• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.487-492
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• 2022

Universities are looking for various methods to enhance educational competence level suitable for the rapidly changing social environment. This study suggests a method to promote academic and educational achievements by reducing drop-out rate from their majors through implementation of pre-survey of satisfaction that revised and complemented survey items. To supplement the CQI method implemented after a general satisfaction survey, a pre-survey of satisfaction was carried out. To consolidate students' competences, this study made prediction and analysis of data with more importance possible using the Random Forest of the machine learning technique that can be applied to AI Medici platform, whose design is underway. By pre-processing the pre-survey of satisfaction, the students information enrolled in classes were defined as an explanatory variable, and they were classified, and a model was created and learning was conducted. For the experimental environment, the algorithms and sklearn library related in Jupyter notebook 3.7.7, Python 3.7 were used together. This study carried out a comparative analysis of change in educational satisfaction survey, carried out after classes, and trends in the drop-out students by reflecting the results of the suggested method in the classes.

• Journal of Science Education
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• v.41 no.3
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• pp.382-404
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• 2017

This study aims to explore a learning progression for eight core concepts of middle school science using constructed response items in the national assessment of educational achievement (NAEA). For this purpose, a total of 7,390 responses of the 9th graders on 8 constructed response items in NAEA conducted in 2015 were inputted by computer and the inputted answers were analyzed and classified into different levels. After completing this process, five levels were set for each construct and a construct map was created according to the levels. In this study, the construct map was written in a progression-based rubric format, which was used as a criterion for leveling the answers of all students. In addition, the Rasch model was applied to measure the scores and achievements of the respondents by means of statistical analysis to correlate the scores of the students with the achievement levels of the constructs. Lastly, a preliminary learning progression was created by revising the construct map reflecting the results of Rasch model application. This study was meaningful in that it explored the possibility of developing the learning process by using constructed response items in NAEA. However, the preliminary learning progression developed in this study is still hypothetical and inferential because it is not longitudinally traced to individual students. Therefore, it is necessary to continually revise and supplement through iterative research process.

• 대한공업교육학회지
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• v.38 no.2
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• pp.176-194
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• 2013

In this research, 'Construction Technology and Environment' units in 12 different technology home economics textbooks for 1st~3rd year middle school students under the 2009 Revised Educational Curriculum and the content system of textbooks were analyzed based on Reigeluth's elaboration theory, and the following conclusions were derived. First, each of the 12 different textbooks presented the elaboration process by procedural method and composed the content system. Second, the 'Construction Technology and Environment' unit presented many 'Thought Opening' as the systematization strategy of advance learning ability, and 'Unit Summary' presented at the end of the unit as the use strategy of the summarizer was presented preponderantly. In addition, 'Learning Objective' that represents the degree of achievement of the students after learning the unit was presented most as the use strategy of the synthesizer although there are differences in terms. In all of the textbooks, 'Figure,' 'Table,' 'Diagram', and 'Explanation of Terms' were used, and particularly, in the vitalizer strategy of the cognitive strategy, overwhelmingly greater number of 'Figure's, compared with all other elements, were presented as the vitalizer strategy of cognitive strategy. Finally, 'Compensatory Learning,' and 'In-depth Study' were presented as the learner control strategy in each of the 4 different textbooks, and there was one textbook that presents the term 'Supplement Reinforcement' in which compensatory learning and in-depth learning were integrated. Third, the metaphor utilization strategy among the 7 teaching strategies of the elaboration theory was hardly used in the composition items in units of textbooks.

