• Journal of The Korean Association For Science Education
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• v.34 no.2
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• pp.123-134
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• 2014

This study aims to develop and validate an instrument to measure students' attitude toward convergence. To do so, we have defined five constructs (i.e. knowledge about convergence, personal relevance, social relevance, interest and self-efficacy) of 'attitude toward convergence' based on literature review, developed items, and collected data from 233 11th grade science track students. The validity of these items have been evaluated by Messick's framework (1995) (i.e. content, substantive, structural aspects of validity), experts' review, Rasch analysis, and confirmatory factor analysis using structural equation modeling. Our results have confirmed the five constructs and 23 selected items have met the benchmark of item validity. Moreover, the theoretical model illustrating that the high level of attitude toward convergence increases the level of science motivation has also been supported by the data. The items developed in this study will be used to measure students' attitude toward convergence and to estimate the effect of learning program for convergence science.

• Journal of The Korean Association of Information Education
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• v.10 no.2
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• pp.261-271
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• 2006

Since the educational guideline on Information and Communication Technology(ICT) was announced, almost every school has taught about ICT during the discretionary classes. Although research on the computer curriculum and comparative studies on computer textbooks have been conducted, a study on the current status of the use of computer textbooks has not been carried out yet. On the basis of such needs, this study was conducted to investigate the current status of the use of computer textbooks in elementary schools(i.e. how teachers use computer textbooks in schools, and what teachers and students think about computer textbooks), and to suggest ideas to be considered in order to improve the quality of computer textbooks. The main finding of this study is that although most teachers use computer textbooks, the frequency of use is low and teachers use the textbook by revising or complementing its content. Also, most teachers respond negatively to some aspects of computer textbooks(i.e. level-based learning, reconstructional facility, systemicity, enhancement of exploring and creative ability, induction of interest, enhancement of self-directed learning, and assignments). In contrast with this result, students respond negatively only to the vocabularies used in computer textbooks. In addition, teachers showed significantly different responses according to their age and teaching experiences, and students demonstrated significantly different responses according to their gender and the frequency of the use of computer textbooks.

• Journal of the Korean Society of Earth Science Education
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• v.9 no.2
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• pp.139-151
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• 2016

The purposes of this study were to develop the student activity-centered science textbook model in high school and explore the field application possibility. For development of student activity-centered science textbook model, we conducted a literature survey about foreign science textbook and science curriculum and we developed the textbook development framework based on 7E learning model. Based on framework, we developed student activity-centered science textbook model about achievement standards 'systems and interaction - earth systems'. A development model is the total amount of five class periods and the various objectives were reflected in pursuit systems thinking & STEAM. 1~4 class periods, learning content composed of student activity-centered exploration activities that organically associated to make final products. Fifth class period was presented to explore job and career. A development model was applied to high school class for one time study. Applying the result of field study, students were responded positively in interested about science class, textbook contents, made final product. Through this study, if science textbook was made on the basis of the revised student activity-centered science textbook model, students were lead to positive change in science class.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.830-860
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• 2022

[Introduction] Nowadays, many companies are shifting their businesses online due to the growing trend among customers to buy and shop online, as people prefer online purchasing products. [Problem] Users share a vast amount of information about products, making it difficult and challenging for the end-users to make certain decisions. [Motivation] Therefore, we need a mechanism to automatically analyze end-user opinions, thoughts, or feelings in the social media platform about the products that might be useful for the customers to make or change their decisions about buying or purchasing specific products. [Proposed Solution] For this purpose, we proposed an automated SentiDecpective approach, which classifies end-user reviews into negative, positive, and neutral sentiments and identifies deceptive crowd-users rating information in the social media platform to help the user in decision-making. [Methodology] For this purpose, we first collected 11781 end-users comments from the Amazon store and Flipkart web application covering distant products, such as watches, mobile, shoes, clothes, and perfumes. Next, we develop a coding guideline used as a base for the comments annotation process. We then applied the content analysis approach and existing VADER library to annotate the end-user comments in the data set with the identified codes, which results in a labelled data set used as an input to the machine learning classifiers. Finally, we applied the sentiment analysis approach to identify the end-users opinions and overcome the deceptive rating information in the social media platforms by first preprocessing the input data to remove the irrelevant (stop words, special characters, etc.) data from the dataset, employing two standard resampling approaches to balance the data set, i-e, oversampling, and under-sampling, extract different features (TF-IDF and BOW) from the textual data in the data set and then train & test the machine learning algorithms by applying a standard cross-validation approach (KFold and Shuffle Split). [Results/Outcomes] Furthermore, to support our research study, we developed an automated tool that automatically analyzes each customer feedback and displays the collective sentiments of customers about a specific product with the help of a graph, which helps customers to make certain decisions. In a nutshell, our proposed sentiments approach produces good results when identifying the customer sentiments from the online user feedbacks, i-e, obtained an average 94.01% precision, 93.69% recall, and 93.81% F-measure value for classifying positive sentiments.

