• Korean Journal of Child Studies
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• v.14 no.2
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• pp.79-94
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• 1993

The purpose of this study was (1) to investigate whether linguistic contrast helps children map a new word into a specific semantic domain when a new word is introduced, (2) to examine the existence of a hierarchy of domains into which children will place a new word, (3) to examine whether children's existing lexicons affect how children map a new word. A total of 320 children from 3 to 6 years of age were drawn from Pusan, Korea. The children were divided into one of four age groups. There were 80 children in each age group. In each group, children were randomly assigned to one of four groups; the linguistic contrast group exposed to color, the linguistic contrast group exposed to shape, a label group and control group. All of the children were tested for production and comprehension of the new word. The results of this study were as follows; (1) The linguistic contrast helped children learn the meanings of a new word. Especially, children age 4 or more showed a significant effect for linguistic contrast; however, it was not sufficient to teach 3-year-old the correct, referent of a term. (2) There was a hierarchy of domains into which children mapped a new word. There was no significant effect for domains into which 3-year-old children mapped the new word, but from 4 years of age children showed a preference for assuming a new word refered to an object's shape rather than its color. (3) Children's existing lexicon had no effect, on how children comprehend a new word.

• Proceedings of the Korea Crystallographic Association Conference
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• 2002.11a
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• pp.4-4
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• 2002

PDZ domains bind to short segments within target proteins in a sequence-specific fashion. GRIP/ABP family proteins contain six to seven PDZ domains and interact via its sixth PDZ domain (class Ⅱ) with the C-termini of various proteins, including liprin-α. In addition the PDZ456 domain mediates the formation of homo- and heteromultimers of GRIP proteins. To better understand the structural basis of peptide recognition by a class Ⅱ PDZ domain and DZ-mediated multimerization, we determined the crystal structures of the GRIPI PDZ6 domain, alone and in complex with a synthetic C-terminal octapeptide of human liprin-α, at resolutions of 1.5 Å and 1.8 Å, respectively. Remarkably, unlike other class Ⅱ PDZ domains, Ile736 at αB5 rather than conserved Leu732 at αB1 makes a direct hydrophobic contact with the side chain of the Tyr at the -2 position of the ligand. Moreover, the peptide-bound structure of PDZ6 shows a slight reorientation of helix αB, indicating that the second hydrophobic pocket undergoes a conformational adaptation to accommodate the bulkiness of the Tyr's side chain, and forms an antiparallel dimer through an interface located at a site distal to the peptide-binding groove. This configuration may enable formation of GRIP multimers and efficient clustering of GRIP-binding proteins.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.225-238
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• 2022

Although the importance of literacy in Artificial Intelligence (AI) education is increasing, there is a lack of testing tools for measuring such competency. To address this gap, this study developed a testing tool that measures AI literacy among middle school students. This goal was achieved through the establishment of an expert group that was enlisted to determine the relevant factors and items covered by the proposed tool. To verify the reliability and validity of the developed tool, a field review, exploratory factor analysis, and confirmatory factor analysis were conducted. These procedures resulted in a testing tool comprising six domains that encompass 30 items. The domains are the social impact of AI (eight items), the understanding of AI (six items), AI execution plans (five items), problem solving with AI (five items), data literacy (four items), and AI ethics (two questions). The items are to be rated using a five-point Likert scale. The internal consistency of the tool was .970 (total), while that of the domains ranged from .861 to .939. This study can serve as reference for developing the analysis of AI literacy, teaching and learning, and evaluation in AI education.

• Communications of Mathematical Education
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• v.34 no.3
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• pp.299-324
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• 2020

The purpose of this study was to identify high school students' mathematics learning style and its characteristics according to their personality disposition types and to propose mathematics learning strategies fit into each personality disposition type. For this purpose, MBTI personality test and survey to find mathematics learning style for 375 high school students were executed. The results were as follows. First, many students highly evaluated the effects of private education and prefer reference book to textbook. Second, there were significant differences on following variable domains of mathematics learning style such as learning attitude, learning habit(concentrativeness to concept understanding), problem solving strategies(effort for problem comprehension, use of various strategies), self management(metacognition) by MBTI personality disposition types(SJ, SP, NT, NF groups). Third, based on the results, the following mathematics learning strategies fit into each personality disposition type were recommended. SJ type students are needed to effort creative approach for open problem and to use mindmap as mathematics learning strategy. SP type students are needed to fulfill stepwise problem solving process and to effort constantly practice long/short term learning objectives. NT type students are needed to expand opportunity to study with friends and to use SRN(self reflection note) or mathematics journal writings as mathematics learning strategy. NF type students are needed to use mathematics learning note writing activity which include logical basis for each step of problem solving and to invest more time on learning algebra which need meticulous calculation.

