• Korean Journal of Cognitive Science
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• v.29 no.4
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• pp.243-263
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• 2018

This research investigated whether inter-word spaces, the spaces between words, can affect the efficiency of Korean-speaking CSL(Chinese as a second language) learners in Chinese reading of Korean-speaking's ability to read Chinese. Through eye movement tracking experiments, CSL learners of different proficiency levels(beginning, intermediate, and advanced) and native Chinese readers were asked to read Chinese sentences with and without inter-word spaces. The tests analysed the participants' fixation counts and the time spent in reading each sentences and also between each words. In terms of the fixation counts and time spent between sentences, the results show that there were no significant difference in participants' fixation counts from reading sentences with and without inter-word spaces. The results also prove that reading sentences with inter-word spaces significantly shortened the reading time for both CSL learners and native Chinese readers. Even for the participants' fixation counts and time duration between each words, participants spent significantly less fixation counts and reading time while reading words with inter-word spaces. The results were more prominent and positive in tests conducted with CSL learners of lower proficiency. This research shows that inter-word spaces in Chinese texts can enhance the efficiency of chinese learners' reading ability.

• Journal of the korean academy of Pediatric Dentistry
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• v.30 no.3
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• pp.341-347
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• 2003

Smith-Magenis syndrome (SMS) is a clinically recognizable multiple congenital anomaly and mental retardation syndrome caused by an interstitial deletion of chromosome 17 p11.2. Physical features include short stature, characteristic facial appearance: flattened mid-face, down-turned mouth, prominent and often rosy cheeks; prominent jaw in older children and adults, chronic ear infections, hearing impairment, eye problems, including: strabismus (an eye which turns in or out) and myopia (nearsightedness), hoarse voice, short fingers and toes, heart defects or murmurs, problems related to the urinary system, scoliosis (curvature of the spine), an unusual gait (walking pattern), and decreased sensitivity to pain. Behavioral and developmental characteristics include speech delay and articulation problems, developmental delay, learning disability, mental retardation, hyperactivity, self-injury, including: head banging; hand biting; picking at skin, sores and nails; pulling off finger- and toenails; inserting foreign objects into ears, nose, or other body orifices, explosive outbursts, prolonged tantrums, destructive and aggressive behavior, excitability, arm hugging or hand squeezing when excited. This report is the case of a Korean 3-year-3-month old male with Smith-Magenis syndrome referred from local clinic for the treatment of dental caries. The patient was treated by physical restraint after prophylatic administration of antibiotic(Amoxacillin 50mg/kg).

• Journal of The Korean Association For Science Education
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• v.40 no.2
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• pp.97-111
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• 2020

In the 2015 revised curriculum, 'Integrated Science' was established to increase convergent thinking and designated as a common subject for all students to learn, regardless of career. In addition, the 2015 revised curriculum introduced 'competence' as a distinctive feature from the previous curriculum. In the 2015 revised curriculum, competencies are divided into core competencies of cross-curricular character and subject competencies based on academic knowledge and skills of the subject. The science curriculum contains five subject competencies: scientific thinking, scientific inquiry, scientific problem solving, scientific communication, scientific participation and life-long learning. However, the description of competencies in curriculum documents is insufficient, and experts' perceptions of competencies are not uniform. Therefore, this study examines the perceptions of science subjects in science high school teachers by deciding that comprehension of competencies should be preceded in order for competency-based education to be properly applied to school sites. First, we analyzed the relationship between achievement standards and subject competencies of integrated science through the operation of an expert working group with a high understanding of the integrated science achievement standards. Next, 31 high school science teachers examined the perception of the five subject competencies through a descriptive questionnaire. The semantic network analysis has been utilized to analyze the teachers' responses. The results of the analysis showed that the three curriculum competencies of scientific inquiry, scientific communication, scientific participation and life-long learning ability are similar to the definitions of teachers and curriculum documents, but in the case of scientific thinking and scientific problem solving, there are some gaps in perception and definition in curriculum documents. In addition, the results of the comprehensive analysis of teachers' perceptions on the five competencies show that the five curriculum competencies are more relevant than mutually exclusive or independent.

• The Mathematical Education
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• v.62 no.2
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• pp.211-236
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• 2023

The purpose of this study is to derive implications of preservice mathematics teacher education in Korea by analyzing the case of edTPA used in the preservice teacher training process in the United States. Recently, there has been a growing interest in promoting professional competencies considering not only the cognitive dimension related to knowledge development of preservice mathematics teachers but also the situational dimension considering reality in the classroom. The edTPA in the United States is a performance-based assessment based on lessons conducted by preservice teachers at school. This study analyzes the professional competencies required of preservice mathematics teachers by analyzing handbooks that described the case of edTPA in which preservice mathematics teachers in the United States participate. The edTPA includes planning, instruction, and assessment tasks, and continuous tasks are performed in connection with classes. Thus, the analysis is conducted on the points of linkage between the description of evaluation items and criteria in the planning, instruction, and assessment tasks, as well as the professional competencies required from that linkage. As a result of analyzing the edTPA handbooks, the professional competencies required of preservice mathematics teachers in the edTPA assessment were the competency to focus on and implement specific mathematics lessons, the competency to reflectively understand the implementation and assessment of specific mathematics lessons, and the competency to make a progressive determination of students' achievement related to their learning and their uses of language and representations. The results of this analysis can be used as constructs for competencies that can be assessed in the preservice in the organization of the preservice mathematics teacher curriculum and practice training semester system in Korea.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.2
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• pp.435-452
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• 2023

This study experimented with automatic classification of subject headings using BERT-based transfer learning model, and analyzed its performance. This study analyzed the classification performance according to the main class of KDC classification and the category type of subject headings. Six datasets were constructed from Korean national bibliographies based on the frequency of the assignments of subject headings, and titles were used as classification features. As a result, classification performance showed values of 0.6059 and 0.5626 on the micro F1 and macro F1 score, respectively, in the dataset (1,539,076 records) containing 3,506 subject headings. In addition, classification performance by the main class of KDC classification showed good performance in the class General works, Natural science, Technology and Language, and low performance in Religion and Arts. As for the performance by the category type of the subject headings, the categories of plant, legal name and product name showed high performance, whereas national treasure/treasure category showed low performance. In a large dataset, the ratio of subject headings that cannot be assigned increases, resulting in a decrease in final performance, and improvement is needed to increase classification performance for low-frequency subject headings.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.1-19
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• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.