• Journal of Science Education
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• v.47 no.1
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• pp.11-23
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• 2023

In this study, we examined the effect of socioscientific issue (SSI) based science lessons on underachieving 9th-grade students. A total of seven lessons centered on two SSIs related to the national science curriculum were developed and implemented during the first semester of 2021. Data were collected from 185 9th-grade students in one middle school in a mid-sized city of South Korea. Among them, 37 were identified as achieving far below the standards (underachieving students hereafter). Quantitative data were collected from pre- and post-tests on basic science content and attitudes and competency measures. To supplement quantitative data, lesson observation notes were recorded, and student interviews with a selected number of students were conducted. The analysis of quantitative data was conducted through the Wilcoxon Signed Rank Test and paired t-tests. Qualitative data were analyzed to find reasons for changing attitudes. The findings showed that the SSI-based lessons were more effective on underachieving students than the others in enhancing basic academic achievement, while there was no significant effect on all in attitudes and competency. Lesson observation data showed that underachieving students were more engaged in SSI-based lessons than before. Student interviews demonstrated several reasons why they were engaged, suggesting the aspects of SSI-based lessons that facilitated underachieving students' learning. Further research topics are suggested.

• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.483-494
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• 2020

With the advent of the 4th Industrial Revolution, interest in AI education is increasing. In order to cultivate talented people with AI competencies who will lead the future, AI education must be conducted in a sound manner at the school site. Although AI education is being conducted at home and abroad, it was determined that the role of the AI education platform is important to implement better AI education, so this study investigated the perception of experts on the AI education platform. A perception survey was conducted based on five criteria: teaching and learning management, educational contents, accessibility, performance of AI education platform, and level suitability of elementary school students. As a results, the number of 103 educational experts selected 'Entry' as the most proper platform among the eight platforms - 'Machine learning for Kids', 'Teachable Machine', 'AI Oceans(code.org)', 'Entry', 'Genie Block', 'Elice', 'mBlock' and etc. Analysis shows that this is because 'Entry' provides quality educational content, has convenient accessibility, is easy to manage teaching and learning, as well as an AI education platform suitable for the level of elementary school. In order to apply various AI education platforms to the school field, it is necessary to train teachers in AI-related training to train them as AI education experts, and to continuously provide opportunities to experience AI education platforms. In this study, there are limitations to what is called 'a population perception survey'. because only 103 people were surveyed, and most of the experts are working in a specific area(Gyeonggi-do). In the future, it is judged that research targeting experts at the national level should be conducted to supplement these limitations.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.375-382
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• 2021

Adolescents with disabilities have unnatural behavior and language, which makes it difficult to use soft and flexible language and behavior, and lack of learning experience has limitations in not being free in mature behavioral communication. Eurhythmics musical rhythm elements were divided into time and space, power and weight, and balance and fluidity and reflected in teaching and learning so that adolescents with disabilities could have comfortable, creative, and original thoughts that bring about changes in thawing. In order to increase the effectiveness of education in the direction of observing the effect of improving self-esteem, communication, and creativity of adolescents with disabilities, the study guide applying the Eurhythmics rhythm element was fused with music education, art education, and physical education, and interviewed by selecting research participants. Based on the questionnaire, an observation method suitable for the study of adolescents with disabilities was conducted. As a result of the study, it was observed that the educational effect of the disabled youth was improved as a result of conducting the class by applying the Eurhythmics rhythm elements time and space, force and weight, balance and fluidity by integrating music, art, and physical education(line dance, playtime). Therefore, to supplement the limitations in this learning process, various educational methods applicable to the education of youth with disabilities, a support system that can reflect Eurhythmics education through physical play, and a method to properly compose various learning tools do.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.166-178
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• 2023

This study aims to introduce and assess CNN Deep Learning methods to analyze visual landscape images on social media with embedded user perceptions and experiences. This study analyzed visual landscape images by focusing on a healing place. For the study, seven adjectives related to healing were selected through text mining and consideration of previous studies. Subsequently, 50 evaluators were recruited to build a Deep Learning image. Evaluators were asked to collect three images most suitable for 'healing', 'healing landscape', and 'healing place' on portal sites. The collected images were refined and a data augmentation process was applied to build a CNN model. After that, 15,097 images of 'healing' and 'healing landscape' on portal sites were collected and classified to analyze the visual landscape of a healing place. As a result of the study, 'quiet' was the highest in the category except 'other' and 'indoor' with 2,093 (22%), followed by 'open', 'joyful', 'comfortable', 'clean', 'natural', and 'beautiful'. It was found through research that CNN Deep Learning is an analysis method that can derive results from visual landscape image analysis. It also suggested that it is one way to supplement the existing visual landscape analysis method, and suggests in-depth and diverse visual landscape analysis in the future by establishing a landscape image learning dataset.

