• Title/Summary/Keyword: type of question

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An Analysis of Types and Sources of Background Knowledges of Elementary Preservice Teachers' Questions about Astronomy Contents in Elementary Science Text Books (초등 과학교과서 천문 내용에 대한 예비교사들의 질문의 배경지식 유형과 출처 분석)

  • Lee, Myeong-Je
    • Journal of Korean Elementary Science Education
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    • v.35 no.2
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    • pp.194-204
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    • 2016
  • The purpose of this study is to find out the relationship between types and sources of background knowledges of elementary preteachers' questions about astronomy contents in the elementary science text books. Data were extracted from the preteachers' classes established in a university of education. The results are as follows. First, right background knowledges of questions were found in about 58% questions, wrong background knowledges 15%, and no background knowledges 26%. Second, it was found that 'school' as a source of background knowledges was found in 29% questions, 'friend' 21%, 'internet' 14%, 'book reading' 12%, 'others' 9%, 'TV' 7%, 'institute' 4%. In case of the type that right background knowledges have casual relation or correlation with question contents, 'book reading' and 'TV' sources rate increased, but 'internet' and 'others' decreased when compared to total questions. In the type which background knowledges are right and did not have casual relation or correlation with question contents, 'internet' source rate increased and 'friend' decreased. In case of the type that wrong background knowledges do not have casual relation or correlation with question contents, 'friend' and 'TV' sources rate increased, but 'school' and 'book reading' decreased. The type which background knowledges are right and did not have casual relation or correlation with question contents, 'internet' source rate increased and 'friend' decreased. In case of the type of no background knowledges, 'TV' and 'institute' source rate increased, but 'internet' and 'book reading' decreased. Third, the questions in 'Earth and Moon' unit have little background knowledges. The questions in 'solar system and stars' have background knowledges with no relation to the questions. Especially, in the unit 'changes of seasons', right background knowledges were found in more than half questions, but the contents of questions and background knowledges were not connected scientifically.

TYPE $I_{\infty}$ OF A VON NEUMANN ALGEBRA ALG$\mathcal{L}$

  • Kim, Jong-Geon
    • East Asian mathematical journal
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    • v.15 no.2
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    • pp.313-324
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    • 1999
  • What we will be concerned with is, first, the question of the condition about $\mathcal{L}$ that gives Alg$\mathcal{L}$ a von Neumann algebra, that is, the question of the condition about $\mathcal{L}$ that will give Alg$\mathcal{L}$ a self-adjoint algebra. Secondly, if Alg$\mathcal{L}$ is a von Neumann algebra, we want to find out what type it is.

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Analysis of Questions in the 'Matter' Units of Elementary Science Textbooks under the 7th Curriculum (제7차 초등학교 과학 교과서 물질 영역에 제시된 발문 분석)

  • Park, Ju-Hyeon;Kwon, Hyeok-Soon
    • Journal of Korean Elementary Science Education
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    • v.26 no.5
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    • pp.551-557
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    • 2007
  • The purpose of this study was to examine the questions in the 'Matter' units of elementary science textbooks under the 7th curriculum. For the analysis, a total of 338 questions were extracted from 15 units. Six criteria (recalling, recognizing, predictive, applied, divergent, and evaluative question) were reconstructed for textbook question analysis based on Blosser(1973)'s question category system for science. The results were as follows. First, there were more closed (recalling, recognizing, predictive, or applied) questions (72.2%) than open (divergent or evaluative) questions (27.8%) in elementary science textbooks. Second, cognitive-memory (recalling or recognizing) question type was the most frequently asked in all grade levels. Open (divergent or evaluative) questions increased according to grade level whereas convergent (predictive or applied) questions decreased. Third, question types were applied based on the characteristics of each unit rather than on children's developmental characteristics. Educational implications were discussed based on the results.

