• Journal of Korean Academic Society of Home Health Care Nursing
• /
• v.22 no.1
• /
• pp.88-97
• /
• 2015

Purpose: This study was conducted to identify the effects of a suction care self video-based debriefing-assisted learning in the fundamentals of nursing practice for nursing students on clinical performance, self-efficacy and problem-solving process. Methods: A nonequivalent control group non-synchronized design study was used and included 97 junior nursing students at P University as participants, 48 of whom were assigned to the experimental group, and 49 of whom were assigned to the control group. The outcome measurements were clinical performance for suction care, self-efficacy, and the problem-solving process. Results: The scores of clinical performance were 23.75 in the experimental group who used the materials and 21.55 in the control group, and the difference was statistically significant (p<.000). Self-efficacy was 4.30 in the experimental group and 4.18 in the control group, which was a statistically significant difference (p=.000), and the pre-to-post differences of self-efficacy was statistically significant as well (p<.001). However, there were no significant differences in the pre-to-post differences of the problem-solving process (p<.802). Conclusions: Self video-based debriefing-assisted learning may be more effective in enhancing clinical performance and self-efficacy than that of conventional practice. Whether self-efficacy will contribute to enhanced learning motivation for nursing students needs further examination.

• International Journal of Advanced Culture Technology
• /
• v.8 no.2
• /
• pp.101-108
• /
• 2020

One difficulty in language learning is the training of reading ability. The improvement on this ability directly affects the process and effect of language learning. At the same time, there are numerous difficulties in actual learning and teaching. Depending on current research, there is two ideas that can utilize to enhance the reading efficiency of learners. One is to amend objective factors; the other is to change subjective factors. Compared with the two ideas, idiosyncratic factors are more manipulable and controllable, so it is more valuable to conduct researches on this. But among the many subjective factors, the degree of their effectiveness is not the same, so this article attempts to compare and analyze the driving effects of two important subjective factors (peer-driven and task-driven) on reading performance. The results show that both factors can have a positive impact on reading comprehension, but different in driving effects. The task-driven has obvious short-term effectiveness; while peer-driven needs to establish its long-term effect on the basis of early coordination and cooperation among team members. Therefore, in order to maximize the achievement of learning, it is necessary to combine strengths and avoid weaknesses according to the characteristics of two factors, so as to help learners improve reading ability most efficiently.

• Journal of Advanced Navigation Technology
• /
• v.14 no.6
• /
• pp.874-881
• /
• 2010

A automatic flight control system(AFCS) of UAS needs to control its flight path along target path exactly as adjusts flight coefficient itself depending on static or dynamic changes of airplane's features such as type, size or weight. In this paper, we propose system which tunes control gain autonomously depending on change of airplane's feature in flight as adding MLM(Machine Learning Module) on AFCS. MLM is designed with Linear Regression algorithm and Reinforcement Learning and it includes EvM(Evaluation Module) which evaluates learned control gain from MLM and verified system. This system is tested on beaver FDC simulator and we present its analysed result.

• Journal of Fisheries and Marine Sciences Education
• /
• v.23 no.1
• /
• pp.23-34
• /
• 2011

The primary purpose of this study was to develop a college adjustment program for freshmen through admission officer system that relies less on test scores and on the various talents evaluated by admissions officers. To help these talented students adjust the new life of the university and enhance their gifts, a college adjustment program was developed with their special needs and characteristics. For that, the survey with 57 students and in-depth interviews with 12 students were conducted. The results revealed that the students wanted to learn study skills, self-management, global mind setting, and life vision and goals setting. Most of the students were worried about their grades because they entered the school with their talents and experience in diverse activities not SAT scores. To promote their academic performance, this program consisted of an academic readiness program which complements students' abilities in primary subjects like math, English, and science, and a potential progress program which is peer-group learning communities based on their own interests like global learning communities, creative learning communities, and service-learning communities. This program was suggested in the context of Comprehensive Development Model. To carry out the program systematically, related organizations and colleges should collaborate with each other.

• International Journal of Computer Science & Network Security
• /
• v.21 no.9
• /
• pp.51-62
• /
• 2021

Plant disease is one of the issues that can create losses in the production and economy of the agricultural sector. Early detection of this disease for finding solutions and treatments is still a challenge in the sustainable agriculture field. Currently, image processing techniques and machine learning methods have been applied to detect plant diseases successfully. However, the effectiveness of these methods still needs to be improved, especially in multiclass plant diseases classification. In this paper, a convolutional neural network with a batch normalization-based deep learning approach for classifying plant diseases is used to develop an automatic diagnostic assistance system for leaf diseases. The significance of using deep learning technology is to make the system be end-to-end, automatic, accurate, less expensive, and more convenient to detect plant diseases from their leaves. For evaluating the proposed model, an experiment is conducted on a public dataset contains 20654 images with 15 plant diseases. The experimental validation results on 20% of the dataset showed that the model is able to classify the 15 plant diseases labels with 96.4% testing accuracy and 0.168 testing loss. These results confirmed the applicability and effectiveness of the proposed model for the plant disease detection task.

