• Knowledge Management Research
• /
• v.9 no.4
• /
• pp.17-33
• /
• 2008

This study proposes University 2.0 as a model case of open, flexible, and distributed learning environment for higher education based on theoretical foundations and perspectives. As web 2.0 technologies emerge into the field of education, ways of generating and disseminating information and knowledge have been drastically changed. Professors are no longer the only source of knowledge. Students using internet often become prosumers of knowledge who search and access information through the web as well as publish their own knowledge using the web. A concept and framework of University 2.0 is introduced for implementing the new interactive learning paradigm with an open, flexible and distributed learning environment for higher education. University 2.0 incorporates online and offline learning environments with various educational media. Furthermore, it employs various learning strategies and integrates formal and informal learning through learning communities. Both instructors and students in University 2.0 environment are expected to be active knowledge generators as well as creative designers of their own learning and teaching.

• International Journal of Computer Science & Network Security
• /
• v.21 no.1
• /
• pp.125-136
• /
• 2021

The development of systems that can generate automatically instructional material is a challenging goal for the e-learning community. These systems pave the way towards large scale e-learning deployment as they produce instruction on-demand for users requesting to learn about any topic, anywhere and anytime. However, realizing such systems is possible with the availability of vast repositories of web information in different formats that can be searched, reused and integrated into information-rich environments for interactive learning. This paradigm of learning relieves instructors from the tedious authoring task, making them focusing more on the design and quality of instruction. This paper presents a mobile learning system (Mole) that supports the generation of instructional material in M-Learning (Mobile Learning) contexts, by reusing and integrating heterogeneous hypermedia web resources. Mole uses open hypermedia repositories to build a Learning Web and to generate learning objects including various hypermedia resources that are adapted to the user context. Learning is delivered through a nice graphical user interface allowing the user to navigate conveniently while building their own learning path. A test case scenario illustrating Mole is presented along with a system evaluation which shows that in 90% of the cases Mole was able to generate learning objects that are related to the user query.

• International conference on construction engineering and project management
• /
• 2020.12a
• /
• pp.137-145
• /
• 2020

Providing safety training to construction workers is essential to reduce safety accidents at the construction site. With the prosperity of visualization technologies, Immersive Virtual Reality (IVR) has been adopted for construction safety training by providing interactive learning experiences in a virtual environment. Previous research efforts on IVR-based training have found that the level of fidelity of interaction between real and virtual worlds is one of the important factors contributing to the sense of presence that would affect training performance. Various interactive devices that link activities between real and virtual worlds have been applied in IVR-based training, ranging from existing computer input devices (e.g., keyboard, mouse, joystick, etc.) to specially designed devices such as high-end VR simulators. However, the need for high-fidelity interactive devices may hinder the applicability of IVR-based training as they would be more expensive than IVR headsets. In this regard, this study aims to understand the impact of the level of fidelity of interactive devices in the sense of presence in a virtual environment and the training performance during IVR-based forklift safety training. We conducted a comparative study by recruiting sixty participants, splitting them into two groups, and then providing different interactive devices such as a keyboard for a low fidelity group and a steering wheel and pedals for a high-fidelity group. The results showed that there was no significant difference between the two groups in terms of the sense of presence and task performance. These results indicate that the use of low-fidelity interactive devices would be acceptable for IVR-based safety training as safety training focuses on delivering safety knowledge, and thus would be different from skill transferring training that may need more realistic interaction between real and virtual worlds.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.4
• /
• pp.119-129
• /
• 2009

In The increasing use of computers and high-speed Internet network has greatly influenced education, causing a veering away from the typical and traditional way of delivering instruction. Specifically, the various kinds of Web-based multimedia technology, the interactive activities on the Internet, and satellite broadcasting technology are accelerating the emergence of a virtual-lectures-based educational model, which transcends time and space. Such virtual lectures make it possible for the entire teaching-learning process to be done in a virtual learning environment, thus giving rise to problem regarding learning guidance, feedback, and appraisal. In this paper, we propose a system for attendance appraisal for learner participation degree based virtual lecture, an appraisal element in virtual learning environments. This appraisal model can set the elements of virtual learning environments in such a way as to reflect in the attendance appraisal of the opened virtual learning environment information regarding the learner's participation in class. In addition, this model motivates the learners to actively participate in the virtual learning environment and to support instructors by accomplishing the activities that are needed for attendance appraisal.