• Journal of Science Education
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• v.35 no.2
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• pp.240-249
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• 2011

The purposes of this study is to compare the beliefs in the nature of science, science teaching and learning of the elementary teachers in charge of the gifted and the general teachers. For this study, a survey on beliefs of the nature of science, science teaching and learning was conducted to 88 elementary teachers for the gifted and 90 elementary general teachers. Data was analyzed by their academic career and major. The results of this study were as follows: There were no significant differences in beliefs in the nature of science and science teaching between the elementary science teachers in charge of the gifted and the general elementary teachers, but the former has a more constructivism in science learning than the latter. In the some sub-domains of the beliefs of the nature of science, science teaching and learning, there were statistically significant differences according to their academic career and major. Implications from findings of this study were suggested, such as recruiting and in-service training system for teachers in charge of the gifted.

• Journal of Korean Society for Quality Management
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• v.48 no.3
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• pp.511-520
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• 2020

Purpose: The purpose of this study was to devise an accurate machine learning model for predicting silica concentrations following the addition of impurities, through time series analysis of mining data. Methods: The mining data were preprocessed and subjected to time series analysis using the machine learning model. Through correlation analysis, valid variables were selected and meaningless variables were excluded. To reflect changes over time, dependent variables at baseline were treated as independent variables at later time points. The relationship between independent variables and the dependent variable after n point was subjected to Pearson correlation analysis. Results: The correlation (R2) was strongest after 3 hours, which was adopted as a dependent variable. According to root mean square error (RMSE) data, the proposed method was superior to the other machine learning methods. The XGboost algorithm showed the best predictive performance. Conclusion: This study is important given the current lack of machine learning studies pertaining to the domestic mining industry. In addition, using time series analysis in mining data will show further improvement. Before establishing a predictive model for the proposed method, predictions should be made using data with time series characteristics. After doing this work, it should also improve prediction accuracy in other domains.

• Journal of the Korea Convergence Society
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• v.9 no.10
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• pp.21-28
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• 2018

To help users who are experiencing difficulties finding the right learning course corresponding to their level of proficiency, we developed a recommendation model for personalized learning course for Intelligence Tutoring System(ITS). The Personalized Learning Course Recommendation model for ITS analyzes the learner profile and extracts the keyword by calculating the weight of each word. The similarity of vector between extracted words is measured through the cosine similarity method. Finally, the three courses of top similarity are recommended for learners. To analyze the effects of the recommendation model, we applied the recommendation model to the Women's ability development center. And mean, standard deviation, skewness, and kurtosis values of question items were calculated through the satisfaction survey. The results of the experiment showed high satisfaction levels in accuracy, novelty, self-reference and usefulness, which proved the effectiveness of the recommendation model. This study is meaningful in the sense that it suggested a learner-centered recommendation system based on machine learning, which has not been researched enough both in domestic, foreign domains.

• School Mathematics
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• v.5 no.4
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• pp.541-553
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• 2003

The purposes of this study are to look into the changing processes of mathematical beliefs and attitudes of the students and to propose the plans how to manage cooperative learning, what can contribute to cognitive affective domains of mathematics learning in applying STAD-based cooperative loaming to mathematics class. So we, the researchers performed cooperative learning in the fifth grade of elementary school and did the exams of mathematical beliefs and attitudes, interviews, supplementary Questions. And students showed meaningful changes in 'the need of cooperative learning', 'critical thinking', 'the acceptance of thoughts of others'. Meanwhile, there were possibilities what all the members of one group can't recognize their errors in STAD, so we proposed 'Tongsinsa'. And we presented concrete methods how to reconstruct groups and somethings to consider when students are not satisfied with the group activities.

• The Journal of the Acoustical Society of Korea
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• v.39 no.4
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• pp.263-269
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• 2020

In this study, a rotating machine that can reproduce normal condition and 8 fault conditions were produced, and vibration data was acquired. Feature is calculated from the acquired data, and accuracy is analyzed through fault diagnosis using artificial neural networks and genetic algorithms. In order to achieve optimal timing and higher accuracy, features by three domains were applied to the fault diagnosis. The learning number was selected as a setting variable. As a result of the rotating machine fault diagnosis, high precision was found in the frequency domain than in others, and precise fault diagnoses were accomplished through all of 10 operations, at the learning number of 5000 and 8000. Given the efficiency of time, it was estimated to be the most efficient when the number of learning was 5000.

• Journal of the Korean earth science society
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• v.27 no.3
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• pp.269-278
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• 2006

In this study, we used Virtual Reality (VR) materials on an introductory earth science course consisted of thirty six pre-service science teacher program students. Before and after class an instrument of Constructivist Learning Environment Survey (CLES) was administered. The main focus of the CLES was to evaluate how the classroom was prepared for student centered learning environment. The pre and post tests of student perceptions regarding their learning environment were compared in six domains: personal relevance, critical voice, shared control, student negotiation, scientific uncertainty, and attitude. Questionnaire regarding the general perception of the VR materials was administered as well. How future science teachers valued the use of VR materials in their classrooms was found from this study. Based on these results, we intend to contribute for a more complete understanding of the potential of VR materials in achieving better learner-centered classroom environment.