• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.115-121
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• 2009

Web 2.0 has become the face next generation Web among the business world and research community. Web 2.0 is instant superficial gratification of people. On the other hand, Semantic Web is deep, meaningful and lasting relationship with data. So, it is difficult to apply the Semantic Web to the real world. In this paper, a platform for educational services using the Semantic Web and Web 2.0 is proposed. The proposed platform is based mix of the Semantic Web and Web 2.0, so it is useful to apply in the real world applications. Two services are presented, one is a semantic email system and the other is a cyber study space. The cyber study space adjusted each student is presented. The study environment is called iStudySpace that has personal scheduler, study status plan table, personalized search engine and several gadgets. Finally characteristics and limitations of the Semantic Web and Web 2.0, the organization and components of the platform, evaluation of iStudySpace are shown.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.137-140
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• 2022

The article deals with increasing the effectiveness of educational content on the YouTube channel with the help of built-in analytics tools. Particular attention is paid to the creation of quality video, taking into account the reaction of end users of video materials. Ways to increase the video audience are considered. Techniques for improving video content apply to individual videos, as well as playlists and channels in general. In this case YouTube is both an independent educational platform and an auxiliary platform in a set of various educational solutions.

• Journal of Practical Engineering Education
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• v.16 no.2
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• pp.167-177
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• 2024

In nursing education, there has been efforts for enhancing the quality, with a growing interest in the utilization of digital technologies. In clinical training of nursing curriculum, the emphasis on digital technology is pronounced, as it has the potential to offer learners effective and accessible educational experience while enabling the integrated management of individualized learning outcomes. This study developed a digital nursing education platform, allowing educators and learners to select functionalities based on the educational content and characteristics of the learning tools. Additionally, the user interface was designed to facilitate learners' accurate understanding and execution of assigned tasks and objectives. The detailed design and implementation process of the platform are elaborated and then the validation of its usefulness was provided based on feedback from ten educators who are responsible for diverse subjects. The high usability of the digital nursing practicum education platform was confirmed, with potential implications for significant improvements in learner performance. The potential of this digital platform is to lead to innovative shifts in educational methodologies within the field of integrative nursing education.

• Journal of Information Technology Applications and Management
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• v.30 no.6
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• pp.53-68
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• 2023

Through the COVID-19 pandemic, the demand for non-face-to-face communication systems has surged, leading to an increased prevalence of virtual interactions across various domains, such as tasks, meetings, orders and deliveries, and even student education. Against this backdrop, interest in the metaverse platform has been on the rise, with metaverse services like Zepeto, Roblox, and Minecraft expanding beyond gaming to encompass educational fields as well. This study aims to identify authenticity factors influencing metaverse platform-based educational services and examine their impact. The authenticity components are defined as integrity, empathy, interactivity, presence, and uniqueness. The study investigates the effects of these authenticity components on both service value and service satisfaction. To achieve this, a survey involving 320 metaverse users was conducted, and the model was subjected to statistical validation. The findings of this research underscore that perceiving metaverse education services, still in the early stages of introduction, as authentic educational methods for learners positively influences satisfaction with the educational service.This study holds significance as it lays the theoretical groundwork for enhancing the authenticity of educational services in virtual space. It defines and proposes authenticity elements for customer satisfaction in metaverse educational services, which are still in their nascent stages. Moving forward, it is anticipated that various studies will be conducted to enhance the value of metaverse education services and achieve higher customer satisfaction as customer experiences evolve and deepen.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.2
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• pp.221-226
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• 2018

Open source software allows revising and adding a new idea on them as well as debugging themselves. The open source software can be utilized as various educational programs as well as development of a commercial software products using them. MIT App Inventor, one of the block-based visual programming environments for education, supports building a local server and even revision of the platform itself by providing its own source codes. In this paper we implement App Inventor open sources on the local server. Especially we present how to revise and implement a new App Inventor platform reflecting their own requirements in schools or educational institutes and how to build a local server operating the revised App Inventor platform. They can provide more interactive educational environments to students and improve educational satisfaction through the active customizing of the platform itself such as adding new programming block components requested by students.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.8-17
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• 2019