• Journal of Korea Entertainment Industry Association
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• v.15 no.2
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• pp.179-189
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• 2021

As the school was in crisis due to the COVID-19, e-Learning was extended. Although it was difficult for everyone, e-Learning were stabilized with the enthusiasm and efforts of school teachers. Online education in Korea, called 'K-edu' is being promoted by school teachers in COVID19, and is considered an important area of future education beyond the post corona. Therefore, analyze the meaning of K-edu experienced by school teachers, studying changes in the educational paradigm in the Post-COVID era is very important in establishing the direction and content of future education. In this study described the K-edu experienced by school teachers in response to Corona 19 as 'changed daily life of school teachers', 'changes in schools', 'difficulties felt by teachers' and 'proposals for K-edu' through the qualitative research method FGI. Based on this, the characteristics of K-edu that changed through COVID-19 were analyzed as 'expansion of educational space', 'expansion of educational form' and 'highlighting the importance of face-to-face education'. Through this study, we hope that K-Edu led by school teachers will serve as a cornerstone for leading the world beyond Korea.

• Journal of The Korean Association For Science Education
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• v.44 no.1
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• pp.105-117
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• 2024

The purpose of this study was to explore changes in elementary teachers' modeling pPCK (personal PCK) resulting from knowledge exchange within the realms of PCK described in the Refined Consensus Model (hereafter RCM). For this purpose, a professional learning community (hereafter PLC) was established for three elementary school teachers to facilitate knowledge exchange specifically focused on science modeling instructions. The study then analyzed the CoRe (content representations) written by the research participants twice to explore any changes in modeling pPCK (personal PCK). In addition, the discourse shared by the participants in the PLC and the data from the in-depth interviews were also analyzed using grounded theory research methods. The results of the study showed that there was no significant change in knowledge of the science curriculum in elementary teachers' modeling pPCK, but there were changes in orientations toward teaching science, knowledge of students' understanding in science, knowledge of instructional strategies and representations, and knowledge of assessment of science learning. Furthermore, the analysis of PLC discourse and in-depth interviews showed that modeling instructions reflection (ePCK; enacted PCK) and educational research-based modeling cPCK (collective PCK) influenced these changes in teachers' modeling pPCK. Accordingly, this study suggests recommendations for pedagogical approaches aimed at improving teachers' modeling PCK.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.306-314
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• 2023

Stream sediments are an important component of water quality management because they are receptors of various pollutants such as heavy metals and organic matters emitted from upland sources and can be secondary pollution sources, adversely affecting water environment. To effectively manage the stream sediments, identification of primary sources of sediment contamination and source-associated control strategies will be required. We evaluated the performance of machine learning models in identifying primary sources of sediment contamination based on the physico-chemical properties of stream sediments. A total of 356 stream sediment data sets of 18 quality parameters including 10 heavy metal species(Cd, Cu, Pb, Ni, As, Zn, Cr, Hg, Li, and Al), 3 soil parameters(clay, silt, and sand fractions), and 5 water quality parameters(water content, loss on ignition, total organic carbon, total nitrogen, and total phosphorous) were collected near abandoned metal mines and industrial complexes across the four major river basins in Korea. Two machine learning algorithms, linear discriminant analysis (LDA) and support vector machine (SVM) classifiers were used to classify the sediments into four cases of different combinations of the sampling period and locations (i.e., mine in dry season, mine in wet season, industrial complex in dry season, and　industrial complex in wet season). Both models showed good performance in the classification, with SVM outperformed LDA; the accuracy values of LDA and SVM were 79.5% and 88.1%, respectively. An SVM ensemble model was used for multi-label classification of the multiple contamination sources inlcuding landuses in the upland areas within 1 km radius from the sampling sites. The results showed that the multi-label classifier was comparable performance with sinlgle-label SVM in classifying mines and industrial complexes, but was less accurate in classifying dominant land uses (50~60%). The poor performance of the multi-label SVM is likely due to the overfitting caused by small data sets compared to the complexity of the model. A larger data set might increase the performance of the machine learning models in identifying contamination sources.

