• Communications of Mathematical Education
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• v.26 no.1
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• pp.109-135
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• 2012

On the standards or elements of teaching evaluation, the Korea Institute of Curriculum and Evaluation(KICE) has carried out the following research such as : 1) development of the standards on teaching evaluation between 2004 and 2006, and 2) investigation on the elements of Teacher Knowledge. The purposes of development of evaluation standards for mathematics teaching through those studies were to improve not only mathematics teachers' professionalism but also their own teaching methods or strategies. In this study, the standards were revised and modified by analyzing the results of those studies focused on the knowledge of subject matter knowledge, knowledge of learners' understanding, teaching and learning methods and assessments, and teaching contexts. For this purpose, the part of subject matter knowledge was consisted of four evaluation domains such as the knowledge of curriculum reconstruction, knowledge of mathematical contents, methodological knowledge, mathematical value. The part of Learners' unders tanding included the evaluation domains such as students' intellectual and achievement level, students' misconception in math, students' motivation on learning, students' attitude on mathematics learning, and students' learning strategies. The part of teaching methods and evaluation was consisted of seventh evaluation domains such as instruction involving instructional goal and content, instruction involving problem-solving activity, instruction involving learners' achievement level and attitude, instruction on communication skills, planning of assessment method and procedure, development on assessment tool, application on assessment result in class were new established. Also, the part of teaching context was consisted of four evaluation domains such as application of instructional tools and materials, commercial manipulatives, environment of classroom including distribution and control of class group, atmosphere of classroom, management of teaching contexts including management of student. According to those evaluation domains of each teacher knowledge, elements on teaching evaluation focused on the teacher's knowledge were established using the instructional evaluation framework, which is developed in this study, including the four areas of obtaining, planning, acting, and reflecting.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.3
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• pp.133-140
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• 2022

We investigate the performance of deep learning-based Korean language models on a task of predicting the score range of Korean essays written by foreign students. We construct a data set containing a total of 304 essays, which include essays discussing the criteria for choosing a job ('job'), conditions of a happy life ('happ'), relationship between money and happiness ('econ'), and definition of success ('succ'). These essays were labeled according to four letter grades (A, B, C, and D), and a total of eleven essay score range prediction experiments were conducted (i.e., five for predicting the score range of 'job' essays, five for predicting the score range of 'happiness' essays, and one for predicting the score range of mixed topic essays). Three deep learning-based Korean language models, KoBERT, KcBERT, and KR-BERT, were fine-tuned using various training data. Moreover, two traditional probabilistic machine learning classifiers, naive Bayes and logistic regression, were also evaluated. Experiment results show that deep learning-based Korean language models performed better than the two traditional classifiers, with KR-BERT performing the best with 55.83% overall average prediction accuracy. A close second was KcBERT (55.77%) followed by KoBERT (54.91%). The performances of naive Bayes and logistic regression classifiers were 52.52% and 50.28% respectively. Due to the scarcity of training data and the imbalance in class distribution, the overall prediction performance was not high for all classifiers. Moreover, the classifiers' vocabulary did not explicitly capture the error features that were helpful in correctly grading the Korean essay. By overcoming these two limitations, we expect the score range prediction performance to improve.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.391-393
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• 2022

In recent years, technologies forecasting demand based on deep learning and big data have accelerated the smartification of the field of e-commerce, logistics and distribution areas. In particular, ports, which are the center of global transportation networks and modern intelligent logistics, are rapidly responding to changes in the global economy and port environment caused by the 4th industrial revolution. Port traffic forecasting will have an important impact in various fields such as new port construction, port expansion, and terminal operation. Therefore, the purpose of this study is to compare the time series analysis and deep learning analysis, which are often used for port traffic prediction, and to derive a prediction model suitable for the future container prediction of Busan Port. In addition, external variables related to trade volume changes were selected as correlations and applied to the multivariate deep learning prediction model. As a result, it was found that the LSTM error was low in the single-variable prediction model using only Busan Port container freight volume, and the LSTM error was also low in the multivariate prediction model using external variables.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.599-604
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• 2005

This paper presents fuzzy rules to predict diagnosis of Wisconsin breast cancer with minimized number of feature in put using the neural network with weighted fuzzy membership functions (NEWFM) and the non-overlap area distribution measurement method. NEWFM is capable of self-adapting weighted membership functions from the given the Wisconsin breast cancer clinical training data. n set of small, medium, and large weighted triangular membership functions in a hyperbox are used for representing n set of featured input. The membership functions are randomly distributed and weighted initially, and then their positions and weights are adjusted during learning. After learning, prediction rules are extracted directly from n set of enhanced bounded sums of n set of small, medium, and large weighted fuzzy membership functions. Then, the non-overlap area distribution measurement method is applied to select important features by deleting less important features. Two sets of prediction rules extracted from NEWFM using the selected 4 input features out of 9 features outperform to the current published results in number of set of rules, number of input features, and accuracy with 99.71%.

