• Communications of Mathematical Education
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• v.33 no.3
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• pp.377-394
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• 2019

The purpose of this study is to scrutinize the characteristics of a teacher's discursive competence on the basis of mathematical competencies. For this purpose, we observed all semester-long classes of a middle school teacher, who changed her own teaching methods for the last 20 years, collected video clips on them, and analyzed classroom discourse. Data analysis shows that in problem solving competency, she helped students focus on mathematically important components for problem understanding, and in reasoning competency, there was a discursive competence which articulated thinking processes for understanding the needs of mathematical justification. And in creativity and confluence competency, there was a discursive competence which developed class discussions by sharing peers' problem solving methods and encouraging students to apply alternative problem solving methods, whereas in communication competency, there was a discursive competency which explored mathematical relationships through the need for multiple mathematical representations and discussions about their differences. These results can provide concrete directions to developing curricula for future teacher education by suggesting ideas about how to combine practices with PCK needed for mathematics teaching.

• Journal of Technologic Dentistry
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• v.42 no.4
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• pp.379-387
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• 2020

Purpose: This study aimed to explore methods to improve the quality recognition and satisfaction level of non-face-to-face lectures among students in the departments of dental technology and dental hygiene. Methods: This survey was conducted to assess the status and preference of non-face-to-face lectures and the level of awareness and satisfaction regarding the quality of these lectures among 179 students of dental technology and 295 students of dental hygiene. Statistical analyses were performed using frequency analysis, independent sample t-test, one-way ANOVA (post-hoc Duncan), Welch analysis (post-hoc Games-Howell), and hierarchical multiple regression analysis. Results: Factors that affected the ability to assess the quality of non-face-to-face lectures were the department, the method of non-face-to-face lectures, the most preferred method for conducting lectures, the level of awareness regarding the quality of face-to-face lecture, and satisfaction level. It has 71.5% explanatory power. Moreover, factors that influenced the satisfaction level of non-face-to-face lectures included the department, grade, the highest satisfied non-face-to-face teaching method, the most effective theoretical non-face-to-face teaching method, the most preferred teaching methods, and the ability to assess quality of face-to-face lectures. It has 46.8% explanatory power. Conclusion: Non-face-to-face classes should be designed and developed for web-based programs to improve the motivation and achievement level of the students and encourage interaction between the professors and students. Our findings suggest that educators should strive to achieve optimal educational effects by efficiently combining face-to-face and non-face-to-face lectures.

• 한국노년학
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• v.28 no.4
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• pp.1213-1225
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• 2008

The purpose of this study was to determine psychosocial variables of exercise behaviors for old adults. A major research problem identified through theory of planned behavior and it's empirical data: Do cognitive-social variables(health risk perception, self-efficacy, group conformity, exercise attitude) significantly mediate exercise behaviors(intention, action, maintenance)? A total of 453 older adults above 65 years(171 males and 282 females) who were enrolled in various classes were randomly selected at adults centers in Seoul. Participants completed a battery of questionnaires including the psycho-social variables(health risk perception, self-efficacy, group conformity, exercise attitude) and exercise behaviors(intention, action, maintenance). The results of statistical procedures(e.g., hierarchical multiple regression) indicated self-efficacy and exercise attitude significantly predicted exercise intentions of older adults. Exercise intention was a significant predictor of action, and action was a significant predictor of exercise maintenance. In discussion, various psycho-social mechanisms were provided to interpret the results of this study, and future directions were suggested.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.49-54
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• 2021

With the recent development of smart healthcare technology, interest in daily diseases is increasing. However, healthcare data has an imbalance between positive and negative data. This is caused by the difficulty of collecting data because there are relatively many people who are not patients compared to patients with certain diseases. Data imbalances need to be adjusted because they affect performance in ongoing learning during disease prediction and analysis. Therefore, in this paper, We replace missing values through multiple imputation in detection models to determine whether they are prevalent or not, and resolve data imbalances through over-sampling. Based on AutoML using preprocessed data, We generate several models and select top 3 models to generate ensemble models.

