• Journal of the Korean Chemical Society
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• v.66 no.5
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• pp.362-375
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• 2022

In this study, science teachers' NOS lessons were observed and the characteristics of the lessons were analyzed. Three science teachers who taught NOS in the 'Science Inquiry Experiment' developed under the 2015 revised curriculum participated in the study. Their NOS lessons were observed and interviews were conducted before and after lessons. The collected data were analyzed using analytical induction and constant comparative method. The analyses of the result revealed the teachers' naive views on NOS were also revealed during the lessons. There were some cases where they showed naive views during the lessons even if they showed informed views in the interviews. Although the domains of NOS taught by them were diverse, all of them taught 'tentativeness' and considered this an important goal. They tended to teach NOS with content related with their major, and teaching NOS was found to be deeply related to their major. In the activity where students learn NOS by inferring the unknown object, teachers disclosed the unknown object, which is unlike the rule of the activity. They thought that could help students' learning. At last, although they emphasized teaching NOS, they either did not assess NOS or assessed NOS in a limited way. Based on the results, some directions for teacher education and follow-up study are suggested.

• Journal of Appropriate Technology
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• v.6 no.2
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• pp.200-207
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• 2020

The purpose of the establishment of Fab Lab is to promote the sustainable development of local communities around the world. To this end, The Fab foundation are preparing a resource-circulating society that maintains a city's self-sufficiency rate of 50% or more by 2054. In developed countries, Fab Lab is not only a manufacturing space for startup support, but an open innovation space for learning and creation. In addition, in emerging countries, Fab Lab is playing a role as a digital production center to create and share appropriate new technologies by reflecting the needs of local communities. India has 70 Fab Labs, the largest emerging country, ahead of Russia's 48. India's Fab Lab is conducting a collaboration project through regular meetings held every six months. The subject of this study, Fab Lab Vigyan Ashram, is defined as a place to transfer the concept of digital lab to alternative schools in rural India. In this study, we looked at a case in which an alternative school for an agricultural community called Vigyan Ashram, the modern version of the Gurukula system, successfully combined with the digital fabrication called Fab Lab to become a new citizen-led making community of the 4th Industrial Revolution. Based on this, we explored the development model of the Indian Fab Lab that fits the local situation.

• Journal of Engineering Education Research
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• v.24 no.4
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• pp.3-20
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• 2021

As we have become more interested in 'competency' that means ability to do something around the world, the competency of the best performers has also been introduced in the university curriculum as a concept of core competency. Research continues on why this competency-based education is needed compared to existing academic-oriented education, how it can be introduced into existing curricula, and how it can be developed and evaluated in detail. This study develops and validates core competency assessment tools that can diagnose core competencies of engineering students. Therefore, this research paper conducted a literature review related to core competencies and also core competency assessment tools of university students. It seeks to explore the implications of core competency assessment tools for engineering students and then lay the foundation for competency-based teaching and learning at engineering colleges. And also it defines the concepts of core competencies and each core competency of engineering students through prior research analysis of competence, core competence, and core competence of university students. The primary core competency assessment tool consisted of sub-factors and questions of core competencies. It were modified through the expert validation of the primary one and then it was used as a core competency assessment tools for preliminary investigation. The core competency assessment tools for engineering students are consisted of 6 competencies, 22 sub-factors, and 91 questions. There are core competencies as follows: engineering basic competencies, major engineering competencies, self-management competencies, communication competencies, interpersonal competencies, global competencies. The preliminary survey was conducted on 426 engineering students attending the Engineering Education FESTA 2019. The preliminary findings were derived by conducting exploratory factor analysis, confirmatory factor analysis, question characteristics analysis, and reliability analysis for validation. The core competency assessment tools developed through this study can be used to verify the effectiveness of the curriculum and programs for students at engineering colleges. In addition, the developed core competencies, sub-factors, and questions can be utilized in a series of courses that design, conduct, and evaluate engineering curricula and programs as competency-based curriculum. The significance of this study is to lay the groundwork for providing competency-based education engineering students to develop core competencies.

• Ecology and Resilient Infrastructure
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• v.8 no.2
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• pp.112-119
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• 2021

In 2012, the National Park Service conducted an ecological health assessment to efficiently preserve and manage the ecosystem. The need for improving pre-existing management indicators was recognized from the revised Natural Park Act because, while the indicators of the existing evaluation system focused on endangered species, ecosystem disturbance, diversity, water quality (BOD, DO), and habitat fragmentation, they did not reflect the lack of indicators for marine ecological assessment, policy changes, and the time demands. The evaluation results comprised a five-point grading system, which made the analysis of immediate changes, difficult. Therefore, the benthic pollution index (BPI) and habitat restoration indicators were added to improve the evaluation system. The National Park was assessed using 10 classifications, however, only four classifications were evaluated. The ratings were divided into five states, and ten classes were presented as pictograms. The assessment results showed a similar trend as the indicators were improved, increasing from level 3 to level 5. However, the results of the Wolaksan National Park after improvement in the indicators were lower than that before the improvement, whereas, for the Juwangsan National Park, it was higher. This study aims at contributing to the scientific and systematic management of the national park ecosystem by improving the ecological health assessment system.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.4
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• pp.109-118
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• 2022

