• Journal of Gifted/Talented Education
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• v.19 no.1
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• pp.95-117
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• 2009

This study investigated the relationships of the self-regulated learning strategies used in both science and English classes and motivation to academic performance of science-gifted high school students. Participants of this study were 144 freshmen of Korea Science Academy It was found out that the use of self-regulation learning strategies and motivation exerts differential influence on the academic performance of science-gifted students, depending on the subjects they study. Results showed that they used more vigorously in science class those self-regulated strategies which consist of cognition, metacognition, and resource management strategies than in English class. In addition, their motivation level in science class was significantly higher than that in English class. Self-regulated strategies did not explain any variance in physics GPA. Task value among the motivation variables accounted for 2 percent of variance in physics GPA. Metacognition and time and study environment variables explained 8 percent and 15 percent of variance in English GPA, respectively. Self-efficacy in motivation accounted for 30 percent of variance in English GPA, These results were discussed in the light of instruction for science-gifted high students.

• Journal of The Korean Association For Science Education
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• v.27 no.7
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• pp.547-558
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• 2007

The purpose of this study is to compare inquiry activities in science textbooks' physics contents for Korean secondary schools with those of Singapore in order to provide a reference for further improvement of inquiry activities in Korean science textbooks. We analyzed inquiry activities using the framework of Millar et al.(1998) and Chinn & Malhotra (2002). The results of this study are as follows: There are differences between Korean and Singaporean inquiry activities in the area of 'learning objectives', 'students' thinking activities' and 'degree of openness'. In the area of 'learning objectives', the Korean textbooks have more activities associated with the learning of science content than those in Singaporean, whereas the Singaporean textbooks have more activities associated with the processes of scientific inquiry than in Korean textbooks. In the area of 'students' thinking activities', the Singaporean textbooks have activities like 'test a prediction', which Korean textbooks lack. The 'degree of openness' is higher in Singaporean textbooks than in Korean textbooks. And some differences in the area of 'authentic scientific inquiry' between Korean and Singaporean textbooks were also found. While the Korean textbooks do not have any activities associated with 'generating research questions', the Singaporean ones feature such activities. In the area of 'designing studies', the Singaporean textbooks have activities corresponding to 'selecting variables' and 'controlling variables', while the Korean ones never have such activities. The results of this study imply that it is necessary to balance inquiry activities in the area of 'learning objectives', 'students' thinking activities' and 'degree of openness', and to present activities close to authentic scientific inquiry in inquiry activities in textbooks.

• Journal of the Korean Chemical Society
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• v.55 no.5
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• pp.875-881
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• 2011

This study examined factors influencing college science learning from the perspectives of college students and high school science teachers. Using a survey created based on focus group interviews, college science majors and high school science teachers rated various factors of high school learning that positively influenced college science learning. Findings suggested that the perceptions differed by college major: the physics major students considered math proficiency and logical thinking skills as the important factors; chemistry major students and biology major students considered English proficiency and basic scientific knowledge as the most important factors. Both college students and science teachers emphasized basic science knowledge and math proficiency. However, differences between the two groups were also found in that the students perceived more need to learn about experimentation than the teachers whereas the teachers had a priority in increasing advanced science content.

• KIISE Transactions on Computing Practices
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• v.23 no.11
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• pp.625-631
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• 2017

The stock price prediction for stock markets remains an unsolved problem. Although there have been various overtures and studies to predict the price of stocks scientifically, it is impossible to predict the future precisely. However, stock price predictions have been a subject of interest in a variety of related fields such as economics, mathematics, physics, and computer science. In this paper, we will study fluctuation patterns of stock prices and predict future trends using the Deep learning. Therefore, this study presents the three deep learning models using Tensorflow, an open source framework in which each learning model accepts different input features. We expand the previous study that used simple price data. We measured the performance of three predictive models increasing the number of priced-based input features. Through this experiment, we measured the performance change of the predictive model depending on the price-based input features. Finally, we compared and analyzed the experiment result to evaluate the impact of the price-based input features in stock price prediction.

• Journal of The Korean Association For Science Education
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• v.13 no.1
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• pp.100-120
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• 1993

Middle school students' conceptual changes on physics, chemistry, biology and earth science concepts which were intentionally selected by researchers had been investigated through traditional teaching and learning by paper and pencil tests and P.O.E. The weak points had been studied by individual interviews about the problems of traditional science classroom teaching after students' testing and learning about science concepts. As results, students' conceptual changes could be hardly found through traditional teaching and learning except several concepts in biology, The weak points of traditional science classroom teaching and learning were as follows: 1) Teachers teach science as finding answers. 2) The conventional science test is not performed to find students' concepts out but to recall simple knowledge or calculus. 3) Students hesitate to ask teacher Questions in science class because of their colleagues' or teachers' blame. These mean that science teachers need specially designed teaching methods on the students' concepts and reseachers had to study about science classroom socialogy, what happened in science classrooms.