• Journal of Information Technology Services
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• v.19 no.6
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• pp.15-29
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• 2020

Facing the era of intelligence, the demands for changes of e-Government system appears to be rising upon the development of AI, VR, IoT and other new technologies. However, it also comes with the increasing possibility of mobile digital divide among regions, ethnicities and social classes. As the e-Government Service is only available for specific groups, the national government should proactively build an information environment to promote the convenient access and use of e-Government Service comprehensively by all the people. In the light of the sociodemographic characteristics, this study tests whether the difference is statistically significant involving the mobile digital divide between different groups with the analysis of variance, while determining the relationship between the mobile digital divide and the usage intention of e-Government Service through multiple regression analysis. The main findings of this study are as follows. First, there are differences and statistical significance between groups of different ethnicities and regions on accessibility with electronic products and networks. Second, there are obvious differences and statistical significance between groups of different ages, educational levels and ethnicities on the competency and usability of electronic products and networks. Third, the accessibility to electronic products and networks has no effect on the usage intention of e-Government Service, while the competency and usability of electronic products and networks have a strong positive impact on the usage intention of e-Government Service. The author hopes that the research findings of this paper can provide reference suggestions and opinions for bridging the digital divide among regions in China and promoting the popularization of the e-Government Service.

• Journal of Forest and Environmental Science
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• v.37 no.2
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• pp.91-103
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• 2021

We conducted an analysis of agroforestry system efficiency to conserve biodiversity in the Mbalmayo Forest Reserve (MFR) between March 2018 and June 2018. A synthesis of forest fragmentation data observed on multiple strata and scale satellite imageries over 31 years, between 1987 and 2018 as well as, the use of both a floristic and a faunal surveys, revealed that although 29.28% of natural forests was fragmented and converted to agroforests landscapes, banana and cocoa based agroforest appeared to perform the most relevant records in carbon storage and to attract wild terrestrial and avifauna. Analysis of NDVI, NDWI and Iron Oxyde helped monitor the vegetation cover of the reserve, and differentiate natural and fragmented classes, majority of conserved forest wetlands and agroforestry systems, and a minority of natural dryland forest. Further analysis also revealed significant correlations between NDVI and Shannon Index, and between NDVI and carbon stock. Based on the NDVI value and the equation Y=3.827×X-1.587 (where Y for the carbon stocks and X for NDVI value), we estimated the total carbon stock of the forest reserve at about 99557.6 tonnes, and its mean value at about 8.491 tons/ha. Nevertheless, environmental efforts to sustainably manage agroforestry landscape appear to be a relevant key to conserve wild biodiversity and mitigate climate change at the level of the Mbalmayo Forest Reserve. If anthropogenic activities have deeply changed the reserve's natural landscape, reduced its carbon sequestration performance, and wildlife conservation status, forest wetlands appear to remain its most conserved places and the best refuge for wild fauna still occurring in diverse strata of the MFR.

• Journal of Physiology & Pathology in Korean Medicine
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• v.35 no.5
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• pp.162-168
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• 2021

This study was conducted to investigate the current status of online classes and evaluations during the COVID-19 pandemic and the satisfaction of students attending the College of Korean Medicine. A survey was conducted with students enrolled in Dongguk University's College of Korean Medicine. The questionnaire was divided into four areas asking about online lectures, laboratory practice, clinical practice, and evaluation experience. The items were composed of multiple-choice, a 5-point scale, and subjective type. After distributing the Google form address through SNS and LMS, only those who agreed to the questionnaire were responded anonymously. 149 out of 457 enrolled students responded. 98.7% of students experienced online lectures, and more frequently experienced real-time online lectures (98.6%) than recorded lectures (43.5%). Overall satisfaction with online lectures was 3.99 on average. 80.5% of the students experienced the online experiment and practice class, and the overall satisfaction with it was 3.29 on average. 1.3% of students experienced online clinical practice. 86.6% of students experienced online evaluation, and when asked about the fairness of the test, the average score was 3.99. Satisfaction with online lectures and evaluations is generally high, so it is expected to be used as an effective learning tool in the future. However, it seems that facility improvement and technical training of instructors are necessary. In experimental and practical education, the satisfaction level is lower than that of online lectures, so it seems necessary to develop a new online program and to prepare a safe offline education system.

