• Education of Primary School Mathematics
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• v.19 no.1
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• pp.31-45
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• 2016

In this study, the case of error became the object of learning, and the investigator applied these cases to an actual class and established three study problems in order to achieve the purpose of this study. The results of analysis of students' errors in figure based on before achievement test are shown as follows: First, the most errors occurred in the figure was the ones from deficient mastery of prerequisite concepts and definitions. Specially, the errors from deficient mastery of prerequisite concepts and definitions have the majority. it is very high ratio even if it considers an influence of an evaluation question item. so, I think it is necessary to teach concept related figure above all. Second, as the results of application 'finding errors' to a class, there is a meaningful difference in the mathematical achievement and reasoning ability within significance level 5%. This means 'finding errors' is one of the teaching method that it develops the mathematical achievement and reasoning ability.

• The Mathematical Education
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• v.60 no.3
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• pp.321-340
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• 2021

As many changes in the future society represented by the age of artificial intelligence(AI) are expected to come, efforts are being made to draw the shape of the future education and various research methods are being employed to support the attempts. While many research studies use methods for deriving generalized results such as expert survey and trend analysis in along with a review of literature, there are attempts to apply the scenario methodology to explore ideas and information needed within a changing context. A scenario method, one of the experiential learning strategies, aims to seek various and alternative approaches by establishing a plan from the present conditions considering future changes. In this study, in-service teachers' perceptions and expectations of the interactivity between human and AI teachers were visualized by applying the role-play presentation technique that grafted the concept of role-play game to the scenario method. In addition, the mandal-art method was introduced to support in conducting productive discussion during the teachers' collaboration. This method appeared to help to depict teachers' perceptions of AI teachers in the detailed and concrete form, which may flow in the abstract otherwise. Through analyses of the teachers' role-play presentations with the implementation of the madal-art method it was suggested that most teachers would want to collaborate with an AI teacher for improved instruction and individualized student learning while they would take the instructional authority over the AI teacher in the classroom.

• Education of Primary School Mathematics
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• v.25 no.2
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• pp.161-178
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• 2022

Korean uses a dual numeral system consisting of native and Chinese words. This dual numerical system is customarily selected in real life, mixed with two methods, or irregularly transformed. Therefore, the burden on both students and teachers is increased in the learning guidance process of numeral. This study recognized the need to improve the difficulty of learning guidance due to the dual numeral system. To this end, the context in which the numeral system method is selected, various modified cases, and related guidance contents of the current curriculum and textbooks were analyzed and organized. As a result of the analysis, there were characteristics of the selection and deformation of the numeral system method, which appears according to the actual situation using numerical. However, the criteria for characteristics were ambiguous and there were no specific guidance guidelines in the curriculum and textbooks. In this case, since the role of the teacher is more important, the teacher should be aware of the detailed characteristics of the actual situation related to the dual numeral system and let the student understand through experience and practice on various aspects of the use of the dual numeral system.

• The Korean Journal of Applied Statistics
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• v.35 no.2
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• pp.189-201
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• 2022

In this study, we propose factor augmentation to improve forecasting power of cryptocurrency return. We consider financial and economic variables as well as psychological aspect for possible factors. To be more specific, financial and economic factors are obtained by applying principal factor analysis. Psychological factor is summarized by news sentiment analysis. We also visualize such factors through impulse response analysis. In the modeling perspective, we consider ARIMAX as the classical model, and random forest and deep learning to accommodate nonlinear features. As a result, we show that factor augmentation reduces prediction error and the GRU performed the best amongst all models considered.

• Genomics & Informatics
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• v.20 no.2
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• pp.23.1-23.9
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• 2022

A survival prediction model has recently been developed to evaluate the prognosis of resected nonmetastatic pancreatic ductal adenocarcinoma based on a Cox model using two nationwide databases: Surveillance, Epidemiology and End Results (SEER) and Korea Tumor Registry System-Biliary Pancreas (KOTUS-BP). In this study, we applied two machine learning methods-random survival forests (RSF) and support vector machines (SVM)-for survival analysis and compared their prediction performance using the SEER and KOTUS-BP datasets. Three schemes were used for model development and evaluation. First, we utilized data from SEER for model development and used data from KOTUS-BP for external evaluation. Second, these two datasets were swapped by taking data from KOTUS-BP for model development and data from SEER for external evaluation. Finally, we mixed these two datasets half and half and utilized the mixed datasets for model development and validation. We used 9,624 patients from SEER and 3,281 patients from KOTUS-BP to construct a prediction model with seven covariates: age, sex, histologic differentiation, adjuvant treatment, resection margin status, and the American Joint Committee on Cancer 8th edition T-stage and N-stage. Comparing the three schemes, the performance of the Cox model, RSF, and SVM was better when using the mixed datasets than when using the unmixed datasets. When using the mixed datasets, the C-index, 1-year, 2-year, and 3-year time-dependent areas under the curve for the Cox model were 0.644, 0.698, 0.680, and 0.687, respectively. The Cox model performed slightly better than RSF and SVM.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.291-297
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• 2022

Modern challenges in the educational environment force scientists and practitioners to search for an adequate answer. In particular, the war in Ukraine demonstrated the importance of developing information competence as one of the main means of distinguishing true information from a whole stream of fake news. This is especially relevant in connection with the introduction of distance learning when students must find and process a large amount of information on their own. Therefore, the purpose of the article is to analyze the training of higher education students through the prism of acquiring the necessary level of informational competence in war conditions. For this, general scientific and special research methods, as well as the experimental method, were used. In the results, the peculiarities of the interpretation of information competence in the distance form of education among modern researchers are determined, the psychological components of resistance to fakes are analyzed. Based on the conducted empirical measurements, it was established that thorough work on student education gives positive skills when working independently with Internet materials, strengthens the ability to distinguish false information and propaganda from the real state of affairs. The conclusions summarize the results of the empirical research and suggest ways to improve the situation with the formation of information competence.

