• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.10
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• pp.2893-2899
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• 2009

The study classified speech styles of shopping hosts and tried to examine how the classified speech styles have an effect on the evaluation of shopping hosts and the purchase intentions. In the evaluation of speech styles of shopping hosts, except customer-oriented confutative style, credibility, descriptive relevance, other speech styles are analyzed to have an impact on the styles. When we investigate the influential relations between speech styles proved by a theory and the evaluation of shopping hosts, the demonstrative style comes first, the expressive style is next and the descriptive follows in terms of influential power. In terms of the purchasing intention, speech styles of shopping hosts have an effect on the demonstrative and expressive types rather than the elucidative and descriptive ones. Namely, the analysis shows that the speech style which is logically persuasive and expresses the contents in detail is preferred to the descriptive and leading speech style.

• Journal of The Korean Association of Information Education
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• v.20 no.3
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• pp.255-262
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• 2016

In this paper, we proposes a method to effectively evaluate learner competencies of computational thinking. Developed descriptive performance assessment tool is the use of assessment items presented in a creative computing MIT. This tool is selected and modified items through expert delphi technique. The performance assessment tool is composed of four areas that are an experimenting and iterating, testing and debugging, reusing and remixing and abstracting and modularizing. We apply to software classes for the pre-service teachers and conducted this descriptive performance assessment. Applying result of the assessment, the developed assessment tool shows the reliability $Cronbach-{\alpha}$ values higher than 0.6. In addition, the validity of the test results is higher in experts delphi test. Descriptive assessment tool suggested in this study are identified as a useful assessment tool to effectively measure student CT competencies.

• Journal of Science Education
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• v.38 no.1
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• pp.168-181
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• 2014

The purpose of this study was to monitor evaluation in science education at primary and secondary school in Korea. In order to do this, the survey was administered. The subject was 518 teachers; 292 elementary school teachers, 110 middle school science teachers and 116 general high school science teachers. It was found that the ratio of paper examination increased while that of performance evaluation decreased according to the grade of school. In the science paper examination, the ratio of selection type item was higher than that of supply type item, and the ratio of item belonging to knowledge area was higher than that of item belonging to the inquiry area regardless of the grade of school, teaching career, and teacher's gender. The teachers recognized the necessity of supply type item, but they suffered from the reliability of the result of that item. And it was hard for them to do performance evaluation because it took much time and effort. This study suggested that the high-quality in-service teacher training be provided and laboratory assistants who help the science experiment and grading test papers be employed in order to fulfil the performance evaluation and increase the ratio of supply type item and items belonging to the inquiry area.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1137-1144
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• 2022

In this study, an artificial intelligence(AI) was developed to help with facial expression practice in order to express emotions. The developed AI used multimodal inputs consisting of sentences and facial images for deep neural networks (DNNs). The DNNs calculated similarities between the emotions predicted by the sentences and the emotions predicted by facial images. The user practiced facial expressions based on the situation given by sentences, and the AI provided the user with numerical feedback based on the similarity between the emotion predicted by sentence and the emotion predicted by facial expression. ResNet34 structure was trained on FER2013 public data to predict emotions from facial images. To predict emotions in sentences, KoBERT model was trained in transfer learning manner using the conversational speech dataset for emotion classification opened to the public by AIHub. The DNN that predicts emotions from the facial images demonstrated 65% accuracy, which is comparable to human emotional classification ability. The DNN that predicts emotions from the sentences achieved 90% accuracy. The performance of the developed AI was evaluated through experiments with changing facial expressions in which an ordinary person was participated.

• Journal of Gifted/Talented Education
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• v.20 no.1
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• pp.61-77
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• 2010

The purpose of this study was to analyze the items that were used in entrance examination for science gifted education center for middle school students by using content analysis and classical item analysis. In content analysis, objective type items exhibited mathematics and physics were dominant. Science giftedness & creativity items were dominant. And essay type items consisted of physics items, have evaluated creative problem solving ability. Item difficulty and discrimination index, on the whole, were appropriate. Comparing with objective type, essay type has higher discrimination index. In correlation analysis between total score and score of each type of items, total score has the highest correlation with essay type items and science giftedness & creativity. It was recommended that mathematics, physics and chemistry items with focusing giftedness & creativity could give some implications for future selection methods of science gifted education center.

• Patent21
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• s.70
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• pp.31-33
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• 2006

• Journal of the Korean School Mathematics Society
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• v.17 no.3
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• pp.409-435
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• 2014

This study examines relations between the 5th graders' fraction operation skills and error types on constructed-response items. As results, first, the participants have lower fraction operation skills on 'multiplication of fraction' than 'addition and subtraction of fraction'. Second, the participants have different error types depend on their constructed-response items. Most of error types which group with high ability made was 'leap of solving process', both groups error type with medium ability as well as low ability is 'misunderstanding of questions'. Third, the operation skills on 'addition and subtraction of fraction' have an influence on their operation skills on 'multiplication of fraction', and error types of 'understanding of questions' and 'understanding of solving process' have the most effects on the influence.

• Journal of Educational Research in Mathematics
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• v.23 no.3
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• pp.389-406
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• 2013

The purpose of this study is to analyze eighth grade students' errors in the constructed-response items to improve teaching and learning of mathematics in schools. By analyzing 99 students' responses to nine constructed-response items, we found several types of students' errors in their responses to the assessment items involving with mathematical reasoning and representations, problems within realistic contexts, and mathematical connections. Not only a single error but also multiple errors (a combination of two or more types of errors) were discovered. In particular, high achieving students showed more simple errors than multiple errors while low achieving students had more multiple errors in various kinds.

• Journal of the Korea Society of Computer and Information
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• v.18 no.8
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• pp.17-25
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• 2013

TIn this paper, we propose a model automatically scoring a student's answer for a descriptive problem by using a voting method. Considering the model construction cost, the proposed model does not separately construct the automatic scoring model per problem type. In order to utilize features useful for automatically scoring the descriptive answers, the proposed model extracts feature values from the results, generated by comparing the student's answer with the answer sheet. For the purpose of improving the precision of the scoring result, the proposed model collects the scoring results classified by a few machine learning based classifiers, and unanimously selects the scoring result as the final result. Experimental results show that the single machine learning based classifier C4.5 takes 83.00% on precision while the proposed model improve the precision up to 90.57% by using three machine learning based classifiers C4.5, ME, and SVM.

• The Mathematical Education
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• v.47 no.4
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• pp.487-503
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• 2008

In this paper, descriptive assessment method for middle school mathematics was evaluated by developing a framework for designing and grading problems for descriptive assessment and analyzing the effectiveness of the problems. The new descriptive assessment problems were developed by reviewing the current 7th National Mathematics Curriculum of Korea and aligned mathematics textbooks to define a set of problem design principles and evaluation framework for the assessment strategy. The developed problems were first pilot tested and then revised based on the feedback from the test. The final version was field tested by 100 students in 7th grade middle school. After the field test, the problems were graded by two middle school math teachers and one math education researcher to determine the overall correlation between graders and also to analyze effectiveness of the evaluation framework of the test. This result of this study is expected to assist in the further development of descriptive problems and grading framework by providing a reference work for teachers to better understand the process and the limitations of executing the new assessment strategy.