• Journal of Digital Convergence
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• v.18 no.6
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• pp.167-175
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• 2020

The purpose of this paper is to provide directional and policy references to develop a higher level of service quality and consumer-oriented e-commerce platform. This paper has established a model of consumer behavior of Chinese fresh agricultural e-commerce using customer satisfaction theory and cognitive value theory, and used survey and SPS23.0 to verify hypothesis. Studies have shown that when consumers consume fresh agricultural products, product quality, logistics and distribution service quality, interactive quality of e-commerce platform, and product price and cognitive value have a positive effect on consumer behavior. This study is meaningful in the study of consumer behavior of fresh agricultural e-commerce, and in the case of fresh agricultural e-commerce companies, consumer behavior can be understood. In the model constructed in this paper, the relationship between each influencing factor and consumer behavior is considered comprehensively, but the possible relationship between fine molecular factors has not been studied and analyzed. In the future learning process, it is necessary to make clear the characteristics and particularity of the industry, think about its influencing factors comprehensively and make in-depth analysis.

• Communications of Mathematical Education
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• v.32 no.3
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• pp.435-453
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• 2018

The results analysis of National Assessment of Educational Achievement(NAEA) can provide various implications for teaching and learning in the school field. In this study we analyzed the deviation of NAEA achievement level-based correct-answer rate and the distribution of the responses percentages for three years from 2015 to 2017 focused on multiple-choice items. First we calculated the deviation of correct-answer rate between advanced level and proficient level and between proficient level and basic level, and then we selected the items whose deviation of correct-answer rate is more than the third quartile. We explored what the content areas, behavior areas and achievement standards of each item are and what the achievement standards and characteristics of these questions are. Based on the results of the analysis, we intended to derive implications for appropriate teaching-learning methods at each achievement-level.

• Communications of Mathematical Education
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• v.25 no.3
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• pp.607-627
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• 2011

The purpose of this study is to analyse teaching and learning effects of the structural-mapping used instruction and to find out the characteristics of problem solving process in permutation and combination. For this study, two classes of 11th grade students(67 students) were randomly selected from S high school in D city. One of them was assigned to the experimental group and the other to the control group, respectively. Four lectures of the structural-mapping used instruction were carried out in the experimental group and same amount of lectures of the text book oriented instruction were carried out in the control group. The research findings are as follows. First, the structural-mapping used instruction is shown to be more effective in achievement than the traditional textbook-oriented instruction. Second, the ball-box model is found out to be easier and simpler than the selection-distribution model. Third, students who used the ball-box model are properly able to use both model.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.2
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• pp.239-246
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• 2019

Teenagers in multicultural families are more prone to depression and problem behaviors caused by violence such as bullying in schools due to their appearance, language presentation skills, and poor learning abilities compared to teenagers in general families. This study is meaningful in that it provides basic information for prevention measures in intervening with damage caused by school violence such as depression, anxiety, suicidal impulses and emotional and social. For this purpose, a survey of 300 elementary school students from 4 to 6 grade, junior high school, and high school students was conducted. A total of 400 questionnaires were distributed and of thos e 385 were used for the final analysis. The results of the study are as follows. First, the psychological factors of suicidal ideation were higher in the victimized group than school violence. Second, there was a significant difference in the relationship between emotional - social isolation and school violence experience. Third, there was a significant difference in the relationship between experience of suicide ideation and depression as well as anxiety of emotional - social isolation with psychological maladjustment. In conclusion, we plan to find ways to stabilize the multicultural society by providing prevention and protection measures against school violence.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.6
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• pp.313-324
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• 2022

The goal of this research is to see how closely accounting programs in Saudi Arabian colleges comply with the International Accounting Education Standards (IESs). Further, it aims to assess the level of awareness and knowledge of IESs among accounting academics and to examine the possible explanatory factors for their variation. A structured questionnaire was sent to accounting faculty members at 37 Saudi universities. Out of 541 distributed questionnaires, a total of 102 usable responses were received from 26 universities. The findings show that accounting programs in Saudi universities are partially compliant with the guidelines of IESs and accounting academics in those universities are moderately aware of IESs. High variation in the level of academics' knowledge of IESs was detected and was significantly influenced by industry work experience, academic ranks, and professional qualification. The findings of this study suggest that Saudi Universities should work closely with the local and international accounting professional bodies, i.e. the Saudi Organization for Chartered and Professional Accountants (SOCPA) and the International Federation of Accountants (IFAC) to improve accounting programs based on the guidelines of IESs to cope with the recent changes in the capital market of the kingdom and the adoption of the International Financial Reporting Standards.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.4
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• pp.109-120
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• 2022

This study has incorporated the mechanics-dynamics-emotions (MDE) and two behavioral learning paths to investigate the customers' co-creation behavior in Taiwan. The intuitive path begins with a gamification design that reflects the customers' proactive and innovative behavior; the cognitive path begins with persuasion knowledge remarks based on rational and reactive reasoning. These two paths conclude what forms user co-creation. The study collects data of 505 active social media users in Taiwan and employs structural equation modeling. The empirical findings demonstrate persuasive knowledge and gamification design are significantly associated with self-reference, and in turn, positively associated with co-creation. It indicates that cognitive behavior plays the main role in forming co-creation. Participants are more drawn to co-creation behaviors by the marketing contents that prompt reactive behaviors than proactive ones. Therefore, marketing managers can use appropriate stimuli to enhance co-creation behavior. Companies can design activities related to users, and more accessible for reactive, instead of proactive behavior, i.e., asking for their initiatives. It also suggests that companies' marketing campaigns should involve key opinion leaders matching the product image and the target audience's preferences. The novelty of this study is to introduce a novel augmented MDE framework to extend the "dynamics" into the incubation and implementation stage.