• The Korean Journal of Applied Statistics
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• v.28 no.1
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• pp.75-82
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• 2015

We discuss confidence intervals for sensitive binomial attributes obtained by a direct question method and indirect question method. The Randomized Response Technique(RRT) by Warner (1965) is an indirect question method that uses a randomization device to reduce the response burden of respondents. We used the mean coverage probability (MCP), root mean squared error (RMSE), and mean expected width (MEW) to compare the confidence intervals by the two methods. The numerical comparisons indicated found that the MEW of RRT is too large and the RRT is so conservative that the MCP exceeds a nominal level(${\alpha}$); therefore, it is necessary to complement these problem in order to increase the utility of the indirect question method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3266-3285
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• 2023

With the popularity of online learning, intelligent tutoring systems are starting to become mainstream for assisting online question practice. Surrounded by abundant learning resources, some students struggle to select the proper questions. Personalized question recommendation is crucial for supporting students in choosing the proper questions to improve their learning performance. However, traditional question recommendation methods (i.e., collaborative filtering (CF) and cognitive diagnosis model (CDM)) cannot meet students' needs well. The CDM-based question recommendation ignores students' requirements and similarities, resulting in inaccuracies in the recommendation. Even CF examines student similarities, it disregards their knowledge proficiency and struggles when generating questions of appropriate difficulty. To solve these issues, we first design an enhanced cognitive diagnosis process that integrates students' affection into traditional CDM by employing the non-compensatory bidimensional item response model (NCB-IRM) to enhance the representation of individual personality. Subsequently, we propose an affection-enhanced personalized question recommendation (AE-PQR) method for online learning. It introduces NCB-IRM to CF, considering both individual and common characteristics of students' responses to maintain rationality and accuracy for personalized question recommendation. Experimental results show that our proposed method improves the accuracy of diagnosed student cognition and the appropriateness of recommended questions.

• Journal of Sasang Constitutional Medicine
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• v.18 no.1
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• pp.91-106
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• 2006

1. Objectives The purpose of this study is to find out the characteristics about the Sasang constitution of elementary school students based on the questions that have significant differences. 2. Methods 146 children who have visited Kang-Nam Kyung-Hee Oriental Hospital Sasang constitution center from Mar. 2003 to May. 2005, were investigated through the questionnaires. These have the categories of personality and emotional characteristics, personal relationship, playing and the way to handle things such as jobs or missions, behavioral characteristics, and etc., were analyzed statistically. 3. Results and Conclusions (1) In the category of the 'Personality and Emotional characteristics', significantly more Soeumin showed positive answers to the question, 'being easily nervous and get irritated' than the other groups, and significantly more Taeumin to the question, 'considerate and thoughtful' than Soyangin. (2) In the category of the 'Personal relationship', there were significantly more Soyangin who showed positive answer to the question 'making a friend easily' than the other groups. (3) In the category of the 'playing and the way to handle things', significantly more Soeumin showed positive answer to the question, 'love to do the exercise' than Soyangin, and significantly more Soeumin showed positive answer to the question, 'not careful and meticulous' than Soyangin, and significantly more Soeumin showed positive answer to the question, 'like to read books' than Taeumin. (4) In the category of the 'Behavioral characteristics', significantly more Soyangin showed positive answer to the question, 'unable to concentrate just one thing even for just a minute and keep on moving.' than the other groups, and significantly more Soyangin showed positive answer to the question, 'act or response quick.' than Taeumin, and significantly more Soyangin showed positive answer to the question, 'behave and go around restlessly and flighty' than Soeumin, and significantly more Taeumin showed the positive answer to the question, 'hate to move by oneself' than Soyangin.

• Journal of KIISE:Software and Applications
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• v.30 no.5_6
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• pp.466-475
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• 2003

To build an efficient Question-Answering (QA) system, a question type classifier is needed. It can classify user's queries into predefined categories regardless of the surface form of a question. In this paper, we propose a question type classifier using a Support Vector Machine (SVM). The question type classifier first extracts features like lexical forms, part of speech and semantic markers from a user's question. The system uses $X^2$ statistic to select important features. Selected features are represented as a vector. Finally, a SVM categorizes questions into predefined categories according to the extracted features. In the experiment, the proposed system accomplished 86.4% accuracy The system precisely classifies question type without using any rules like lexico-syntactic patterns. Therefore, the system is robust and easily portable to other domains.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.1
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• pp.27-36
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• 2019

In this paper, we propose a method to find the most similar answer to the user's response from the question-answer database in order to avoid generating a redundant question in retrieval-based automatic question generation system. As a question of the most similar answer to user's response may already be known to the user, the question should be removed from a set of question candidates. A similarity detector calculates a similarity between two answers by utilizing the same words, paraphrases, and sentential meanings. Paraphrases can be acquired by building a phrase table used in a statistical machine translation. A sentential meaning's similarity of two answers is calculated by an attention-based convolutional neural network. We evaluate the accuracy of the similarity detector on an evaluation set with 100 answers, and can get the 71% Mean Reciprocal Rank (MRR) score.

