• Journal of Educational Research in Mathematics
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• v.9 no.2
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• pp.439-457
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• 1999

In this paper, we tried to find out what makes the students feel anxious to mathematics and the ways to decrease their anxiety by comparing two learning types, self-directed-learning and learning in a body, by means of continuous observation and interviews. To perform this study, two classes of self-directed-learning and other two classes of learning-in a body were chosen from the third year-students in Wando Middle School in Chollanamdo. In this study, we obtained the following results: 1. In high group in math grade, students in self-directed-learning are less anxious than students in learning-in a body. 2. In average group in math grade, students in self-directed-learning are much more anxious than students in learning-in a body. 3. In low group in math grade, both students in self-directed-learning and students in teaming-in a body feel anxious about math and there is no difference between them. 4. Anxiety about math hove positive influence on high group in math grade. 5. Anxiety about math have negative influence on average and low groups in math grade. Especially, low group students had no interests about mathematics because of their math anxiety. We observed that some students got over the math anxiety to some meaningful extent by means of interviews or appropriate advices, and became to have confidence and interests in mathematics.

• The Journal of the Convergence on Culture Technology
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• v.5 no.2
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• pp.375-380
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• 2019

In this paper, we study learning process mining and analytic technology based on open education platform. A study on mining through personal learning history log data based on an open education platform such as MOOC which is growing in interest recently. This technology is to design and implement a learning process mining framework for discovering and analyzing meaningful learning processes and knowledge from learning history log data. Learning process mining framework technology is a technique for expressing, extracting, analyzing and visualizing the learning process to provide learners with improved learning processes and educational services.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.4
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• pp.111-121
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• 2020

This study analyzed the effects on system quality, learning commitment, and satisfaction in a mobile environment. A survey was conducted on 192 students enrolled in K University, and the research results are as follows. first, it was found that usefulness had an effect on learning commitment, but connectivity and reliability did not affect learning commitment. second, it was found that the usefulness and connectivity of the system quality had a significant effect on the satisfaction of use. third, the intermediary effect of learning immersion was verified as the connectivity, reliability, and usefulness of the system quality influence the satisfaction of use. connectivity and reliability had no mediating effect of learning commitment, and usefulness was found to play a partial mediating role in affecting user satisfaction. This study is meaningful in that it can provide a plan for improving the quality management of mobile learning and improving the learning effect by analyzing the effects on mobile learning from multiple perspectives.

• Journal of Digital Contents Society
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• v.17 no.6
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• pp.489-497
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• 2016

This study focused on the focus group interview based on the questionnaire. Prior to the interview, we used questionnaires from the previous researchers in order to select the questionnaires and interviews of the focus group. In order to measure the possibility, which is the expression characteristic of the safety education app, the items related to cognitive, sensual, physical, and safety behaviors were used as constituent factors. And the safety education app to analyze was selected 'Water Go GO!' App developed by the National Emergency Management Agency. The results of this study are as follows: First, the learner should help to participate in learning continuously in order to make meaningful learning activities in safety education app learning environment. Second, learners must interact with mobile devices in their apps to facilitate learning while reducing the number of factors that can interfere with learners' learning. This study is meaningful in that it can utilize this design principle as a guideline for enhancing safety behaviors.

• Journal of Elementary Mathematics Education in Korea
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• v.11 no.2
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• pp.161-176
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• 2007

It is useless to say that time is precious and important. So it does when we emphasize the importance of studying the quality and efficiency of time in learning, especially in the learning of Mathematics. In this respect, this study aims to examine the overall structure of time application in the learning of Mathematics, understanding the state and problems of Mathematics education in respect of time application, and finally seeking to find the solutions for the problems. As a first step, the items below were examined for the solutions: First, the eight viewpoints of time in Mathematics education was examined and the meaning of each viewpoint was analysed. Second, the variables resulting from teachers was examined. The preconditions for mathematics education, the attitude towards Mathematics classes, viewpoints of mathematics, the forms of self-expression, the way of utterance can be considered as the variables mentioned above. Third, the variables resulting from students was examined. Learning attitude, specific activity(both meaningful and meaningless), practical uses of teaching tools, game activities, the ways of communication and problem solving can be examined as well. In conclusion, it needs to be stressed that Mathematics class should be the meaningful time for learners, parents, and teachers. The class should guarantee the satisfaction of the learners. In other words, even if physical time is applied the same to everyone, it may differ in degree of quality and value of time application according to the way one spends the time.