• Journal of Korean Dental Hygiene Science
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• v.4 no.2
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• pp.53-65
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• 2021

Background: To survey and analyze awareness and recognition during a non-face-to-face lecture, and satisfaction with among dental technology students. Methods: Total 179 undergraduates were surveyed from the Department of Dental Technology. Frequency analysis, cross analysis, independent sample t-test, correlation analysis, and multiple regression analysis were used for analyzing statistics. Results: Overall satisfaction with the non-face-to-face lecture was the highest (p=.037) while watching a recorded lecture in the theory curriculum subject. In the case of practical subjects, satisfaction with face-to-face lectures appeared to be higher (p=.039) compared to non-face-to-face lectures. Factors influencing the recognition of non-face-to-face lecture quality included awareness of a place to conduct a class and of face-to-face delivered lecture quality, satisfaction with face-to-face lecture, and satisfaction with non-face-to-face lecture. Factors affecting satisfaction with a non-face-to-face lecture included a place to conduct a class, the most effective theory non-face-to-face class method, the method of having been experienced the most among non-face-to-face lecture methods, and the recognition of non-face-to-face lecture quality. Conclusions: Future educational environment should include combined face-to-face and non-face-to-face lectures. An efficient educational indicator will be needed to evaluate learners' assessments and opinions about online classes, followed by its application to teaching methods.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.193-202
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• 2022

The classification of hyperspectral imagery (HSI) is essential in the surface of earth observation. Due to the continuous large number of bands, HSI data provide rich information about the object of study; however, it suffers from the curse of dimensionality. Dimensionality reduction is an essential aspect of Machine learning classification. The algorithms based on feature extraction can overcome the data dimensionality issue, thereby allowing the classifiers to utilize comprehensive models to reduce computational costs. This paper assesses and compares two HSI classification techniques. The first is based on the Joint Spatial-Spectral Stacked Autoencoder (JSSSA) method, the second is based on a shallow Artificial Neural Network (SNN), and the third is used the SVM model. The performance of the JSSSA technique is better than the SNN classification technique based on the overall accuracy and Kappa coefficient values. We observed that the JSSSA based method surpasses the SNN technique with an overall accuracy of 96.13% and Kappa coefficient value of 0.95. SNN also achieved a good accuracy of 92.40% and a Kappa coefficient value of 0.90, and SVM achieved an accuracy of 82.87%. The current study suggests that both JSSSA and SNN based techniques prove to be efficient methods for hyperspectral classification of snow features. This work classified the labeled/ground-truth datasets of snow in multiple classes. The labeled/ground-truth data can be valuable for applying deep neural networks such as CNN, hybrid CNN, RNN for glaciology, and snow-related hazard applications.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.257-263
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• 2021

This study analyzed the factors affecting online class satisfaction and tried to use it as basic data for more effective class management. The survey was collected on 208 students majoring in dental laboratory technology in Jeonbuk and Chungbuk. The data were analyzed by reliability analysis, descriptive stastistics, compare means(t-test, one-way ANOVA), Pearson's correlation coefficient and stepwies multiple regression analysis(SPSS program). The analysis results showed that expected benefit of time was 3.87, expected benefit of learning was 3.30, technology familiarity was 3.40, and class satisfaction was 3.21. The most influential factor in class satisfaction was technology familiarity. In order to increase the online class satisfaction, it is necessary to build a learning environment to improve the ability to learning tools used in classes and technology familiarity with the online class system.