• Journal of Practical Engineering Education
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• v.15 no.2
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• pp.439 -447
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• 2023

This paper aims to develop a map for optimized class space using ZEP among the metaverse platforms. As a research method, the classroom space was organized so that the subject of learning became a learner, and the classroom space was modified and supplemented to optimize while being applied to elementary school computer classes. The contents of the study investigated learners' prior perception of metaverse, and compared and analyzed the advantages and disadvantages of the metaverse platform. In addition, the map was designed by reflecting the results of the survey, and after applying the map to the class, necessary APIs and apps were installed to supplement it. As a result, the learner became the subject of learning in the metaverse space, freely identified the space, and actively participated in the class. In particular, we found that students who were passive offline and those who had a low participation rate due to lack of skills participated more actively. In particular, students who were passive offline or whose participation was low due to lack of skills participated more actively. If API and JavaScript programs are added to collect log data of learners for learning analysis, real-time feedback is possible for learners, and learner feedback is possible for instructors with statistical data. If this is possible, the metaverse space can fully expect the role of a learning assistant for learners and a teaching assistant for instructors.

• Journal of the Korean School Mathematics Society
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• v.10 no.2
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• pp.263-288
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• 2007

The purpose of this study is to search the effective teaching-learning program by considering how affect on formation of the process-object perspective of linear function using Excel. In this study we analyzed function units in textbook and examined how Excel affect on the formation of the process-object perspective of linear function. Teaching experiment was based on qualitative case study and performed for five classes with five 8th graders. Data were gathered through observations, audio-taped interviews, video recording of the students 'work, students' worksheets, and detailed field notes. Findings indicate that exploration learning environment using Excel could supplement paper-and-pencil environment. We found that intuitive, dynamic, explorative, feedback skills via Excel can play the role of scaffolding supporting formation of process perspective object perspective of linear function.

• Korean Journal of Biological Psychiatry
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• v.12 no.2
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• pp.165-172
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• 2005

Objectives:The purpose of this study is to 1) conduct a discrimination analysis of schizophrenia and bipolar affective disorder using MMPI profile through artificial neural network analysis and logistic regression analysis, 2) to make a comparison between advantages and disadvantages of the two methods, and 3) to demonstrate the usefulness of artificial neural network analysis of psychiatric data. Procedure:The MMPI profiles for 181 schizophrenia and bipolar affective disorder patients were selected. Of these profiles, 50 were randomly placed in the learning group and the remaining 131 were placed in the validation group. The artificial neural network was trained using the profiles of the learning group and the 131 profiles of the validation group were analyzed. A logistic regression analysis was then conducted in a similar manner. The results of the two analyses were compared and contrasted using sensitivity, specificity, ROC curves, and kappa index. Results:Logistic regression analysis and artificial neural network analysis both exhibited satisfactory discriminating ability at Kappa index of greater than 0.4. The comparison of the two methods revealed artificial neural network analysis is superior to logistic regression analysis in its discriminating capacity, displaying higher values of Kappa index, specificity, and AUC(Area Under the Curve) of ROC curve than those of logistic regression analysis. Conclusion:Artificial neural network analysis is a new tool whose frequency of use has been increasing for its superiority in nonlinear applications. However, it does possess insufficiencies such as difficulties in understanding the relationship between dependent and independent variables. Nevertheless, when used in conjunction with other analysis tools which supplement it, such as the logistic regression analysis, it may serve as a powerful tool for psychiatric data analysis.