• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.117-129
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• 2022

The ability to creatively pursue new knowledge and perspectives across various disciplines has established itself as a basic literacy for living in the 21st-century convergence era. With the development of various creative education programs, assessment tools that can objectively and systematically evaluate learners' academic achievement are also required. Therefore, this paper proposed the self assessment, peer assessment, creativity assessment, and reflection tool based on the hyper blended practical model as assessment tools for creative convergence education programs for elementary and secondary school students. The developed assessment tools attempted to develop more completed evaluation methods by modifying two items and deleting four items through validity tests. In addition, the evaluation tool was applied to 596 elementary and secondary school students nationwide, and the application results were analyzed through one-way ANOVA and Wordcloud system. As a result of the analysis, it was found that the self assessment and the reflection tool need to develop questions according to the grade group. In addition, we proposed to use these assessment tools in blended classes or various educational activities in the changing classroom environment. We hope that this paper provides implications for developing evaluation systems and tools for creative convergence education.

• Journal of the Korean Chemical Society
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• v.66 no.2
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• pp.107-123
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• 2022

The purpose of this study is to investigate the effects of learning using computer-based science inquiry program. To this end, the three lessons computer-based science inquiry were developed in domain of material's properties. The developed program was put into K middle school located in Seoul and the effects were verified. For the experimental group, the three lessons computer-based science inquiry related to the separation of mixture were introduced, and for the comparison group, the contents presented in the textbook were introduced as a teacher-centered teaching method. To verify the effects of the program, 2-way ANCOVA was performed on positive experiences about science and science core competency, and 2-way ANOVA was performed on academic achievement. As a result of the study, there were significant differences between the two groups in positive experiernces about science and scientific core competencies and academic achievement (p<.05), and group^*gender interaction effect was only significant in academic achievement (p<.05). From the results of this study, we could see the possibility of using a computer-based science inquiry program as a chemistry teaching method that enables sustainable scientific inquiry.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.5
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• pp.328-334
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• 2022

The process that one may consciously focuses on necessary stimulation among tremendous amount of stimulation through human sensory systems is called attention in psychology. It is known that the attention can be affected by many factors such as room temperatures, humidity level, etc. In the field of sports science, ice packs are widely used for recovery from exercise fatigue providing fast heat transfer by conduction. However, the effect on attention by so-called iced-pack-cooling has not been tested. This research focuses on the attention levels when one is provided with a special cooling pad on their dorsal and lateral cervices. 40 subjects were divided into four groups and their attention level was evaluated based on the exposure conditions of combinations in reading and light walking with and without the cooling pad. The Frankfruter Aufmerksamkeits-Inventar, FAIR was used to evaluate the attention levels; the performance index, quality index, and continuity index consist of the FAIR test indicating the selectiveness of the attention, correctness of the attention, and maintaining term of the attention, respectively. Analysis of variance was carried out for those variables and post-hoc if applicable. When visual attention is constantly used for reading and studying, application of conductive heat transfer by the cooling pads is significantly helpful for improvement in selectiveness of the attention and maintaining terms of the attention levels. Also, light walking yielded improvement in selectiveness of the attention and maintaining terms of the attention levels; however one should presupposedly consider the loss of reading time.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.185-191
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• 2021

The purpose of this study is to develop middle school English classes using Problem-Based Learning(PBL) based on flipped learning and to examine its effects. Recently, various attempts to combine flipped learning and PBL have been made; however, many studies have not been applied to middle and high school curriculums yet. The attempt of this study is expected to have theoretical and practical significance. The instructional model was derived from the review of previous studies, and the development of instructional program followed the general design procedure(analysis-design-development-implement-evaluation), and its validity was secured with the advice of related experts. To verify the effectiveness of the program, the English academic achievement test and the English key competency test were conducted before and after the program. Changes in English academic achievement were analyzed by the paired-sample t-test, and the effect of key competency and the level of achievement test performance (high vs, low) on the pre-post score change was analyzed by the mixed effects repeated measures ANOVA. As a result of the analysis, both academic achievement and key competencies increased, and the low-level students in the pre-academic achievement test showed more improvements. In conclusion, the PBL class based on flipped learning is effective in improving the English academic achievement and key competencies of middle school students, and in particular, it is shown to be an effective teaching method for students with low academic achievement.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.376-386
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• 2023

