• Journal of Korean Elementary Science Education
• /
• v.28 no.4
• /
• pp.467-475
• /
• 2009

This study is to enquire about ideals on combustion and to propose of teaching program using the history a science in '5. Combustion and Extinguishing' unit of elementary school science textbook in 6th grade. For this purpose, investigation questionnaires based on preceding research and science textbook are developed. The reliability of the questionnaires is .784, and the questionnaires are applied to 247 students in T elementary school in Busan. Through the results of the investigation, scientific conceptions existed in some parts. But some misconceptions still existed especially (question 1), substance's changes (question 7), formation process of product (question 13), combustibles among requirements of combustion. The patterns of the misconception are similar to historical misconceptions about combustion. Besides, the discoveries and inventions of combustion have some points about correcting misconceptions. Thus the five step teaching programs on combustion which were applied to history of the science are suggested. The confidence of the developed programs was verified as being 'excellent' by specialists. This program will be applied to think deeply about combustion in elementary school lesson and useful to introduce the history of science.

• The Journal of Korean Association of Computer Education
• /
• v.21 no.6
• /
• pp.83-92
• /
• 2018

The subjective question is appropriate for evaluation of deep thinking, but it is not easy to score. Since, regardless of same scoring criterion, the graders are able to produce different scores, we need the objective automatic evaluation system. However, the system has the problem of Korean analysis and comparison. This paper suggests the Korean syntactic analysis and subjective grading system using the syntactic-semantic tree comparator. This system is the hybrid grading system of word based and syntactic-semantic tree based grading. This system grades the answers on the subjective question using the syntactic-semantic comparator. This proposed system has the good result. This system will be utilized in Korean syntactic-semantic analysis, subjective question grading, and document classification.

• International journal of advanced smart convergence
• /
• v.13 no.2
• /
• pp.205-213
• /
• 2024

This study uses a large language model (LLM) to identify Aristotle's rhetorical principles (ethos, pathos, and logos) in COVID-19 information on Naver Knowledge-iN, South Korea's leading question-and-answer community. The research analyzed the differences of these rhetorical elements in the most upvoted answers with random answers. A total of 193 answer pairs were randomly selected, with 135 pairs for training and 58 for testing. These answers were then coded in line with the rhetorical principles to refine GPT 3.5-based models. The models achieved F1 scores of .88 (ethos), .81 (pathos), and .69 (logos). Subsequent analysis of 128 new answer pairs revealed that logos, particularly factual information and logical reasoning, was more frequently used in the most upvoted answers than the random answers, whereas there were no differences in ethos and pathos between the answer groups. The results suggest that health information consumers value information including logos while ethos and pathos were not associated with consumers' preference for health information. By utilizing an LLM for the analysis of persuasive content, which has been typically conducted manually with much labor and time, this study not only demonstrates the feasibility of using an LLM for latent content but also contributes to expanding the horizon in the field of AI text extraction.

• Journal of Korea Multimedia Society
• /
• v.25 no.11
• /
• pp.1643-1652
• /
• 2022

Most of the existing machine reading research has used Recurrent Neural Network (RNN) and Convolutional Neural Network (CNN) algorithms as networks. Among them, RNN was slow in training, and Question Answering Network (QANet) was announced to improve training speed. QANet is a model composed of CNN and self-attention. CNN extracts semantic and syntactic information well from the local corpus, but there is a limit to extracting the corresponding information from the global corpus. Graph Convolutional Networks (GCN) extracts semantic and syntactic information relatively well from the global corpus. In this paper, to take advantage of this strength of GCN, we propose I-QANet, which changed the CNN of QANet to GCN. The proposed model performed 1.2 times faster than the baseline in the Stanford Question Answering Dataset (SQuAD) dataset and showed 0.2% higher performance in Exact Match (EM) and 0.7% higher in F1. Furthermore, in the Korean Question Answering Dataset (KorQuAD) dataset consisting only of Korean, the learning time was 1.1 times faster than the baseline, and the EM and F1 performance were also 0.9% and 0.7% higher, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.10
• /
• pp.2718-2731
• /
• 2023

This paper presents a method of using syntax and shallow semantic analysis for Vietnamese question generation (QG). Specifically, our proposed technique concentrates on investigating both the syntactic and shallow semantic structure of each sentence. The main goal of our method is to generate questions from a single sentence. These generated questions are known as factoid questions which require short, fact-based answers. In general, syntax-based analysis is one of the most popular approaches within the QG field, but it requires linguistic expert knowledge as well as a deep understanding of syntax rules in the Vietnamese language. It is thus considered a high-cost and inefficient solution due to the requirement of significant human effort to achieve qualified syntax rules. To deal with this problem, we collected the syntax rules in Vietnamese from a Vietnamese language textbook. Moreover, we also used different natural language processing (NLP) techniques to analyze Vietnamese shallow syntax and semantics for the QG task. These techniques include: sentence segmentation, word segmentation, part of speech, chunking, dependency parsing, and named entity recognition. We used human evaluation to assess the credibility of our model, which means we manually generated questions from the corpus, and then compared them with the generated questions. The empirical evidence demonstrates that our proposed technique has significant performance, in which the generated questions are very similar to those which are created by humans.