The main purpose of this study isto explore the potential of affective computing (AC) platforms in education through two phases ofresearch: Phase I - platform analysis and Phase II - classification of academic emotions. In Phase I, the results indicate that the existing affective analysis platforms can be largely classified into four types according to the emotion detecting methods: (a) facial expression-based platforms, (b) biometric-based platforms, (c) text/verbal tone-based platforms, and (c) mixed methods platforms. In Phase II, we conducted an in-depth analysis of the emotional experience that a learner encounters in online video-based learning in order to establish the basis for a new classification system of online learner's emotions. Overall, positive emotions were shown more frequently and longer than negative emotions. We categorized positive emotions into three groups based on the facial expression data: (a) confidence; (b) excitement, enjoyment, and pleasure; and (c) aspiration, enthusiasm, and expectation. The same method was used to categorize negative emotions into four groups: (a) fear and anxiety, (b) embarrassment and shame, (c) frustration and alienation, and (d) boredom. Drawn from the results, we proposed a new classification scheme that can be used to measure and analyze how learners in online learning environments experience various positive and negative emotions with the indicators of facial expressions.

• Journal of Internet of Things and Convergence
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• v.8 no.6
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• pp.85-92
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• 2022

Demand for big data analysis and AI developers is increasing, but there is a lack of an education base to supply them. In this paper, by developing a cloud-based artificial intelligence education platform, the goal was to establish an environment in which practical practical training can be efficiently learned at low cost at educational institutions and IT companies. The development of the education platform was carried out by planning scenarios for each user, architecture design, screen design, implementation of development functions, and hardware construction. This training platform consists of a containerized workload, service management platform, lecture and development platform for instructors and students, and secured cloud stability through real-time alarm system and age test, CI/CD development environment, and reliability through docker image distribution. The development of this education platform is expected to expand opportunities to enter new businesses in the education field and contribute to fostering working-level human resources in the AI and big data fields.

• Communications of Mathematical Education
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• v.36 no.3
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• pp.417-438
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• 2022

The purpose of this study is to suggest implications for mathematics teaching and learning when using AI-based educational platforms that support personalized mathematics learning. To this end, we selected five platforms(Knock-knock! Math Expedition, knowre, Khan Academy, MATHia, CENTURY) and analyzed how the AI-based educational platforms for mathematics reflect the three elements(PLP, PLN, PLE) to support personalized learning. The results of this study showed that although the characteristics of PLP, PLN, and PLE implemented on each platform varied, they were designed to form PLEs that allow learners to make their autonomous decisions about learning based on PLP and PLN. The significance of this study can be found in that it has improved the understanding and practicability of personalized mathematics learning with the AI-based educational platforms.

• The Journal of Korean society of community based occupational therapy
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• v.11 no.1
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• pp.23-43
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• 2021

Objective : The purpose of this study was to establish a systematic educational operation platform by collecting expert opinions so that occupational therapists can use continuing education well as a means to become professional occupational therapists in a particular field. Methods : A Delphi study was conducted with 23 experts on continuing education courses in common areas, elderly or dementia, community-based, physical rehabilitation, and developmental disabilities conducted in 2019 and 2020. The first Delphi investigated the suitability of the course as a professional continuing education and the appropriate level of education. In the second Delphi, we derived the final platform by verifying its suitability with verification of its content validity. Results : As a result, 87 items were derived for common areas, 53 items for elderly or dementia, 66 items for community-based, 66 items for physical rehabilitation, and 85 items for developmental disabilities. The main contents included the expertise needed by occupational therapists, the role in various fields, the solution of difficulties in clinical practice, and the topic of preparing for the future. Conclusion : This study was meaningful in presenting an educational operation platform for training professional occupational therapists as a basic study. It is hoped that the optimal education operation platform will be developed to strengthen professional skills of occupational therapists efficiently through future research.

• MALSORI
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• no.51
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• pp.151-165
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• 2004

For educational and research purposes, a Korean speech recognition platform is designed. It is based on an object-oriented architecture and can be easily modified so that researchers can readily evaluate the performance of a recognition algorithm of interest. This platform will save development time for many who are interested in speech recognition. The platform includes the following modules: Noise reduction, end-point detection, met-frequency cepstral coefficient (MFCC) and perceptually linear prediction (PLP)-based feature extraction, hidden Markov model (HMM)-based acoustic modeling, n-gram language modeling, n-best search, and Korean language processing. The decoder of the platform can handle both lexical search trees for large vocabulary speech recognition and finite-state networks for small-to-medium vocabulary speech recognition. It performs word-dependent n-best search algorithm with a bigram language model in the first forward search stage and then extracts a word lattice and restores each lattice path with a trigram language model in the second stage.