• Journal of The Korean Association of Information Education
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• v.26 no.4
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• pp.285-293
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• 2022

The COVID-19 outbreak, which took longer than expected, caused considerable damage to students' basic academic ability in mathematics. In this paper, a multiplication table practice application that can help students improve their basic multiplication arithmetic skills has been developed based on a cloud-service. The performance of the application was improved by integrating the Flutter framework, Google Cloud, and Google Sheets. As a result of applying this application to 72 6th graders in elementary schools located in K Metropolitan City, for one week. students' spending time required for solving multiplication table problems was reduced by more than 28% compared to the initial period, while students' learning data was able to be accurately collected without errors. It is hoped that the development case conducted through the Flutter framework in this study can lead to the development of other educational learning applications.

• Education of Primary School Mathematics
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• v.25 no.3
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• pp.213-232
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• 2022

With the importance of number line in learning fractions, this study investigated how 4th grade students understand fractions and its operations in number line. The questionnaire consisted 22 items which were related to representing fractions, comparing the size of fractions, and operating addition and subtraction of fractions. Both structured number line and sub-structured number line were presented in the items. As results of the study, the overall success rates were not high and even some items showed higher incorrect answer rates than the success rates. Also, the students showed a difficulty in solving non-structured number line tasks. It was also noticeable that students showed several types of incorrect answers, which means that students had incomplete understanding of both fractions and number line. This paper is expected to shed light on elementary students' understanding of fractions and number line and to provide implications of how to deal with number line in teaching and learning fractions in the elementary school.

• Imaging Science in Dentistry
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• v.52 no.4
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• pp.383-391
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• 2022

Purpose: Periodontitis, the most prevalent chronic inflammatory condition affecting teeth-supporting tissues, is diagnosed and classified through clinical and radiographic examinations. The staging of periodontitis using panoramic radiographs provides information for designing computer-assisted diagnostic systems. Performing image segmentation in periodontitis is required for image processing in diagnostic applications. This study evaluated image segmentation for periodontitis staging based on deep learning approaches. Materials and Methods: Multi-Label U-Net and Mask R-CNN models were compared for image segmentation to detect periodontitis using 100 digital panoramic radiographs. Normal conditions and 4 stages of periodontitis were annotated on these panoramic radiographs. A total of 1100 original and augmented images were then randomly divided into a training (75%) dataset to produce segmentation models and a testing (25%) dataset to determine the evaluation metrics of the segmentation models. Results: The performance of the segmentation models against the radiographic diagnosis of periodontitis conducted by a dentist was described by evaluation metrics(i.e., dice coefficient and intersection-over-union [IoU] score). MultiLabel U-Net achieved a dice coefficient of 0.96 and an IoU score of 0.97. Meanwhile, Mask R-CNN attained a dice coefficient of 0.87 and an IoU score of 0.74. U-Net showed the characteristic of semantic segmentation, and Mask R-CNN performed instance segmentation with accuracy, precision, recall, and F1-score values of 95%, 85.6%, 88.2%, and 86.6%, respectively. Conclusion: Multi-Label U-Net produced superior image segmentation to that of Mask R-CNN. The authors recommend integrating it with other techniques to develop hybrid models for automatic periodontitis detection.

• Communications of Mathematical Education
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• v.36 no.1
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• pp.59-72
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• 2022

The purpose of this study is to understand the characteristics of the mathematical modeling tasks and lesson designs developed by pre-service teachers based on the inherent awareness of mathematical modeling, considering the importance of creating a task to perform mathematical modeling activity and designing a lesson. As a result, the mathematical modeling tasks developed by pre-service teachers mainly presents an appropriate amount of information using real life contexts for the purpose of learning using concepts, and it showed a tendency to develop to the level of cognitive demand that required procedures with connections to understanding, meaning, or concepts. And most of the developed modeling task-based lessons showed a tendency to design warm-up activity, model-eliciting activity, and model-exploration activity. This result is due to the lack of experience of pre-service teachers in creating mathematical modeling tasks. Therefore, it is necessary to continuously provide opportunities for pre-service teachers to learn concepts or create mathematical modeling tasks intended for exploration according to various mathematical contents, thereby actively cultivating their ability to create modeling tasks in the course of training pre-service teachers. Furthermore, it is necessary to strengthen the expertise in mathematical modeling teaching and learning by providing opportunities to actually perform the mathematical modeling-based classes designed by pre-service teachers and to experience the process of reflecting on the lessons.