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Semantic-based Query Generation For Information Retrieval

  • Shin Seung-Eun;Seo Young-Hoon
    • International Journal of Contents
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    • v.1 no.2
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    • pp.39-43
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    • 2005
  • In this paper, we describe a generation mechanism of semantic-based queries for high accuracy information retrieval and question answering. It is difficult to offer the correct retrieval result because general information retrieval systems do not analyze the semantic of user's natural language question. We analyze user's question semantically and extract semantic features, and we .generate semantic-based queries using them. These queries are generated using the se-mantic-based question analysis grammar and the query generation rule. They are represented as semantic features and grammatical morphemes that consider semantic and syntactic structure of user's questions. We evaluated our mechanism using 100 questions whose answer type is a person in the TREC-9 corpus and Web. There was a 0.28 improvement in the precision at 10 documents when semantic-based queries were used for information retrieval.

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Question-Answering System using the Superlative Words (최상급 단서 어휘를 이용한 질의-응답시스템)

  • Park, Hee-Geun;Oh, Su-Hyun;Ahn, Young-Min;Seo, Young-Hoon
    • Proceedings of the Korea Contents Association Conference
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    • 2006.05a
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    • pp.140-143
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    • 2006
  • In this paper, we describe a question-answering system which extracts answers for the superlative questions which include the superlative words such as "the most", "the best", "the first", "the largest", "the least", and so on. The superlative questions are composed of four main components and others. Four main components are the superlative word, answer type, regional information, and a verb modified by the superlative word. We classify the superlative words into two types as to whether the verb has to be needed to be a question or not. The superlative word, answer type and regional information are essential elements to extract answer for all superlative questions. But the verb may be an essential element by the type of superlative word. Our system analyzes input question, and finds four main components of the superlative question. Also, our system searches relative documents and candidate sentences using them, and extracts answers from candidate sentences. Empirical result shows that our system has high precision and high recall for the superlative questions.

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The question at issue of connector wire in High Speed Railway Catenary System of France (프랑스 고속철도 전차선로 시스템에서 균압선의 문제점)

  • 안영훈
    • Proceedings of the KSR Conference
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    • 2000.11a
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    • pp.636-651
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    • 2000
  • In these days, SNCF replace the connector wire (M-T type) with a dropper has a equivalent role and function of the one in general lines of TGV, and change the connector wire (T-T-M-M-T-T, T-T-M-M-T type, etc) into a New one has more flexible cable in parallel lines (air section air joint, etc) of TGV. The Connector wire has many problems according to a flow of excessive circulation current (or traction current) and a sudden rise of temperature on catenary when electric locomotive is running in high speed. To solve the question at issue of the connector wire in high speed railway catenary system of Fiance, SNCF return their operating experience in TGV lines to design and execution of catenary system Therefore, we have to deal with the question in design and execution of catenary system for kyoungbu HSR line because we will spend a lot of time and more money for maintenance than for construction of that.

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A Korean Community-based Question Answering System Using Multiple Machine Learning Methods (다중 기계학습 방법을 이용한 한국어 커뮤니티 기반 질의-응답 시스템)

  • Kwon, Sunjae;Kim, Juae;Kang, Sangwoo;Seo, Jungyun
    • Journal of KIISE
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    • v.43 no.10
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    • pp.1085-1093
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    • 2016
  • Community-based Question Answering system is a system which provides answers for each question from the documents uploaded on web communities. In order to enhance the capacity of question analysis, former methods have developed specific rules suitable for a target region or have applied machine learning to partial processes. However, these methods incur an excessive cost for expanding fields or lead to cases in which system is overfitted for a specific field. This paper proposes a multiple machine learning method which automates the overall process by adapting appropriate machine learning in each procedure for efficient processing of community-based Question Answering system. This system can be divided into question analysis part and answer selection part. The question analysis part consists of the question focus extractor, which analyzes the focused phrases in questions and uses conditional random fields, and the question type classifier, which classifies topics of questions and uses support vector machine. In the answer selection part, the we trains weights that are used by the similarity estimation models through an artificial neural network. Also these are a number of cases in which the results of morphological analysis are not reliable for the data uploaded on web communities. Therefore, we suggest a method that minimizes the impact of morphological analysis by using character features in the stage of question analysis. The proposed system outperforms the former system by showing a Mean Average Precision criteria of 0.765 and R-Precision criteria of 0.872.