• Journal of Engineering Education Research
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• v.19 no.3
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• pp.35-43
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• 2016

The purpose of this study is to explore directions for improvement of teaching at college of engineering based on analysis of differences from course evaluation of students and instructors. Data was collected from 86 instructors' ratings on courses and their 3004 students' ratings on courses at college of engineering in a two-year, a three-year college and a University from 2010 to 2013. The results of the survey indicate significant differences in the statistics from the several questions between the instructors and the students as well as between the course in a two-year, a three-year college and in a University. First, instructors' self evaluation of the course is higher than students' satisfaction ratings of the course on the average. Instructors' self evaluation are high on the questions 'The subject was proper for the course', 'The course provided the latest theory and trend of the field', and 'Fairness and objectivity about the exams and the assignments'. Also, the difference between Instructors and students on the questions is significant in the statistics. The professor must make sure that students know well how to organize the course content and the method for feedback to test result and homework. Second, instructors have higher satisfaction ratings on the six questions and students have higher satisfaction ratings on the one question('Make students participate in the class effectively') at a two-year and a three-year college. However, students have higher satisfaction ratings on the three questions('Make students participate in the class effectively', 'Concern about students' learning process', and 'Use of E-learning and media equipments') and instructors have higher satisfaction ratings on the one question. It means instructors at a University feel pressure on a teaching and they are unsatisfied with their teaching skills. Third, the result of comparing six parts of the questions shows that students' satisfaction ratings are higher on 'Students participation' and 'Application of media equipments' parts whereas instructors' self evaluation are higher on 'Exams and assignments' part. Fourth, the question 'Make students participate in the class effectively' is significant in statistic based on comparison of instructors and students, and comparison of in a college and a University. Students' satisfaction ratings are higher than instructors' self evaluation.

• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.61-69
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• 2019

In this paper, we propose a multisensory(i.e., visual-auditory-tactile) based AR system for the education of cultural heritage. The proposed system provides a multisensory interaction by designing a user to experience with a 3D printed artifact which is mapped by a virtual 3D content of digital heritage. Compared with the existing systems of cultural heritage education based on augmented reality(AR) technology, this system focused on not only providing learning experience via a sense of visual and auditory, but also a sense of tactile. Furthermore, since this systems mainly provided the direct interactions using a 3D printed model, it gives a higher degree of realism than existing system that use touch or click motions on a 2D display of mobile phones and tablets. According to a result of user testing, we concluded that the proposed system delivered the excellent presence and learning flow to users. Particularly, from the usability evaluation, a 3D printed target artifact which is similar in shape to original heritage artifact, achieved the highest scores among the various tested targets.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.207-212
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• 2024

The importance of hydrogen fuel cells continues to be emphasized, and there is a growing demand for education and training in this field. Among various educational environments, metaverse education is opening a new era of change in the global education industry, especially to adapt to remote learning. The most significant change that the metaverse has brought to education is the shift from one-way, instructor-centered, and static teaching approaches to multi-directional and dynamic ones. It is expected that the metaverse can be effectively utilized in hydrogen fuel cell engineer education, not only enhancing the effectiveness of education by enabling learning and training anytime, anywhere but also reducing costs associated with engineering education.In this research, inspired by these ideas, we are designing a fuel cell education platform. We have created a platform that combines theoretical and practical training using the metaverse. Key aspects of this research include the development of educational training content to increase learner engagement, the configuration of user interfaces for improved usability, the creation of environments for interacting with objects in the virtual world, and support for convergence services in the form of digital twins.