• Journal of the Korea Society of Computer and Information
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• v.20 no.5
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• pp.161-169
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• 2015

In this paper, we propose an smart device based robot programming education program and analyzing students' perceptions such as satisfaction, Expectancy-Value of IT convergence learning after the robot education program according to elementary gifted students' level. Smart device based robot programming education program designed based on schematic of the convergence suggested by WTEC and consist of creative phase, integration/fusion phase, innovation phase, outcome phase for learning practical process of the IT convergence. We are conducting a smart device based robot programming education class to consist of 126 gifted students and analysing the difference of perception. According to analysis of the result, core and advanced students' perception on satisfaction score shows also high. However, advanced level students' satisfaction score shows higher than core students' satisfaction score. Also, advanced level students' expectancy-value score on IT convergence learning shows higher than core students' score.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.16-30
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• 2023

The elderly population is increasing owing to a low fertility rate and an aging population. In addition, life expectancy is increasing, and the advancement of medicine has increased the importance of health to most people. Therefore, government and companies are developing and supporting smart healthcare, which is a health-related product or industry, and providing related services. Moreover, with the development of the Internet, many people are managing their health through online searches. The most convenient way to achieve such management is by consuming nutritional supplements or seasonal foods to prevent a nutrient deficiency. However, before implementing such methods, knowing the nutrient status of the individual is difficult, and even if a test method is developed, the cost of the test will be a burden. To solve this problem, we developed a questionnaire related to nutrient classification twice, based upon which an adaptive algorithm was designed. This algorithm was designed as a machine learning based algorithm for nutrient classification and its accuracy was much better than the other machine learning algorithm.

• Journal of Engineering Education Research
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• v.16 no.2
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• pp.50-57
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• 2013

The study to improve engineering students' performance in studying physics lacked despite of the importance of studying physics in engineering education. The cognitive belief and the motivational belief in studying physics had a strong effect on studying physics. The purpose of this study was to seek the educational way through comparing professors' expectations with students' beliefs about the cognitive belief and the motivational belief in studying physics. The cognitive belief in studying physics was considered as variables like 'knowledge', 'learning' and 'relation'. The motivational belief in studying physics was considered as variables like 'expectancy' and 'value'. It was the 'expectancy' that was the most different dimension between professors' expectations and students' beliefs. It means that students have little confidence in their abilities to study physics, though professors expect their students to be confident. Professor who teaches physics to engineering students recognize these differences, need to have interest in affective domains of beliefs to teach. In addition, there is need to teaching and learning strategies that can lead engineering students' beliefs about ability to perform the task, the purpose, importance, interesting for physics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.90-113
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• 2021

Electronic Records Management System (ERMS) is a computer program or set of applications that is utilized for keeping up to date records along with their storage. ERMS has been extensively utilized for enhancing the performance of academic institutions. The system assists in the planning and decision-making processes, which in turn enhances the competencies. However, although ERMS is significant in supporting the process of decision-making, the majority of organizations have failed to take an initiative to implement it, taking into account that are some implementing it without an appropriate framework, and thus resulted in the practice which does not meet the accepted standard. Therefore, this study identifies the factors influencing the adoption of ERMS among employees of HLI in Yemen and the role of such adoption in the decision-making process, using the Unified Theory of Acceptance and Use of Technology (UTAUT) along with Technology, Organization and Environment (TOE) as the underpinning theories. The study conducts a cross-sectional survey with a questionnaire as the technique for data collection, distributed to 364 participants in various Yemeni public Higher Learning Institutions (HLI). Using AMOS as a statistical method, the findings revealed there are significant and positive relationships between technology factors (effort expectancy, performance expectancy, IT infrastructure and security), organizational factors (top management support, financial support, training, and policy),environmental factors (competitiveness pressure, facilitating conditions and trust) and behavioral intention to adopt ERMS, which in return has a significant relationship with the process of decision-making in HLI. The study also presents a variety of theoretical and empirical contributions that enrich the body of knowledge in the field of technology adoption and the electronic record's domain.

• Journal of the Korean Society of Systems Engineering
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• v.17 no.2
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• pp.98-105
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• 2021

As the average life expectancy is rising, the population is aging and the number of chronic diseases is increasing. This has increased the importance of healthy life and health management, and interest in mobile health services is on the rise thanks to the development of ICT(Information and communication technologies) and the smartphone use expansion. In order to meet these interests, many mobile services related to daily health are being launched in the market. Therefore, in this study, the characteristics of users who actually use mobile health services were analyzed and a predictive model applied with machine learning modeling was developed. As a result of the study, we developed a prediction model to which the decision tree and ensemble methods were applied. And it was found that the mobile health service users' continued use can be induced by providing features that require frequent visit, suggesting achievable activity missions, and guiding the sensor connection for user's activity measurement.