Due to climate changes, landslide hazards in the Republic of Korea (hereafter South Korea) continuously increase. To establish the effective landslide mitigation strategies, such as erosion control works, landslide hazard estimation in the long-term perspective should be proceeded considering the influence of climate changes. In this study, we examined the change in landslide-damaged areas in South Korea responding to climate change scenarios using the multivariate regression method. Data on landslide-damaged areas and rainfall from 1981-2010 were used as a training dataset. Sev en indices were deriv ed from rainfall data as the model's input data, corresponding to rainfall indices provided from two SSP scenarios for South Korea: SSP1-2.6 and SSP5-8.5. Prior to the multivariate regression analysis, we conducted the VIF test and the dimension analysis of regression model using PCA. Based on the result of PCA, we developed a regression model for landslide damaged area estimation with two principal components, which cov ered about 93% of total v ariance. With climate change scenarios, we simulated landslide-damaged areas in 2030-2100 using the regression model. As a result, the landslide-damaged area will be enlarged more than the double of current annual mean landslide damaged area of 1981-2010; It infers that landslide mitigation strategies should be reinforced considering the future climate condition.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.207-221
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• 2023

This study suggests deep neural network models for estimating air temperature with Level 1B (L1B) datasets of GEO-KOMPSAT-2A (GK-2A). The temperature at 1.5 m above the ground impact not only daily life but also weather warnings such as cold and heat waves. There are many studies to assume the air temperature from the land surface temperature (LST) retrieved from satellites because the air temperature has a strong relationship with the LST. However, an algorithm of the LST, Level 2 output of GK-2A, works only clear sky pixels. To overcome the cloud effects, we apply a deep neural network (DNN) model to assume the air temperature with L1B calibrated for radiometric and geometrics from raw satellite data and compare the model with a linear regression model between LST and air temperature. The root mean square errors (RMSE) of the air temperature for model outputs are used to evaluate the model. The number of 95 in-situ air temperature data was 2,496,634 and the ratio of datasets paired with LST and L1B show 42.1% and 98.4%. The training years are 2020 and 2021 and 2022 is used to validate. The DNN model is designed with an input layer taking 16 channels and four hidden fully connected layers to assume an air temperature. As a result of the model using 16 bands of L1B, the DNN with RMSE 2.22℃ showed great performance than the baseline model with RMSE 3.55℃ on clear sky conditions and the total RMSE including overcast samples was 3.33℃. It is suggested that the DNN is able to overcome cloud effects. However, it showed different characteristics in seasonal and hourly analysis and needed to append solar information as inputs to make a general DNN model because the summer and winter seasons showed a low coefficient of determinations with high standard deviations.

• Journal of The Korean Association For Science Education
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• v.22 no.4
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• pp.872-881
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• 2002

Student questioning is included in the priority of science literacy, to enable students to solve problems by exploring questions, communicating and constructing knowledge(AAAS, 1989). Also, the essence of student questioning in science lies in its function as a link between thinking and learning. But educators did not pay much attention to students' questioning in Korea. The purpose of this study was to investigate the effects of science question enhancement instruction on students' science questioning level and achievement. Also, this study showed the effects of other variables(logical thinking, science achievement, interest, and gender) on students' science questioning level. The pretest-posttest control group design group design was used. The sample was consisted of 80 second grade middle school students in experimental group(Science question enhancement instruction) and 74 students in control group(Traditional learning). Students in both groups were received identical content instruction on the unit 'Structures and functions of plant'. These groups were treated for 15 hours during 6 weeks. Students' questions were rated using the four levels described by the Middle School Students' Science Question Rating Scale(r= .96,)(Cuccio-Schirripa & Steinner, 2000). Science achievement data were collected using a 17 item multiple choice test(Cronbach ${\alpha}$= .84). To investigate students' logical thinking ability, a abridged GALT(Cronbach ${\alpha}$= .69) was used. Five-way ANOVA, ANCOVA, and multiple regression analysis were used to analyze the results. The results indicated that students who received instruction on researchable questioning outperformed those students who were not instructed on high-order questioning(p< .01). Results of correlations indicated that instruction(r= .640), science achievement(r= .311) and logical thinking ability(r= .212) was significantly and positively related with students' questioning level. But, interest and gender did not show any significant correlation with students' questioning level. Science question enhancement instruction was more effective on science achievement than the traditional instruction(p< .01).

• Korean Journal of Psychosomatic Medicine
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• v.24 no.1
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• pp.102-108
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• 2016

Objectives : The deficit of recognition memory has been found as one of the common neurocognitive impairments in patients with schizophrenia. In addition, they were reported to fail to enhance the memory about emotional stimuli. Previous studies have shown that bilateral eye movements enhance the memory retrieval. Therefore, this study was conducted in order to investigate the memory enhancement of bilaterally alternating eye movements in schizophrenic patients. Methods : Twenty one patients with schizophrenia participated in this study. The participants learned faces (angry or neutral faces), and then performed a recognition memory task in relation to the faces after bilateral eye movements and central fixation. Recognition accuracy, response bias, and mean response time to hits were compared and analysed. Two-way repeated measure analysis of variance was performed for statistical analysis. Results : There was a significant effect of bilateral eye movements condition in mean response time(F=5.812, p<0.05) and response bias(F=10.366, p<0.01). Statistically significant interaction effects were not observed between eye movement condition and face emotion type. Conclusions : Irrespective of the emotional difference of facial stimuli, recognition memory processing was more enhanced after bilateral eye movements in patients with schizophrenia. Further study will be needed to investigate the underlying neural mechanism of bilateral eye movements-induced memory enhancement in patients with schizophrenia.

