• Title/Summary/Keyword: language of science

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Relationship between Maternal Conversational Function and Question Type and Early Language Development (어머니가 사용한 담화기능 및 질문유형과 영아의 언어발달과의 관계)

  • Lee Kwee-Ock
    • The Korean Journal of Community Living Science
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    • v.17 no.3
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    • pp.3-14
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    • 2006
  • The purpose of this study was to investigate the relationship between conversational function and question type in mothers' utterances and their infant's language development. The subjects were 20 infants from 1;07 to 1;11 years of age in Yanji, China. Each child's spontaneous natural speech during interaction with his/her mother was videotaped for about 30 minutes. The children and their mother's spontaneous utterances were transcribed and coded for the number of type and token of word, grammatical morpheme conversational function and type of question in mother's language input to her child. The result showed that mothers used questions as the most frequent conversational function with their infants. The number of questions in conversational function in mothers' utterances positively correlated with the type of word, type of morpheme and grammatical morpheme in infants' utterance. However, there was no correlation between mothers' language input and infant early language development.

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A BERT-Based Automatic Scoring Model of Korean Language Learners' Essay

  • Lee, Jung Hee;Park, Ji Su;Shon, Jin Gon
    • Journal of Information Processing Systems
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    • v.18 no.2
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    • pp.282-291
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    • 2022
  • This research applies a pre-trained bidirectional encoder representations from transformers (BERT) handwriting recognition model to predict foreign Korean-language learners' writing scores. A corpus of 586 answers to midterm and final exams written by foreign learners at the Intermediate 1 level was acquired and used for pre-training, resulting in consistent performance, even with small datasets. The test data were pre-processed and fine-tuned, and the results were calculated in the form of a score prediction. The difference between the prediction and actual score was then calculated. An accuracy of 95.8% was demonstrated, indicating that the prediction results were strong overall; hence, the tool is suitable for the automatic scoring of Korean written test answers, including grammatical errors, written by foreigners. These results are particularly meaningful in that the data included written language text produced by foreign learners, not native speakers.

Adversarial Learning for Natural Language Understanding (자연어 이해를 위한 적대 학습 방법)

  • Lee, Dong-Yub;Whang, Tae-Sun;Lee, Chan-Hee;Lim, Heui-Seok
    • Annual Conference on Human and Language Technology
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    • 2018.10a
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    • pp.155-159
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    • 2018
  • 최근 화두가 되고있는 지능형 개인 비서 시스템에서 자연어 이해(NLU) 시스템은 중요한 구성요소이다. 자연어 이해 시스템은 사용자의 발화로부터 대화의 도메인(domain), 의도(intent), 의미적 슬롯(semantic slot)을 분류하는 역할을 한다. 하지만 자연어 이해 시스템을 학습하기 위해서는 많은 양의 라벨링 된 데이터를 필요로 하며 새로운 도메인으로 시스템을 확장할 때, 새롭게 데이터 라벨링을 진행해야 하는 한계점이 존재한다. 이를 해결하기 위해 본 연구는 적대 학습 방법을 이용하여 풍부한 양으로 구성된 기존(source) 도메인의 데이터부터 적은 양으로 라벨링 된 데이터로 구성된 대상(target) 도메인을 위한 슬롯 채우기(slot filling) 모델 학습 방법을 제안한다. 실험 결과 적대 학습을 적용할 경우, 적대 학습을 적용하지 않은 경우 보다 높은 f-1 score를 나타냄을 확인하였다.

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KULLM: Learning to Construct Korean Instruction-following Large Language Models (구름(KULLM): 한국어 지시어에 특화된 거대 언어 모델)

  • Seungjun Lee;Taemin Lee;Jeongwoo Lee;Yoonna Jang;Heuiseok Lim
    • Annual Conference on Human and Language Technology
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    • 2023.10a
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    • pp.196-202
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    • 2023
  • Large Language Models (LLM)의 출현은 자연어 처리 분야의 연구 패러다임을 전환시켰다. LLM의 핵심적인 성능향상은 지시어 튜닝(instruction-tuning) 기법의 결과로 알려져 있다. 그러나, 현재 대부분의 연구가 영어 중심으로 진행되고 있어, 다양한 언어에 대한 접근이 필요하다. 본 연구는 한국어 지시어(instruction-following) 모델의 개발 및 최적화 방법을 제시한다. 본 연구에서는 한국어 지시어 데이터셋을 활용하여 LLM 모델을 튜닝하며, 다양한 데이터셋 조합의 효과에 대한 성능 분석을 수행한다. 최종 결과로 개발된 한국어 지시어 모델을 오픈소스로 제공하여 한국어 LLM 연구의 발전에 기여하고자 한다.

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Investigation of Elementary Students' Scientific Communication Competence Considering Grammatical Features of Language in Science Learning (과학 학습 언어의 문법적 특성을 고려한 초등학생의 과학적 의사소통 능력 고찰)

  • Maeng, Seungho;Lee, Kwanhee
    • Journal of Korean Elementary Science Education
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    • v.41 no.1
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    • pp.30-43
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    • 2022
  • In this study, elementary students' science communication competence was investigated based on the grammatical features expressed in their language-use in classroom discourse and science writings. The classes were designed to integrate the evidence-based reasoning framework and traditional learning cycle and were conducted on fifth graders in an elementary school. Eight elementary students' discourse data and writings were analyzed using lexico-grammatical resource analysis, which examined the discourse text's content and logical relations. The results revealed that the student language used in analyzing data, interpreting evidence, or constructing explanations did not precisely conform to the grammatical features in science language use. However, they provided examples of grammatical metaphors by nominalizing observed events in the classroom discourses and those of causal relations in their writings. Thus, elementary students can use science language grammatically from science language-use experiences through listening to a teacher's instructional discourses or recognizing the grammatical structures of science texts in workbooks. The opportunities in which elementary students experience the language-use model in science learning need to be offered to understand the appropriate language use in the epistemic context of evidence-based reasoning and learn literacy skills in science.

Comparison of the Features of Science Language between Texts of Earth Science Articles and Earth Science Textbooks (지구과학 논문과 지구과학 교과서 텍스트의 과학 언어적 특성 비교)

  • Lee, Jeong-A;Kim, Chan-Jong;Maeng, Seung-Ho
    • Journal of The Korean Association For Science Education
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    • v.27 no.5
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    • pp.367-378
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    • 2007
  • The purpose of this study is to investigate the features of science language in Earth science textbooks and Earth science research articles. We examined two Earth science textbooks and two Earth science articles using the taxonomy of scientific words, the text structure analysis of explanations, the analysis of conjunctive relations and reasoning, and the function of conjunction. The results showed that school science language revealed in Earth science textbooks had high proportion of naming words and the text structures in which definition/exemplification structure and description structure were dominant. Also, internal relations that showed additional arrangement rather than logical inference, were predominant in Earth science textbooks. However, scientists' science language revealed in the Earth science articles had more proportion of process words and concept words than the Earth science textbooks and the schematic structure of explanation texts, such as orientation - implication sequence - conclusion. In addition, the text structures in each sentences of implication -sequence showed cause/effect or problem-solving after description structures. Also each sentences expressed causal or abductive reasoning through the internal relations using verbs or adverbial inflection. It is necessary that we bridge the gap between the two languages for students' authentic use of science language. For the bridging, we propose "interlanguage", which mediates between school science language and scientists' language.