• Journal of Science Education
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• v.35 no.1
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• pp.13-22
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• 2011

There is an increasing emphasis on science teaching in inclusion education setting, but still few research and practice in science education field including science teacher training course as well. It is well known that teaching efficacy of teacher is an important factor to influence teaching behavior and students' learning, but it is hard to find related studies about self-efficacy on teaching science for the disabled students. In this study pre-service science teachers' self-efficacy on science teaching for the disabled students was investigated and analyzed. For this a questionnaire consisted of 3 sub-scale like learning efficacy scale, teaching efficacy scale, and outcome expectancy scale was enacted to 97 pre-service science teachers. As a result, pre-service science teachers showed relatively low efficacy in teaching but showed positive learning efficacy and outcome expectancy. There was no meaningful difference in distribution of efficacy belief by gender, however the experience of teaching science for the disabled students made difference in outcome expectancy. From this study the implication for science teacher training course was inferred to meet the needs for science education in inclusion setting.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.2
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• pp.83-93
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• 2020

The purpose of this study was to verify the effect on learning using YouTube. The relationship between expectations, cognitive attitudes, emotional attitudes, and reuse intentions was explored. The results are as follows. First, the factors affecting the intention to reuse YouTube were emotional attitude and expectation. cognitive attitude did not show any significant effect. Second, cognitive attitude and expectation agreement were significant variables in emotional attitude. cognitive attitude was identified as a major factor affecting emotional attitude. Third, expectation agreement was found to have a significant influence on cognitive attitude. Therefore, expectancy is an important factor in identifying cognitive attitudes. In particular, the satisfaction of expectations after experiencing a new technology or system, such as YouTube, affects the cognitive attitude. Finally, the main findings of this study were that cognitive attitude was not a variable affecting the intention to reuse YouTube. The reason for this is that YouTube is used as a medium of interest, and it is not used as a medium for searching the main data source for learning. Therefore, in order to activate YouTube learning, it is necessary to convert recognition into YouTube for learning rather than YouTube for play.

• Journal of The Korean Association For Science Education
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• v.17 no.4
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• pp.415-423
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• 1997

The purposes of this study were to investigate the intercorrelations among various motivational patterns and learning strategies and to examine the differences in motivation and strategy usage in terms of students' science achievement level, gender, and grade. A questionnaire on achievement goal, self-efficacy, self-concept of ability, expectancy, value, causal attributions, and learning strategies was administered to 360 junior high/high school students (178 males, 182 females). Students who adopted performance-oriented goal tended not to be task oriented. Task-oriented students had high levels of self-efficacy, high self-concept of ability, and expectancies for future performance in science. They also valued science and attributed thier failures to the lack of effort. However, performance-oriented students evaluated their ability negatively, did not value science, and attributed thier failures to uncontrollable causes. With respect to learning strategy, task-oriented students tended to use deep-level strategy, whereas performance-oriented students tended to use surface-level strategy and not to use deep-level strategy. High-achieving students, boys, and junior high school students were more task-oriented, evaluated their ability more positively, and valued science more than low-achieving students, girls, and high school students, respectively. High-achieving students and boys also used deep-level strategy more than each of their counterparts. However, no significant difference in learning strategy was found between junior high school students and high school students. Educational implications of these findings are discussed.

• Journal of the Semiconductor & Display Technology
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• v.15 no.3
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• pp.46-50
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• 2016

Recently, Depending on expectancy effect and ripple effect of augmented reality, the convergence between augmented reality and culture & arts are being actively conducted. This paper proposes a learning method for effective object tracking in 3D storytelling augmented reality in cultural properties. The proposed system is based on marker-less tracking, and there are four modules that are recognition, tracking, detecting and learning module. Recognition module is composed of SURF and LSH, and then this module generates standard object information. Tracking module tracks an object using object tracking based on reliability. This information is stored in Learning module along with learned time information. Detecting module finds out the object based on having the best possible knowledge available among the learned objects information, when the system fails to track. Also, it proposes a method for robustly implementing a 3D storytelling augmented reality in cultural properties in the future.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1233-1241
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• 2022

Tumors of the brain are the deadliest, with a life expectancy of only a few years for those with the most advanced forms. Diagnosing a brain tumor is critical to developing a treatment plan to help patients with the disease live longer. A misdiagnosis of brain tumors will lead to incorrect medical treatment, decreasing a patient's chance of survival. Radiologists classify brain tumors via biopsy, which takes a long time. As a result, the doctor will need an automatic classification system to identify brain tumors. Image classification is one application of the deep learning method in computer vision. One of the deep learning's most powerful algorithms is the convolutional neural network (CNN). This paper will introduce a novel deep learning structure and image gradient to classify brain tumors. Meningioma, glioma, and pituitary tumors are the three most popular forms of brain cancer represented in the Figshare dataset, which contains 3,064 T1-weighted brain images from 233 patients. According to the numerical results, our method is more accurate than other approaches.