The data of the missing section among the vertex surface sea temperature observation data was imputed using the Bidirectional Recurrent Neural Network(BiRNN). Among artificial intelligence techniques, Recurrent Neural Networks (RNNs), which are commonly used for time series data, only estimate in the direction of time flow or in the reverse direction to the missing estimation position, so the estimation performance is poor in the long-term missing section. On the other hand, in this study, estimation performance can be improved even for long-term missing data by estimating in both directions before and after the missing section. Also, by using all available data around the observation point (sea surface temperature, temperature, wind field, atmospheric pressure, humidity), the imputation performance was further improved by estimating the imputation data from these correlations together. For performance verification, a statistical model, Multivariate Imputation by Chained Equations (MICE), a machine learning-based Random Forest model, and an RNN model using Long Short-Term Memory (LSTM) were compared. For imputation of long-term missing for 7 days, the average accuracy of the BiRNN/statistical models is 70.8%/61.2%, respectively, and the average error is 0.28 degrees/0.44 degrees, respectively, so the BiRNN model performs better than other models. By applying a temporal decay factor representing the missing pattern, it is judged that the BiRNN technique has better imputation performance than the existing method as the missing section becomes longer.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.29-35
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• 2022

UV rays have beneficial or harmful effects on the human body depending on the degree of exposure. An accurate UV information is required for proper exposure to UV rays per individual. The UV rays' information is provided by the Korea Meteorological Administration as one component of daily weather information in Korea. However, it does not provide an accurate UVI at the user's location based on the region's Ultraviolet index. Some operate measuring instrument to obtain an accurate UVI, but it would be costly and inconvenient. Studies which assumed the UVI through environmental factors such as solar radiation and amount of cloud have been introduced, but those studies also could not provide service to individual. Therefore, this paper proposes a deep learning model to calculate UVI using solar object information and sunlight characteristics to provide an accurate UVI at individual location. After selecting the factors, which were considered as highly correlated with UVI such as location and size and illuminance of sun and which were obtained through the analysis of sky images and solar characteristics data, a data set for DNN model was constructed. A DNN model that calculates the UVI was finally realized by entering the solar object information and sunlight characteristics extracted through Mask R-CNN. In consideration of the domestic UVI recommendation standards, it was possible to accurately calculate UVI within the range of MAE 0.26 compared to the standard equipment in the performance evaluation for days with UVI above and below 8.

• Therapeutic Science for Rehabilitation
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• v.11 no.3
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• pp.81-92
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• 2022

Objectives : This study aimed to investigate the effect of beat-keeping games in smartphone applications on improving executive functions in children with developmental delays. Methods : Three children diagnosed with developmental delay were included in this study. The ABA design used a single-subject experimental research design. The independent variable was the beat-keeping game. The game was held three times a week for a total of seven times for 20 minutes, including breaks. The dependent variable, "Visual-motor speed," was measured every session to assess if the beat-keeping game was effective in improving the participant's executive function. Further, before and after the intervention, "Children's Color Trails Test (CCTT)", "Block design," and "Finding hidden picture" were measured. Results : All three participants showed improvement in the performance of the beat-keeping game and the executive functions of "Visual-motor speed" and visual attention. Conclusions : Based on the results of this study, various effective applications for learning and intervention can be developed and applied to children with developmental delays who have difficulty in motivating themselves and lack attention.

• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.855-863
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• 2022

In this study, the Artificial Neural Network (ANN) was used to mapping air temperature in Seoul. MODerate resolution Imaging Spectroradiomter (MODIS) data was used as auxiliary data for mapping. For the ANN network topology optimizing, scatterplots and statistical analysis were conducted, and input-data was classified and combined that highly correlated data which surface temperature, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), time (satellite observation time, Day of year), location (latitude, hardness), and data quality (cloudness). When machine learning was conducted only with data with a high correlation with air temperature, the average values of correlation coefficient (r) and Root Mean Squared Error (RMSE) were 0.967 and 2.708℃. In addition, the performance improved as other data were added, and when all data were utilized the average values of r and RMSE were 0.9840 and 1.883℃, which showed the best performance. In the Seoul air temperature map by the ANN model, the air temperature was appropriately calculated for each pixels topographic characteristics, and it will be possible to analyze the air temperature distribution in city-level and national-level by expanding research areas and diversifying satellite data.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.77-89
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• 2022

It has been proven through many previous researches that the pretrained language model with a large corpus helps improve performance in various natural language processing tasks. However, there is a limit to building a large-capacity corpus for training in a language environment where resources are scarce. Using the Cross-lingual Post-Training (XPT) method, we analyze the method's efficiency in Korean, which is a low resource language. XPT selectively reuses the English pretrained language model parameters, which is a high resource and uses an adaptation layer to learn the relationship between the two languages. This confirmed that only a small amount of the target language dataset in the relationship extraction shows better performance than the target pretrained language model. In addition, we analyze the characteristics of each model on the Korean language model and the Korean multilingual model disclosed by domestic and foreign researchers and companies.

• Journal of the Korean Society of Earth Science Education
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• v.15 no.2
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• pp.263-272
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• 2022

The purpose of this study is to investigate the effect of developing and applying a program in the field of astronomy that can improve the spatial perception ability and task commitment of elementary science gifted students. The subjects of this study were 22 students in the advanced course in the elementary science gifted class affiliated with the Gifted and Talented Center of University B. In order to improve spatial perception ability and task attachment to students in elementary school science gifted class, a total of 12 educational learning programs were developed and applied. The results of this study were interpreted as quantitative analysis. The results of this study are as follows. First, the astronomy class had a positive effect on the spatial perception ability improvement of elementary science gifted students. Second, the astronomy class had a positive effect on improving the task commitment of elementary school science gifted students. Third, astronomy class of elementary school science gifted students was more effective in improving spatial perception than improving task commitment. Since elementary school science gifted students are selected with excellent intelligence, creativity, and task commitment, an Individualized Education Program (IEP) is developed and applied to better express their potential giftedness. In addition, in order to express more in-depth giftedness in gifted education, it is necessary to pay attention to the development of programs that can express individual gifted characteristics.