• Journal of the Korean Institute of Educational Facilities
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• v.27 no.5
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• pp.13-23
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• 2020

From the perspective of smart learning space, this study aims to take a look at the learning space of college students who do online remote learning in the COVID-19 era, and analyze their demands on what smart learning space they want. Furthermore, this study intends to provide valuable implications for the technology-enhanced learning environments by deriving design elements that make up the university's smart learning space. To achieve these goals, we conducted a review of prior studies, interviews with experts, and case analysis on smart learning spaces of major Korean and foreign universities, which are considered as innovative cases. Additionally, in order to confirm the difference between the importance level recognized by the college students and the current performance level for nine components of technology and for ten components of spaces and facilities, a paired t-test and an Importance-Performance Analysis (IPA) were carried out. According to the result of IPA analysis, Internet of Things from the technological aspects, a desk that can supply power and a flexible learning space from the aspects of spaces and facilities were found to have much lower performance than the importance. This result is meaningful in suggesting key design components for smart campus development in the post-COVID-19 world.

• Journal of Korean Home Economics Education Association
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• v.23 no.1
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• pp.113-141
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• 2011

The purpose of this study was to examine the effects of home economics instruction in food labeling using a motivational(ARCS-Attention, Relevance, Confidence, and Satisfaction) strategy to increase middle school students' learning motivation, recognition and use of food labels. To achieve this purpose, teaching-learning plans of food label instruction using a motivation(ARCS) strategy were developed over four class periods using a pretest-posttest experimental design. The experiment was conducted across two groups as follows: 4 experimental groups that received the motivation(ARCS) strategy instruction, and 3 comparative groups that received lecture type instruction. The pretest-posttest scores of the experimental and comparative groups were compared. The 203 data of questionnaires for the experiment were analyzed and evaluated by Analysis of Covariance(ANCOVA) using SPSS Win 12,0. The results of this study were as follows: First, teaching-learning plans, learning materials, and teacher reference materials for the home economics food label instruction that applied the motivation(ARCS) strategy were developed in five subject areas: nutrition labels, food additives, genetically modified food, irradiated food, and food quality verification labels. Second, students' learning motivation of the two groups showed statistically meaningful differences. Home economics instruction using a motivation(ARCS) strategy was more effective in increasing students' learning motivation than lecture type instruction. Third, as a result of ANCOVA which regulated the recognition of food labels in the pre-experimental design, the recognition of food labels in the post-experimental design showed the meaningful differences depending on the instruction style(motivation strategy and lecture type instruction). In addition, comprehensibility, practical use and educational necessity of food label details showed statistically meaningful differences. Home economics instruction using motivation(ARCS) strategy was more effective than lecture type instruction in improving students' recognition of food labeling. Fourth, as a result of ANCOVA which regulated the use of food labels in the pre-experimental stage, the use of food labels in the post-experimental stage showed meaningful differences between experimental and comparative groups depending on the instruction style. Therefore, home economics instruction in food labeling using motivation(ARCS) strategy was more effective than lecture type instruction in increasing students' use of food labels.

• Journal of Information Technology Applications and Management
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• v.15 no.2
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• pp.33-49
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• 2008

The purpose of this study is to find student factors associated with the students' evaluation of university teaching, and to provide a meaningful reference to policy-making of teaching evaluation. Based on the surveyed questionnaires from 232 students who participated in e-learning course. in combination with applying descriptive statistics, this study analyzes (1) the influences of students' pre-motivation level of student based-on ARCS theory on class satisfaction, (2) the influences of students' grade, attendance, and class involvement on class satisfaction, and (3) the influences of e-learning experience on students' pre-motivation level and class satisfaction. Result of this study shows that: (1) students' pre-motivation level including Attention(A), Relevance(R), Confidence(C), and Satisfaction(S) is positively correlated to students' evaluation for teaching, (2) students' grade, attendance. and class involvement are positively correlated to students' evaluation for teaching, and (3) students' e-learning experience is not related with students' pre-motivation level, whereas it is related with class satisfaction.

• International Journal of Advanced Culture Technology
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• v.8 no.4
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• pp.119-128
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• 2020

Object detection is an important field of computer vision and is applied to applications such as security, autonomous driving, and face recognition. Recently, as the application of artificial intelligence technology including deep learning has been applied in various fields, it has become a more powerful tool that can learn meaningful high-level, deeper features, solving difficult problems that have not been solved. Therefore, deep learning techniques are also being studied in the field of object detection, and algorithms with excellent performance are being introduced. In this paper, a deep learning-based object detection algorithm used to detect multiple objects in an image is investigated, and future development directions are presented.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.437-442
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• 2021

In this study, a recommendation algorithm was implemented by learning a deep learning-based classification model for consumer data. For this purpose, a meaningful result is presented as a result of learning using ResNet50, which is commonly used in classification tasks by converting user data into images.