• Journal of Science Education
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• v.41 no.2
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• pp.248-266
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• 2017

The purpose of this study is to present various examples of collaborative learning based on the Instruction of Internet in the 6th grade elementary school mathematics class. So we introduce the design method of classroom environment for classroom Internet and give example of various teaching methods. This study was conducted for nine months from March to November, 2016, one sixth grade of elementary school in D area. During this period, we conducted Instruction of Internet-based collaborative learning to classify typical teaching cases. We classified into 5 type collaborative learning. First, collaborative learning in the classroom. Second, remote collaborative learning between classroom and classroom. Third, Live participation classes. Forth, project collaborative learning. Fifth, using virtual reality in collaborative learning. In addition, we could identify that there is a difference compared to the conventional learning. It became possible to conduct collaborative learning with other students simultaneously or have opening class with both parents and teachers by using Youtube. These examples can be presented as a case to depart from traditional mathematics class in one classroom. In this regard, we will be able to provide several implications about teaching methods utilizing smart device and Internet in future classroom.

• Journal of Digital Convergence
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• v.16 no.10
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• pp.1-9
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• 2018

The purpose of this study is to examine the concepts and types of cross-cultural collaborative online learning that enhance the utilization of advanced ICT in education and contribute to the promotion of educational exchanges between countries, and suggest exchange learning design models necessary for the active introduction. For this study, previous studies related to cross-cultural collaborative online learning were examined. As a result, cross-cultural collaborative online learning is an educational method based on constructivism that explore and construct knowledge by interacting and collaborating with students, teachers, and field experts who are linguistically and culturally heterogeneous based on advanced ICT. The type of cross-cultural collaborative online learning could be divided into synchronous exchange learning centered on remote video classes and asynchronous exchange learning centered on website based tasks. A PPIE learning design model considering the characteristics of each type is presented.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.5
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• pp.914-923
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• 2015

Recently, as the number of smart devices (such as smart TV or Web based IPTV) increases, the way of digital broadcast contents is changed. This change leads that conventional broadcast media accepts Web platform and its services to provide more quality contents. Based on this change, in education field, education broadcasting also follows the trend. The traditional education broadcasting platforms, which just delivered the lecture in one-way, are utilized the Web technology to make interaction between teacher and student. Current education platforms, however, are insufficient to satisfy users' demands for two-way interactions. This paper proposes a new remote collaborative learning platform which able to provide high interactivity among users. Based on new functional requirements from original use case, the platform provides collaborative contents sharing and collaborative video streaming techniques by utilizing WebRTC (Web Real-Time Communication) technology. The implementation demonstrates the operability of proposed system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.958-979
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• 2023

Due to laws, regulations, privacy, etc., between 70-90 percent of providers do not share medical data, forming a "data island". It is essential to collaborate across multiple institutions without sharing patient data. Most existing methods adopt distributed learning and centralized federal architecture to solve this problem, but there are problems of resource heterogeneity and data heterogeneity in the practical application process. This paper proposes a collaborative deep learning modelling method based on the blockchain network. The training process uses encryption parameters to replace the original remote source data transmission to protect privacy. Hyperledger Fabric blockchain is adopted to realize that the parties are not restricted by the third-party authoritative verification end. To a certain extent, the distrust and single point of failure caused by the centralized system are avoided. The aggregation algorithm uses the FedProx algorithm to solve the problem of device heterogeneity and data heterogeneity. The experiments show that the maximum improvement of segmentation accuracy in the collaborative training mode proposed in this paper is 11.179% compared to local training. In the sequential training mode, the average accuracy improvement is greater than 7%. In the parallel training mode, the average accuracy improvement is greater than 8%. The experimental results show that the model proposed in this paper can solve the current problem of centralized modelling of multicenter data. In particular, it provides ideas to solve privacy protection and break "data silos", and protects all data.

