• Korean Journal of Child Studies
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• v.25 no.4
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• pp.163-175
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• 2004

In this study, 63 university seniors majoring Child Studies were in an 8-week Web Based Instruction (WBI) program. Student characteristics of learning motivation, self-regulatory learning strategy, and learning style (Kolb, 1985) were the independent variables. Learning effects as dependent variables were measured by paper test and work assessment. Spearman's $\rho$ was calculated and tests of rank order difference were used for the data analysis. Results showed that learning motivation and self-regulatory learning strategy had meaningful positive relations with learning effects on the paper test score. Learning effects showed differences by learning style. These findings indicated that the learner's characteristics should be considered in the design and development of more effective WBI environments.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.11a
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• pp.186-187
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• 2021

Education in Korean universities is rapidly expanding to online education due to COVID-19. In response to such changes, this study proposed a means of improving the learning management system of Korean universities and analyzed the effects of using the system. The important results of this study are as follows: the learning management system was composed of 'pre-class learning,' 'team activity,' and 'participation learning' to support team-based learning. The effects that the users (instructors, learners) can obtain by adopting team-based learning and using the system were analyzed. The study concludes that for instructors, teaching work may be alleviated. For learners, it was demonstrated that they could more easily access and use data required for their education.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.212-222
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• 2021

Multiple waves of COVID-19 highlighted one crucial aspect of this pandemic worldwide that factors affecting the spread of COVID-19 infection are evolving based on various regional and local practices and events. The introduction of vaccines since early 2021 is expected to significantly control and reduce the cases. However, virus mutations and its new variant has challenged these expectations. Several countries, which contained the COVID-19 pandemic successfully in the first wave, failed to repeat the same in the second and third waves. This work focuses on COVID-19 pandemic control and management in Saudi Arabia. This work aims to predict new cases using deep learning using various important factors. The proposed method is called Deep Learning and Dynamic Weighing-based (DLDW) COVID-19 cases prediction method. Special consideration has been given to the evolving factors that are responsible for recent surges in the pandemic. For this purpose, two weights are assigned to data instance which are based on feature importance and dynamic weight-based time. Older data is given fewer weights and vice-versa. Feature selection identifies the factors affecting the rate of new cases evolved over the period. The DLDW method produced 80.39% prediction accuracy, 6.54%, 9.15%, and 7.19% higher than the three other classifiers, Deep learning (DL), Random Forest (RF), and Gradient Boosting Machine (GBM). Further in Saudi Arabia, our study implicitly concluded that lockdowns, vaccination, and self-aware restricted mobility of residents are effective tools in controlling and managing the COVID-19 pandemic.

• Journal of Information Processing Systems
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• v.6 no.4
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• pp.609-620
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• 2010

In order to provide a tailored education for learners within the ubiquitous environment, it is critical to undertake an analysis of the learning activities of learners. For this purpose, SCORM (Sharable Contents Object Reference Model), IMS LD (Instructional Management System Learning Design) and other standards provide learning design support functions, such as, progress checks. However, in order to apply these types of standards, contents packaging is required, and due to the complicated standard dimensions, the facilitation level is lower than the work volume when developing the contents and this requires additional work when revision becomes necessary. In addition, since the learning results are managed by the server there is the problem of the OS being unable to save data when the network is cut off. In this study, a system is realized to manage the actions of learners through the event interception of a web-browser by using event hooking. Through this technique, all HTMLbased contents can be facilitated again without additional work and saving and analysis of learning results are available to improve the problems following the application of standards. Furthermore, the ubiquitous learning environment can be supported by tracking down learning results when the network is cut off.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4214-4230
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• 2020

This paper introduces a pilot allocation scheme for massive MIMO systems based on deep convolutional neural network (CNN) learning. This work is an extension of a prior work on the basic deep learning framework of the pilot assignment problem, the application of which to a high-user density nature is difficult owing to the factorial increase in both input features and output layers. To solve this problem, by adopting the advantages of CNN in learning image data, we design input features that represent users' locations in all the cells as image data with a two-dimensional fixed-size matrix. Furthermore, using a sorting mechanism for applying proper rule, we construct output layers with a linear space complexity according to the number of users. We also develop a theoretical framework for the network capacity model of the massive MIMO systems and apply it to the training process. Finally, we implement the proposed deep CNN-based pilot assignment scheme using a commercial vanilla CNN, which takes into account shift invariant characteristics. Through extensive simulation, we demonstrate that the proposed work realizes about a 98% theoretical upper-bound performance and an elapsed time of 0.842 ms with low complexity in the case of a high-user-density condition.