• Journal of KIISE:Computer Systems and Theory
• /
• v.33 no.4
• /
• pp.231-241
• /
• 2006

Creating controllable, responsive avatars is an important problem in computer games and virtual environments. Recently, large collections of motion capture data have been exploited for increased realism in avatar animation and control. Large motion sets have the advantage of accommodating a broad variety of natural human motion. However, when a motion set is large, the time required to identify an appropriate sequence of motions is the bottleneck for achieving interactive avatar control. In this paper, we present a novel method for training avatar behaviors from unlabelled motion data in order to animate and control avatars at minimal runtime cost. Based on machine learning technique, called Q-teaming, our training method allows the avatar to learn how to act in any given situation through trial-and-error interactions with a dynamic environment. We demonstrate the effectiveness of our approach through examples that include avatars interacting with each other and with the user.

• Journal of The Korean Association of Information Education
• /
• v.25 no.6
• /
• pp.1015-1024
• /
• 2021

There are various educational programming environments in which students can train artificial intelligence (AI) using block-based programming languages, such as Entry, Machine Learning for Kids, and Teachable Machine. However, these programming environments are designed so that students can train AI through a separate menu, and then use the trained model in the code editor. These approaches have the advantage that students can check the training process more intuitively, but there is also the disadvantage that both the training menu and the code editor must be used. In this paper, we present a novel artificial intelligence block that can perform both AI training and programming in the code editor. While this AI block is presented as a Scratch block, the training process is performed through a Python server. We describe the blocks in detail through the process of training a model to classify a blue pen and a red pen, and a model to classify a dental mask and a KF94 mask. Also, we experimentally show that our approach is not significantly different from Teachable Machine in terms of performance.

• Journal of The Korean Association of Information Education
• /
• v.5 no.2
• /
• pp.216-229
• /
• 2001

A more interactive teaching-learning system is increasingly necessary in the consumer-oriented environment of distance education. This article would like to suggest a more spontaneous system which is learners at various levels. The suggested system keynotes its efficiency with the introduction of a "mobile agent" concept through which learners are able to network and complete their assignments despite their dispersed environments. This article also suggests some managerial techniques for the systematic management of agent-based learners possessing diverse characteristics. Through this study, we expect more highly effect by offer data adapted to learning goal to learner's ability, get out of uniform web-based teaching-learning.

• Asia pacific journal of information systems
• /
• v.22 no.1
• /
• pp.1-27
• /
• 2012

Asynchronous Learning Networks (ALN) has become a kind of prevalent information systems to supplement or even substitute a traditional classroom face-to-face teaching method. In this paper, we investigate the impacts of types of courses, lecturers' instruction models and computer self-efficacy on the ALN effectiveness in teaching from lecturers' perspective. We conducted survey to professors in various faculties such as School of Computing, Faculty of Arts, Science, Business, Law and Engineering in the National University of Singapore. According to the responses from ninety-eight professors, instruction modes positively influence the usage of ALN; types of course and lecturers' computer-efficacy influence lectures' satisfaction of ALN in teaching. Both the usage of ALN and satisfaction of ALN positively influence the effectiveness of ALN. The results of this study fill the gap of ALN researches in education by examining it from lecturers' perspective and enable schools to improve their implementation of ALN systems based on our findings.

• Journal of Digital Contents Society
• /
• v.9 no.2
• /
• pp.225-233
• /
• 2008

Rapid advancement information and communication technologies has introduced various dimension of e-Learning environment such as u-learning(ubiquitous learning), m-learning(mobile learning) and t-learning(television learning). These technologies enabled learners to access learning contents through variety of devices with more flexibility and consistency. In order to implement learning through these multiple environments, basically it is necessary to acquire and process the platform information that contains properties and status of the web-accessing devices. In this study, we introduce the design and implementation of a Platform Analyzer Model which is essential for learning systems that support multi-platform environment. We also present a Interactive DTV-Centered multi-platform learning environment framework using PC, PDA or Mobile phone. Finally, we will discuss the possibility of the multi-platform learning environment with sample scenario and contents.

• The Journal of Korean Association of Computer Education
• /
• v.23 no.2
• /
• pp.53-64
• /
• 2020

As online learning forms centered on video lectures become more common and constantly increasing, the video-based learning environment applying various educational methods is also changing and developing to enhance learning effectiveness. Learner's log data has emerged for measuring the effectiveness of education in the online learning environment, and various analysis methods of log data are important for learner's customized learning prescriptions. To this end, the study analyzed learner behavior data and predictions of achievement by machine learning in video-based learning environments. As a result, interactive behaviors such as video navigation and comment writing, and learner-led learning behaviors predicted achievement in common in each model. Based on the results, the study provided implications for the design of the video learning environment.