• Journal of Engineering Education Research
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• v.27 no.1
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• pp.41-49
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• 2024

The purpose of this study is to explore ways to improve major satisfaction that can be applied by universities through the analysis of factors influencing major satisfaction of engineering college students. To this end, Korea-National Survey of Student Engagement(K-NSSE) data involving 814 students from T University were used, and logistic regression analysis and t-test were applied. The main results obtained through this are as follows. First, engineering college students' major satisfaction factors include major-career relevance, college immersion, and positive academic sentiment. Second, depending on the grade, it was confirmed that the factor of major-career relevance in the lower grades, and the factors of meaningful learning experience and college immersion in addition to major-career relevance in the upper grades had a significant influence. Third, the higher the meaningful learning experience, positive academic sentiment, and college immersion, including the major-career relevance, the higher the major satisfaction was found in the middle-class group with a score of BO or higher. This study is meaningful in that it revealed differences in influence by individual characteristics as well as major satisfaction influencing factors that can be practiced in universities such as learning experiences.

• Journal of the Korean Institute of Educational Facilities
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• v.24 no.1
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• pp.11-22
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• 2017

The main purpose of this research is to consider educational environment, concept, and spatial organization and its characteristic based on the early 20th century European child-centered educational philosophy. For this process, the study of the following have been done : 1) Literature review, which includes educational ideology, perspective of child development of Maria Montessori, Rudolf Steiner, Peter Peterson, and Celestin Freinet. 2) Comparisons of spatial organization and classrooms of schools operated with the educational philosophy of mentioned philosophers from above. These schools have classrooms(or multi-purpose space near classroom) contained self-directed individual learning space, group and collaborative learning space, and training space of practical life. These configuration of learning space intended 1) learning based on individual child's interest, experience 2) developing of responsibility based on freedom 3) sociality and community spirit of children.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.3
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• pp.207-221
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• 2014

Education environment of modern society is rapidly changing along the usage of various device and development of contents. Learners of diverse age groups and genders are exposed in smart education environment. Thus in order to investigate effective smart education contents production, this study classified interactive types that affect learning satisfaction into CAI (Computer Assisted Instruction) based , NCS (Network Communication System) based , and NTS (New Technology System) based . Then we investigated how each interactive types affect immersion, utility, self-efficacy, practicality, and stimulation. The effects were measured according to the learner's gender and age. As the result, interactive types do affect smart education, where male had higher learning satisfaction for CAI based, game type, and wiki type while female had higher satisfaction for relationship establishment type and experience type. Also, for age group, the 10s preferred NTS based, 20~30s NCS based, and 40s and over CAI based interactive type. Thus, if satisfaction levels according to gender and age are considered when producing smart education contents, it may be possible to create educative contents that meet the dispositions of the learners.

• Journal of IKEEE
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• v.25 no.2
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• pp.337-343
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• 2021

Deep reinforcement learning is an artificial intelligence algorithm that enables learners to select optimal behavior based on raw and, high-dimensional input data. A lot of research using this is being conducted to create an optimal movement path of a mobile robot in an environment in which obstacles exist. In this paper, we selected the Dueling Double DQN (D3QN) algorithm that uses the prioritized experience replay to create the moving path of mobile robot from the image of the complex surrounding environment. The virtual environment is implemented using Webots, a robot simulator, and through simulation, it is confirmed that the mobile robot grasped the position of the obstacle in real time and avoided it to reach the destination.

• Journal of Korean Clinical Health Science
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• v.12 no.1
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• pp.1678-1688
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• 2024

Purpose: This study was conducted to explore the experiences of nursing students who participated in the pneumonia and pleural effusion using web-based virtual reality and high-fidelity simulation. Methods: This study is qualitative study using inductive content analysis. We developed simulation scenario regarding pneumonia and pleural effusion. Eleven nursing students who participated in simulation were interviewed between June 20 to August 25, 2022. The interviews were transcribed and analyzed according to the inductive content analysis. Results: The results were analyzed into three key categories: 'pre-learning and psychological burden before simulation','increased learning satisfaction','improved clinical performance'. Conclusions: Participants was able to integrate their previous experience, including clinical practice experiences, web-based virtual simulation, into high-fidelity simulation and effectively enhanced their learning experience. Therefore, when providing various types of simulation simultaneously, it is necessary to take into account the prior students' experiences and to organize simulation education by considering the characteristics of simulation.

• International Journal of Contents
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• v.8 no.2
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• pp.23-27
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• 2012

The successful use of digital textbooks (DTs) in schools requires the development of various teaching and learning methods that are appropriate for DTs. However, recent DT studies have focused mainly on the implementation of DT features and formats. The objective of this study was to investigate a problem-based learning instructional model appropriate to DTs and to present the experimental results using the problem-based DT to demonstrate its educational effectiveness. Two learning-achievements tests were conducted to analyze the learning experience and effectiveness of the problem-based DT after it had been used in a high school for a certain period. The experimental results indicated that the students who used the DT, especially lower-level students, exhibited improved problem-solving ability and demonstrated a better practical understanding of the subject than students who used printed textbooks.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.33-38
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• 2022

This study examines the impact of e-learning on the educational level of students with intellectual disabilities from the viewpoint of their teachers. The study sample consisted of seven teachers: two working in primary school, two in middle school, and three in secondary school. The research applied a qualitative approach, using interviews with the participants. The results showed that the following are required for the effective use of e-learning: firstly, appropriate training courses need to be offered to teachers, students, and families and secondly, it is vital students are provided with the appropriate digital devices to maintain contact with their teachers. The study concludes by recommending the development of educational applications and/or programs capable of supporting teachers and students in their use of e-learning.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.2
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• pp.33-48
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• 2020

By Digital Transformation, new technologies like ML (Machine Learning), Big Data, Cloud, VR/AR are being used to video streaming technology. We choose ML to provide optimal QoE (Quality of Experience) in various network conditions. In other words, ML helps DASH in providing non-stopping video streaming. In DASH, the source video is segmented into short duration chunks of 2-10 seconds, each of which is encoded at several different bitrate levels and resolutions. We built and compared the performances of five prototypes after applying five different machine learning algorithms to DASH. The prototype consists of a dash.js, a video processing server, web servers, data sets, and five machine learning models.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.2
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• pp.1-8
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• 2011

In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The finite failure non-homogeneous Poisson process models presented and the life distribution applied extreme distribution which used to find the minimum (or the maximum) of a number of samples of various distributions. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than automatic error that is generally efficient model could be confirmed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error.

• Journal of Information Technology Services
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• v.21 no.4
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• pp.75-90
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• 2022

From the past to the present, reviews have had much influence on consumers' purchasing decisions. Companies are making various efforts, such as introducing a review incentive system to increase the number of reviews. Recently, as various types of reviews can be left, reviews have begun to be recognized as interesting new content. This way, reviews have become essential in creating loyal customers. Therefore, research and utilization of reviews are being actively conducted. Some studies analyze reviews to discover customers' needs, studies that upgrade recommendation systems using reviews, and studies that analyze consumers' emotions and attitudes through reviews. However, research that predicts the future using reviews is insufficient. This study used a dataset consisting of two reviews written in pairs with differences in usage periods. In this study, the direction of consumer product evaluation is predicted using KoBERT, which shows excellent performance in Text Deep Learning. We used 7,233 reviews collected to demonstrate the excellence of the proposed model. As a result, the proposed model using the review text and the star rating showed excellent performance compared to the baseline that follows the majority voting.