• Journal of The Korean Association For Science Education
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• v.31 no.8
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• pp.1175-1185
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• 2011

Language skills in science education seem to have a great impact on student achievement. Most of the language skills affecting students' science learning can be accounted for an understanding of scientific terms. The ultimate goal of this study is selecting and grading the scientific terms for science education. As a basic research, we investigated scientific terms contained in science textbooks, because they are the most basic and selected terminologies. As a result of investigation of scientific terms in physics units of middle school science textbooks, we made a list of 556 scientific terms by grade level. This includes 249 words for grade 7, 170 words for grade 8, and 137 words for grade 9.

• Journal of the Korean earth science society
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• v.27 no.7
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• pp.730-744
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• 2006

The United States curriculum reform movement has recently started in each area of science education. The initiatives on curriculum reform stem from a notion that the low rate of science curricula offered in schools has been a serious problem. The schools in the United States are not only facing a lack of offerings within science curricula but also low enrollment in science courses, especially in physics, chemistry, and earth science. This trend resulted in low performances on international achievement tests including TIMSS and PISA. This paper introduces the efforts to solve existing problems through curriculum reform; including ChemCom, BioCom, EarthComm, and Active Physics. In this paper, a discussion is presented to show how the curricula can help address the status quo in science education. More specifically, this paper focuses on curriculum reform in high school earth science (EarthComm), providing a closer look at the scope and sequence of the reform movement. EarthComm was chosen because it was released based on the development of the National Science Education Standards (NRC, 1996). Consequently, EarthComm became a curriculum that espoused the visions of the Standards, which has been guiding the reform of the US curriculum. At the end of this paper, two research outcomes of the EarthComm curriculum implementation in schools are discussed in terms of student learning and differences from conventional curricula.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.1
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• pp.31.2-31.2
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• 2021

To estimate the contribution of quasars on keeping the IGM ionized, building a quasar luminosity function (LF) is necessary. Quasar LFs derived from multiple quasar surveys, however, are incompatible, especially for the faint regime, emphasizing the need for deep images. In this study, we construct quasar LF reaching M₁₄₅₀~-21.5 AB magnitude at z ~ 5, which is 1.5 mag deeper than previously reported LFs, using deep images from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). We trained an artificial neural network (ANN) by inserting the colors as inputs to classify the quasars at z ~ 5 from the late-type stars and low-redshift galaxies. The accuracy of ANN is > 99 %. We also adopted the Bayesian information criterion to elaborate on the quasar-like objects. As a result, we recovered 5/5 confirmed quasars and remarkably minimized the contamination rate of high-redshift galaxies by up to six times compared to the selection using color selection alone. The constructed quasar parametric LF shows a flatter faint-end slope α=-127^+0.16_-0.15 similar to the recent LFs. The number of faint quasars (M₁₄₅₀ < -23.5) is too few to be the main contributor to IGM ionizing photons.

• Journal of The Korean Association For Science Education
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• v.35 no.3
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• pp.363-374
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• 2015

The purpose of this study is to investigate the learning contents presented in high school science and in pre-service science textbooks of college of education, and to examine educational implications for pre-service science teachers by analysing their connection to each other. High school science is called as 'convergence science.' Seven high school science textbooks and eleven science textbooks related to physics, chemistry, biological science, and earth science for pre-service teachers were selected to analyse learning contents. The relationship between high school science with those of college-level science textbooks for pre-service science teachers was found when the learning contents were compared. Science textbooks for pre-service science teachers have the biggest number of learning contents on the chapter 'Energy and Environment' of high school science. About 86.6% of learning contents of high school science were introduced on textbooks on science, but pre-service teachers should learn the remainder. The part of learning contents presented in high school science textbooks was higher than the college-level for pre-service science teachers. Moreover, the part of learning contents was included in Engineering & Technology. And these required a special teacher education. Accordingly, the results suggested that learning contents for high school science should be optimized and reduced. Also, various educational programs should be developed and educational curriculum for pre-service science teachers should be revised.

• Journal of The Korean Astronomical Society
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• v.52 no.6
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• pp.217-225
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• 2019

We apply a modified Convolutional Neural Network (CNN) model in conjunction with transfer learning to predict whether an active region (AR) would produce a ≥C-class or ≥M-class flare within the next 24 hours. We collect line-of-sight magnetogram samples of ARs provided by the SHARP from May 2010 to September 2018, which is a new data product from the HMI onboard the SDO. Based on these AR samples, we adopt the approach of shuffle-and-split cross-validation (CV) to build a database that includes 10 separate data sets. Each of the 10 data sets is segregated by NOAA AR number into a training and a testing data set. After training, validating, and testing our model, we compare the results with previous studies using predictive performance metrics, with a focus on the true skill statistic (TSS). The main results from this study are summarized as follows. First, to the best of our knowledge, this is the first time that the CNN model with transfer learning is used in solar physics to make binary class predictions for both ≥C-class and ≥M-class flares, without manually engineered features extracted from the observational data. Second, our model achieves relatively high scores of TSS = 0.640±0.075 and TSS = 0.526±0.052 for ≥M-class prediction and ≥C-class prediction, respectively, which is comparable to that of previous models. Third, our model also obtains quite good scores in five other metrics for both ≥C-class and ≥M-class flare prediction. Our results demonstrate that our modified CNN model with transfer learning is an effective method for flare forecasting with reasonable prediction performance.