• Proceedings of the IEEK Conference
• /
• 2003.11b
• /
• pp.133-136
• /
• 2003

Due to recent explosion of information available online, question- answering (Q&A) systems are becoming a compelling framework for finding relevant information in a variety of domains. Question-answering system is one of the best ways to introduce a novice customer to a new domain without making him/her to obtain prior knowledge of its overall structure improving search request with specific answer. However, the current web poses serious problem for finding specific answer for many overlapped meanings for the same questions or duplicate questions also retrieved answer for many overlapped meanings fer the same questions or duplicate questions also retrieved answer is slow due to enhanced network traffic, which leads to wastage of resource. In order to avoid wrong answer which occur due to above-mentioned problem we propose the system using ontology by RDF, RDFS and mobile agent based on JAVA. We also choose wireless internet based embedded device as our test bed for the system and apply the system in E-commerce information domain. The mobile agent provides agent routing with reduced network traffic, consequently helps us to minimize the elapsed time for answers and structured ontology based on our proposed algorithms sorts out the similarity between current and past question by comparing properties of classes.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
• /
• v.9 no.1
• /
• pp.11-16
• /
• 1998

Background and Objectives : Electrolarynx has been used as one of the methods of rehabilitation for the laryngectomees. Previous electrolarynx could not alter frequency and intensity simultaneously. This institute developed an electrolarynx named "Evada" using FSR(force sensing resistor) sensor, which can control the frequency(and/or intensity) simultaneously. This study was performed for the normal control and laryngectomees with three types of electrolarynx (Evada, Servox-inton, Nu-vois) to reveal functional characteristics of Evada Materials and Methods : five laryngectomees and five normal adults were made to express there sentences(discriptive sentence, "You stay here" ; question sentence, "You stay here？" ; exclamation sentence, "You!! stay here!"), using three types of electrolarynx. Frequency change and intensity change from first and last vowel was calculated in three sentences and analyzed statistically by paired T-test. Results : The frequency change in the question sentence and exclamation sentence was more prominent in Evada than in Servox-inton and Nu-vois. The intensity change in the question sentence and exclamation sentence was also more prominent in Evada than in Servox-inton and Nu-vois. Conclusions : Evada could control frequency and intensity simultaneously and control degree of frequency(and/or intensity) according to the pressing force into the button. Evada could adjust continuously frequency and intensity during conversation. So, Evada is better in producing intonation and contrastive stress than Nu-vois and Servox-inton.

• Journal of Fisheries and Marine Sciences Education
• /
• v.15 no.1
• /
• pp.101-114
• /
• 2003

This study focused on how to activate the fisheries high school and develop fisheries. This data was collected from 108 vocational high school teachers and 94 middle school teachers. The treatment of materials is classified by gender, level of academic career and teaching career. This research evaluated percentage to the frequency of reponses to each question and carried out ${\chi}^2$-test and t-test, for the benefit of reliability. This statistically significant level which was conducted by using SPSS10.0 in accounted for p<.05. The conclusions of this study were as follows: The middle school teachers and vocational high school teachers showed positive response when general contents were included in question items, the other hand showed negative response when definite and special contents were included in question items. The vocational high school teachers showed lower answer score in the fisheries consciousness then middle school teachers in spite of vocational educational function. Different degrees of fisheries consciousness of two groups were resulted from research areas.

• Korean Journal of Cognitive Science
• /
• v.2 no.2
• /
• pp.309-339
• /
• 1990

The most common way that people communicate is by speaking or writing natural languages.But if people use computers in the modern technology,they should learn artificial programming languages.If computers could understand what people mean when people speak or type natural languages,people would use the computers more easily and naturally.but there is a problem.The language which people use has vagueness.For example,the convential computer system cant's handle the subjective feeling like 'tall' or 'young'.So peole must specify the exact threshold like 'more'than 25 ages'.We have developed the knowledge-based natural language question answering system which can handle sentences having fuzzy concepts by using blackboard model.Our goal of this research is to develop a portable question answering system as interface for database systems or understanding systems.

• The Journal of Korean Academic Society of Nursing Education
• /
• v.21 no.2
• /
• pp.266-275
• /
• 2015

Purpose: The aim of this study was to evaluate the effect of student question-centered lessons for bi-directional faculty-student communication. Methods: This study performed one-group pretest-posttest design; participants were university students majoring in health science (nursing 58, physical therapy 45) in city C. Data was collected and the program was conducted from March 3 to June 14, 2014. Measurements employed were the ARCS model of motivational design, self-assertiveness, learning satisfaction, and interpersonal relationship. Data was analyzed through frequency statistics, descriptive statistics, and repeated measurement of one-way analysis of variance with the SPSS 19.0 program. Results: In this student question-centered lesson participants exhibited significant enhanced satisfaction in terms of learning motivation, learning satisfaction, self-assertiveness, behavioral assertiveness, general assertiveness, and sensibility regarding interpersonal relationships. Conclusion: The results suggest that student question-centered lessons are applicable to a variety of subjects. Also, for comparative purposes, a faculty-centered lesson will be undertaken.