• Journal of the Korean earth science society
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• v.27 no.1
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• pp.20-31
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• 2006

This study analysed student teachers' notable questions about the earth science contents in the elementary science textbooks. The contents of notable questions were defined as ‘notable question contents 1' and 'notable question contents 2'. Both the question contorts are contents about which the number of questions is above three times and from two times to three times as much as the mean number of questions per page of each unit respectively. The results are as follows. First, question contents 1 are found as 'clouds observation', 'geological strata formation' and so on. Question contents 2, 'rainfall measurement', 'moon's movement during one night' and so on are found. Second, the number of interrelationships of main terms in questions increased in each question of question contents 1, but 4 term-patterns are found more in question contents 2 than question contents 1. Third, high interrelationship patterns of terms in question contents 1 are 'coal and petroleum-generation', 'metamorphosis-heat and pressure', 'metamorphosis-heat and pressure-metamorphic rocks', 'planet-sun-comet-revolution' and in question contents 2. 'constellation plate-use', 'dryness and wetness hygrometer-principle', 'seismograph-principle-earthquake', 'earth rotation axis-tilting-occurrence', 'dryness and wetness hygrometer-principle-humidity' and so on. The sources of questions analysed in this study are estimated as the content construction system of textbooks, or students' general questions about the earth science contents. If this is the former, the problems in texts and illustrations in textbooks should be articulated and resolved. And if the latter, the elementary science curriculum has to be reconsidered in view of scientific literacy in earth science.

• Journal of Science Education
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• v.39 no.1
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• pp.58-79
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• 2015

This study is to analyze the 2289 students questionnaires from 3rd to 9th grade students in order to analyze the students' perceptions change aspect by their grade about the frequency and type of students' question during various science class context. After the class contexts proposed in the questionnaire subcategorize into 19 subitems about 4 areas of class content, class pattern, class material and class process, this study examined the frequency and type of students' question during a science class by each item. The results of this study were as follows. First, the type of students' question was that the most frequent was understanding question and the second was memory question and these both types were half frequency. There was no special tendency related the change of students' question type by school year. Second, the frequency of 4th grade students' question was the highest among other school year students and the frequency of students' question was lowered by the higher school year. The change of students' question by school year was the biggest between 3rd and 4th grade. The class strategies for improving the class effect reflect that the various and active students' question by class context and school year stimulates students' thinking and also builds up the active class environment.

• ETRI Journal
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• v.42 no.6
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• pp.899-911
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• 2020

The data in tables are accurate and rich in information, which facilitates the performance of information extraction and question answering (QA) tasks. TableQA, which is based on tables, solves problems by understanding the table structure and searching for answers to questions. In this paper, we introduce both novice and intermediate Korean TableQA tasks that involve deducing the answer to a question from structured tabular data and using it to build a question answering pair. To solve Korean TableQA tasks, we use S3-NET, which has shown a good performance in machine reading comprehension (MRC), and propose a method of converting structured tabular data into a record format suitable for MRC. Our experimental results show that the proposed method outperforms a baseline in both the novice task (exact match (EM) 96.48% and F1 97.06%) and intermediate task (EM 99.30% and F1 99.55%).

• Education of Primary School Mathematics
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• v.19 no.3
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• pp.249-260
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• 2016

The purpose of this study was to analyze the effectiveness of an instruction to enhance students' questioning, that is 'mathematics instruction with students' question using question card' In order to achieve the goal of this study, research questions were established as follows. Is there any significant improvement on perception of mathematics classroom culture through 'mathematics instruction with students question using question card' Is there any significant improvement on mathematics learning attitude through 'mathematics instruction with students question using question card' The findings of this experimental results were obtained as follows. There was significant statistical difference in perception of mathematics classroom culture between the experimental group and control group. It also shown that instruction with students' questioning improved participants' mathematics learning attitude. In conclusion, the instruction with students' questioning using question card can be effective teaching strategy of improving students' perception of mathematics classroom culture and mathematics learning attitude.

• Korean Journal of Logic
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• v.19 no.2
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• pp.185-232
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• 2016

In order to explain why begging the question is a fallacy, some of the challenges must be met. First we need to understand what begging the question is in subtle ways. In addition, it is necessary to reflect on the nature and the purpose of arguments in order to explain why begging the question is a fallacy. In this paper, I first have a general proposal about the main purpose of arguments. Then I place my own multi-layered theory of begging the question proposed in a previous study in the context of the proposals in this paper for the main purpose of arguments. Moreover, I develop a more comprehensive theory of why begging the question is a fallacy. Finally, I examine and criticize the main previous theories of begging the question, such as Frank Jackson's theory, Douglas Walton's theory, David Sanford's theory, John Biro's theory.