• The Journal of Sustainable Design and Educational Environment Research
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• v.21 no.3
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• pp.1-13
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• 2022

This study is a case study to identify the spatial composition and structural problems of existing schools for spatial innovation as a future school that can operate a credit system for old high schools and establish a mid-to-long-term arrangement plan as a credit system operating school capable of various teaching and learning in the future. The study results are as follows: First, most of the problems of the old high schools entailed that there was very poor connectivity between buildings as most of them were arranged in a single, standard design-type unit building and distributed in multiple buildings. In addition, the floor plan of each building is suggested to be a structure in which student exchange and rest functions cannot be achieved during the break period due to the spatial composition of the classroom and hallway concepts. Second, in the direction of the high school space configuration for future school space innovation, the arrangement plan should be established by reflecting the collective arrangement in consideration of the shortening of the movement route and the expansion of subject areas due to the movement of students on the premise of the subject classroom system. Moreover, it is desirable to provide a square-type space for rest and exchange in the central area where communication and exchange are possible according to the moving class. Third, as the evaluation criteria for relocating old high schools, a space program is prepared based on the number of classes in the future, and legal analysis of school land use and land use efficiency analysis considering regional characteristics are conducted. Based on such analysis data, mid-to-long-term land use plans and space arrangement plans for the entire school space such as the school facility complex are established.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.39-55
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• 2019

Recently banks and large financial institutions have introduced lots of Robo-Advisor products. Robo-Advisor is a Robot to produce the optimal asset allocation portfolio for investors by using the financial engineering algorithms without any human intervention. Since the first introduction in Wall Street in 2008, the market size has grown to 60 billion dollars and is expected to expand to 2,000 billion dollars by 2020. Since Robo-Advisor algorithms suggest asset allocation output to investors, mathematical or statistical asset allocation strategies are applied. Mean variance optimization model developed by Markowitz is the typical asset allocation model. The model is a simple but quite intuitive portfolio strategy. For example, assets are allocated in order to minimize the risk on the portfolio while maximizing the expected return on the portfolio using optimization techniques. Despite its theoretical background, both academics and practitioners find that the standard mean variance optimization portfolio is very sensitive to the expected returns calculated by past price data. Corner solutions are often found to be allocated only to a few assets. The Black-Litterman Optimization model overcomes these problems by choosing a neutral Capital Asset Pricing Model equilibrium point. Implied equilibrium returns of each asset are derived from equilibrium market portfolio through reverse optimization. The Black-Litterman model uses a Bayesian approach to combine the subjective views on the price forecast of one or more assets with implied equilibrium returns, resulting a new estimates of risk and expected returns. These new estimates can produce optimal portfolio by the well-known Markowitz mean-variance optimization algorithm. If the investor does not have any views on his asset classes, the Black-Litterman optimization model produce the same portfolio as the market portfolio. What if the subjective views are incorrect? A survey on reports of stocks performance recommended by securities analysts show very poor results. Therefore the incorrect views combined with implied equilibrium returns may produce very poor portfolio output to the Black-Litterman model users. This paper suggests an objective investor views model based on Support Vector Machines(SVM), which have showed good performance results in stock price forecasting. SVM is a discriminative classifier defined by a separating hyper plane. The linear, radial basis and polynomial kernel functions are used to learn the hyper planes. Input variables for the SVM are returns, standard deviations, Stochastics %K and price parity degree for each asset class. SVM output returns expected stock price movements and their probabilities, which are used as input variables in the intelligent views model. The stock price movements are categorized by three phases; down, neutral and up. The expected stock returns make P matrix and their probability results are used in Q matrix. Implied equilibrium returns vector is combined with the intelligent views matrix, resulting the Black-Litterman optimal portfolio. For comparisons, Markowitz mean-variance optimization model and risk parity model are used. The value weighted market portfolio and equal weighted market portfolio are used as benchmark indexes. We collect the 8 KOSPI 200 sector indexes from January 2008 to December 2018 including 132 monthly index values. Training period is from 2008 to 2015 and testing period is from 2016 to 2018. Our suggested intelligent view model combined with implied equilibrium returns produced the optimal Black-Litterman portfolio. The out of sample period portfolio showed better performance compared with the well-known Markowitz mean-variance optimization portfolio, risk parity portfolio and market portfolio. The total return from 3 year-period Black-Litterman portfolio records 6.4%, which is the highest value. The maximum draw down is -20.8%, which is also the lowest value. Sharpe Ratio shows the highest value, 0.17. It measures the return to risk ratio. Overall, our suggested view model shows the possibility of replacing subjective analysts's views with objective view model for practitioners to apply the Robo-Advisor asset allocation algorithms in the real trading fields.