning process. Second, conversely the persistent connection offered by cellular phones using a telecommunication protocol, but with a relatively weak computing power and very limited network bandwidth which makes ubiquitous learning or m-learning become a time-consuming process. Moreover, learning contents are currently composed of various multimedia resources that induce long latency to display on handheld devices such as smartphones with GPRS. Recently, a lot of e-learning systems and contents have conformed to the sharable content object reference model (SCORM) since it was introduced by ADL in the late 90s. The sequencing and navigation (S&N) specification is an important part of SCORM. S&N is defined to prescribe the intended studentpsilas learning sequence by instructors. In this paper, we propose an adaptive learning sequencing prediction strategy based on the S&N specification in a ubiquitous learning environment.

An intelligent travel note management application using agent technologies

Many people love traveling for entertainment nowadays. In a journey, visitors often produce digital multimedia resources by capturing images, audios and videos. With digital devices like cameras, travel notes are not limited to texts, multimedia resources are also used for decorating records in a journey. In this paper, an intelligent travel note application is proposed to save time for creating travel notes. Visitors can use handheld mobile devices like PDA to capture photos or videos and collect related resources from internet by an agent. With the GPS functionalities provide by mobile devices, precise location coordinates can be obtained for further analysis and search. Visitors can focus on activities and sightseeing in a journey without dealing with complicated operations of creating travel notes. The intelligent travel note management application is designed for helping visitors to easily record and share wonderful experience in a journey via internet.