The Analysis on Question's Patterns in Elementary School Science Teacher's Guidebooks of 5, 6th Grade under the 2009 Revised Curriculum (2009 개정 교육과정에 따른 5, 6학년 초등과학과 교사용 지도서에 제시된 발문 유형 분석)

  • Kim, Gyeong-ah;Lee, Hyeong-cheol
    • Journal of Korean Elementary Science Education
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    • v.35 no.1
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    • pp.1-12
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    • 2016
  • The purpose of this study was to analyze question's patterns in elementary school science teacher's guide books of 5, 6th grade under the 2009 revised curriculum. A modified analysis framework based on Blosser's classified system was used to analyze 1,982 questions extracted from elementary science teacher's guide books by grade, by domain, and by teaching and learning stage. The findings of this study were as follows. First, of the 1,982 questions, the most prominent type of question was the propositional question and the following was the reproductive question. And, in comparing the question's patterns between 5, 6th grade, it was found that 6th grade had higher rate of close typed question, while 5th grade had higher rate of open typed question in its curriculum. Secondly, a comparative study about two domains, material and energy science domain and earth and life science domain, showed that the number of questions of each domain was not much different. However, it was found that propositional questions and applicable questions showed a higher rate in material and energy science domain, and anticipated questions and open typed questions including divergent and evaluative question showed higher rate in earth and life science domain. Moreover, although the total number of questions from integration and my fun research domain's contents was small, the rate of open typed questions was higher than any other domains. Finally, as a result of comparing and analyzing question's pattern in teaching and learning stages, the rate of reproductive question and anticipated questions was high at the stage of introduction. At the stage of development, the rate of propositional and reproductive questions was high. At the stage of conclusion, the rate of synthetic and applicable questions was high.

A Hybrid Method for classifying User's Asking Points (하이브리드 방법의 사용자 질의 의도 분류)

  • Harksoo Kim;An, Young Hun;Jungyun Seo
    • Journal of KIISE:Software and Applications
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    • v.30 no.1_2
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    • pp.51-57
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    • 2003
  • For QA systems to return correct answer phrases, it is very important that they correctly and stably analyze users' intention. To satisfy this need, we propose a question type classifier (i.e. asking point identifier) for practical QA systems. The classifier uses a hybrid method that combines a statistical method with a rule-based method according to some heuristic rules. Owing to the hybrid method, the classifier can reduce the time to manually construct rules, yield high precision rate and guarantee robustness. In the experiment, we accomplished 80% accuracy of the question type classification.

A Statstical Analysis of the Question Categories concerning 'Total Physiognomy' ('전체적 인상'에 관한 문진항목의 통계적 분석)

  • Kim, Hong-Gie;Kim, Jong-Yeol
    • Journal of Sasang Constitutional Medicine
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    • v.15 no.2
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    • pp.64-74
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    • 2003
  • Objectives : To evaluate the properness and effectiveness of the question categories concerning 'total physiognomy', used in Iksan Wonkwang Oriental Medicine. Methods: We statistically analyzed data from those 1335 patients focussing on 'relative discrimination ability' to sasang constructions and 'response ratio'. Patients included in this research are only those who had been well treated in Iksan Wonkwang Oriental Medicine during the Period of three years from 2000 to 2002. The data are obtained through the electronic chart developed by Kim Jong-Yeol, and analyzed using the statistical Package SPSS. Results: The first category for discriminating Taeum type, 'heavy and looking steady', has more discriminating power and effectiveness among women than men, and especially in wemen with an age of 21 or more. The second category for discriminating Soeum type, 'delicate and modest', is more discriminating and effective among men than women, and mostly among men with ages 21-40. The third category for Soyang type, 'fast and brave', is almost equally discriminating and effective to both women and men, especially among women with ages 40 or less and among men with ages 21 or more. Finally, the forth category for discriminating Taeyang type, 'progressive', is neither discriminating nor effective among most the women than men in all age groups. Conclusions: The definition of 'relative discriminating power of constitution' and 'response ratio' are well evaluating the properness and effectiveness of the question categories regarding 'total physiognomy'. The first category is most discriminating and effective among women with ages 20 or less, and the second among 21-40 year old men, the third among women with ages 40 or less and among men with ages 21 or over. The forth category is neither discriminating nor effective.

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