• Journal of Platform Technology
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• v.9 no.3
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• pp.70-77
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• 2021

The purpose of Serious games in immersive Metaverse platform to provide users both fun and intriguing learning experiences. We proposes a serious game for self-trainable fire evacuation drill with collaboration among avatars synchronized with multiple trainees and optionally with real-time supervising placed at different remote physical locations. The proposed system architecture is composed of wearable motion sensors and a Head Mounted Display to synchronize each user's intended motions to her/his avatar activities in a cyberspace in Metaverse environment. The proposed system provides immersive as well as inexpensive environments for easy-to-use user interface for cyber experience-based fire evacuation training system. The proposed configuration of the user-avatar interface, the collaborative learning environment, and the evaluation system on the VR serious game are expected to be applied to other serious games. The game was implemented only for the predefined fire scenario for buildings, but the platform can extend its configuration for various disaster situations that may happen to the public.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.216-222
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• 2021

Advances in technology have given educators a tool to empower them to assist with developing the best possible human resources. Teachers at universities prefer to use more modern technological advances to help them educate their students. This opens up a necessity to research the capabilities of cloud-based learning services so that educational solutions can be found among the available options. Based on that, this essay looks at models and levels of deployment for the e-learning cloud architecture in the education system. A project involving educators explores whether gement Systems (LMS) can function well in a collaborative remote learning environment. The study was performed on how Blackboard was being used by a public institution and included research on cloud computing. This test examined how Blackboard Learn performs as a teaching tool and featured 60 participants. It is evident from the completed research that computers are beneficial to student education, especially in improving how schools administer lessons. Convenient tools for processing educational content are included as well as effective organizational strategies for educational processes and better ways to monitor and manage knowledge. In addition, this project's conclusions help highlight the advantages of rolling out cloud-based e-learning in higher educational institutions, which are responsible for creating the integrated educational product. The study showed that a shift to cloud computing can bring progress to educational material and substantial improvement to student academic outcomes, which is related to the increased use of better learning tools and methods.

• Journal of the Korea Computer Graphics Society
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• v.14 no.4
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• pp.35-39
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• 2008

A computer supported collaborative system provides with a shared virtual workspace over the Internet where its remote users cooperate in order to achieve their goals by overcoming problems caused by distance and time. VRMMS (Virtual Reality Molecular Modeling System) [1] is a VR based collaborative system where biologists can remotely participate in and exercise molecular modeling tasks such as viewing three dimensional structures of molecular models, confirming results of molecular simulations and providing with feedbacks for the next simulations. Biologists can utilize VRMMS in executing molecular simulations. However, first-time users and beginners need to spend some time for studying and practicing in order to skillfully manipulate molecular models and the system. The best way to resolve the problem is to have a face-to-face session of teaching and learning VRMMS. However, it is not practically recommended in the sense that the users are remotely located. It follows that the learning time could last longer than desired. In this paper, we propose to use Second Life [2] combining with VRMMS for removing the problem. It can be used in building a shared workplace over the Internet where molecular simulations using VRMMS can be exercised, taught, learned and practiced. Through the web, users can collaborate with each other using VRMMS. Their avatars and tools of molecular simulations can be remotely utilized in order to provide with senses of 'being there' to the remote users. The users can discuss, teach and learn over the Internet. The shared workspaces for discussion and education are designed and implemented in Second Life. Since the activities in Second Life and VRMMS are designed to realistic, the system is expected to help users in improving their learning and experimental performances.

• Journal of the Society of Disaster Information
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• v.19 no.4
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• pp.924-935
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• 2023

Purpose: The central aim of this study is to leverage machine learning techniques for the classification of Intrusion Detection System (IDS) data, with a specific focus on identifying the variables responsible for enhancing overall performance. Method: First, we classified 'R2L(Remote to Local)' and 'U2R (User to Root)' attacks in the NSL-KDD dataset, which are difficult to detect due to class imbalance, using seven machine learning models, including Logistic Regression (LR) and K-Nearest Neighbor (KNN). Next, we use the SHapley Additive exPlanation (SHAP) for two classification models that showed high performance, Random Forest (RF) and Light Gradient-Boosting Machine (LGBM), to check the importance of variables that affect classification for each model. Result: In the case of RF, the 'service' variable and in the case of LGBM, the 'dst_host_srv_count' variable were confirmed to be the most important variables. These pivotal variables serve as key factors capable of enhancing performance in the context of classification for each respective model. Conclusion: In conclusion, this paper successfully identifies the optimal models, RF and LGBM, for classifying 'R2L' and 'U2R' attacks, while elucidating the crucial variables associated with each selected model.