• Educational Technology International
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• v.11 no.2
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• pp.105-121
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• 2010

Collaborative learning encourages the use of high-level cognitive strategies, critical thinking, and interpersonal relationships. Despite these advantages, most instructors reveal the difficulties of using project-based collaborative learning; a common problem is the failure of the group to work effectively together. Thus, this study attempted to provide practical advice on group composition with self-regulation. In a college course, 31 groups with 129 students were asked to discuss and prepare the final presentation material and present it together as a collaborative work. All students' self-regulation skills were measured at the beginning of the semester, and the collective self-regulation was computed as an average of the individual scores of each group. The results of regression analysis indicate that the group's collective self-regulation shows a highly significant positive effect on group performance and satisfaction, as self-regulation predicts individual academic performance. The results also show that there is a significant positive relationship between students' self-regulation and participation in group work.

• Journal of Practical Engineering Education
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• v.14 no.1
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• pp.179-194
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• 2022

After the work-study combination PBL method was first introduced into the P-Tech type in 2018, it was introduced into the degree-linked high-skilled professional course in operation as a pilot project in 2020, and ever since each department has reorganized the standard completion system to meet the PBL operation regulations and developed and operated PBL-based learning and training courses accordingly. With the expansion of the work-study combination PBL in 2021, the operating regulations were revised more elaborately. This paper examined the characteristics of the work-study combination PBL, the PBL operation regulations for each degree-linked high-skilled professional course, and the most recently implemented PBL operation regulations in detail through literature research. Based on this research, it introduced the development process and the result of the PBL-based standard completion system by the IT Convergence SW Engineering Department of KOREATECH and the result of the survey conducted to verify the suitability of the standard completion system after an operation and presented the challenges and improvements required for the degree-linked high-skilled professional course in relation to the changing operation regulations for the work-study combination PBL. This study is expected to provide universities with a reference to the development of training courses to smoothly apply the work-study combination PBL. It is also expected to contribute to the establishment and steady expansion of a unique PBL system that reflects the characteristics of work-study combination by presenting discourses on how the work-study combination PBL should develop, including high-skilled professional courses.

• Journal of Convergence for Information Technology
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• v.11 no.8
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• pp.151-159
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• 2021

The purpose of this study was to examine the mediating effects of Positive Psychological Capital on the relationship between Small Business Enterpreneur's Learning Goal Orientation and Work Engagement. In order to achieve the purpose of research, the survey results of 300 small business Enterpreneurs who participated in the K-BIZ's Small Business Enterpreneurs Support Program were used for analysis. The collected data were analyzed using frequency analysis, reliability analysis, confirmatory factor analysis, descriptive statistical analysis, correlation analysis and structural equation model. The results of this study were as follows: First, learning goal orientation of small business enterpreneurs had positive effect on positive psychological capital. Second, positive psychological capital of small business enterpreneurs had positive effect on work engagement. Third, positive psychological capital of small business enterpreneurs had full mediating effect on the relationship between learning goal orientation and work engagement. Based upon these results, several suggestions were suggested to promote small business enterpreneurs' learning goal orientation, work engagement, and positive psychological capital.

• Educational Technology International
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• v.19 no.2
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• pp.229-254
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• 2018

Universities in Korea have driven universities' new attempts to adopt more learner-centered and active learning in English. Problem-based Learning (PBL) is one of the well-known constructive teaching and learning methodologies in higher education. Our research goal was to design and develop the optimal PBL practices for a college physics course taught in English to promote learning and course satisfaction. For four semesters, we have tried and adjusted PBL components, and looked at the trend of the exam scores and group work achievement in each semester. We found that the number of problems and the duration of problem solving are the critical factors that influence the effect of PBL in a college physics course taught in English by going through iterative implementation. The iterative process of applying, designing, and constructing PBL to physics classes was meaningful not only in that we have found the optimal PBL model for learning a college physics course, but also in that we have been reflecting on the continuous interaction with learners during the course.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.1-6
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• 2022

Teaching and learning are one of the major issues during this pandemic (COVID-19). Since the pandemic started, there are many changes in teaching and learning styles as everything related to studies started online. Game-Based Learning has got remarkable importance in the educational system and pedagogy as an effective way of increasing student inspiration and engagement. In this field, most of the work has been carried out in digital games. This research uses an Animated Game-Based Learning design in enhancing student engagement and perception of learning. In teaching Computer Science (CS) concepts in higher education, to enhance the pedagogy activities in CS concepts, more specifically the concepts of "Data Structures (DS)" i.e., Array, Stack, and Queue concepts are focused. This study aims to observe the difference in students' learning with the use of different learning methods i.e., the traditional learning (TL) method and the Animated Game-Based Learning (AGBL) Method. The experimental results show that learning DS concepts has been improved by the AGBL method as compared to the TL method.