• Journal of KIBIM
• /
• v.9 no.4
• /
• pp.31-40
• /
• 2019

With Building Information Modeling(BIM) becoming the de facto standard for data sharing in the AEC industry, additional needs have increased to ensure the data integrity of BIM models themselves. Although the Industry Foundation Classes provide an open and neutral data format, its generalized schema leaves it open to data loss and misclassifications This research applied deep learning to automatically classify BIM elements and thus check the integrity of BIM-to-IFC mappings. Multi-view CNN(MVCC) and PointNet, which are two deep learning models customized to learn and classify in 3 dimensional non-euclidean spaces, were used. The analysis was restricted to classifying subtypes of architectural walls. MVCNN resulted in the highest performance, with ACC and F1 score of 0.95 and 0.94. MVCNN unitizes images from multiple perspectives of an element, and was thus able to learn the nuanced differences of wall subtypes. PointNet, on the other hand, lost many of the detailed features as it uses a sample of the point clouds and perceived only the 'skeleton' of the given walls.

• Iberoamérica
• /
• v.23 no.2
• /
• pp.209-241
• /
• 2021

Over the last few years, rural areas in northeastern Mexico have present significant changes in social, economic, and territorial aspects linked to the New Rurality. In this context, winemaking has become one of the most dynamic and growing activities in the regional economy. This emerging development has prompted different forms of appropriation and use of this space, but it also highlights the lack of access to knowledge for wine production due to the lack of formal educational centers. As a result, learning communities enable the development of skills and competencies through non-formal educational practices. The objective of this paper is to analyze the role of learning communities in non-formal educational environments, taking as a case study: a collective of small-scale wine producers in Parras de la Fuente, Coahuila. This research focuses on two perspectives of learning: appropriation and technology transfer, and promotion of Mexican wine culture. The main finding was to demonstrate the importance of including educational processes that respond to the context and needs of the community.

• 한국정보교육학회:학술대회논문집
• /
• 2021.08a
• /
• pp.7-11
• /
• 2021

This study designs block-based machine learning education program using sound data that can be easily applied in elementary schools. The education program designed its goals and directions based on the results of a demand analysis conducted on 70 elementary school teachers in advance according to the ADDIE model. Scratch in Machine Learning for Kids was used for block-based programming, and the education program was designed to discover regularity of data values using sound data, learn the principles of artificial intelligence, and improve computational thinking in the programming process. In a later study, the education program needs to verify what changes there are in attitudes and computational thinking about artificial intelligence.

• Smart Media Journal
• /
• v.12 no.5
• /
• pp.88-101
• /
• 2023

As the definition and role of design changes over time with the times and society, design education needs to update teaching methods to match it. The course design in this study began with an optimisation of the learning model based on previous research and analysis, followed by in-depth interviews, the application of the interview results to the final curriculum design, and finally a questionnaire to verify the positive effects of this teaching model. This teaching model has been applied to teach a pilot class in a university of applied sciences in China. The main characteristics of the course design are Project-Based Learning (PJBL) oriented, team cooperation centric, and an educational model developed based on peer assessment. In every stage of the UI design course, realistic project simulations are adopted, enhancing students' abilities through practical experience, teamwork, and peer assessment. The innovation lies in validating the effectiveness and advantages of this model at every stage of the UI design course, innovating existing teaching methods, optimizing learning models, and combining practice with evaluation. This research found that a project-oriented team course design based on PJBL has a high degree of effectiveness and relevance in each stage of the UI design course, significantly improving students' overall competence. It is expected that the results of this study can be applied in various ways to the course design of the courses that similar to design majors.

• Journal of Digital Convergence
• /
• v.18 no.5
• /
• pp.1-8
• /
• 2020

This study analyzed the different needs between the after-school programs of elementary schools in metropolitan and non-metropolitan areas to understand the areas that need addressing to meet with the requisites of the programs. To this end, this study conducted a survey among teachers with experience in after-school management (n=233), and the needs and performance recognized by teachers were analyzed in the IPA model matrix. To sum up the results, 'Online educational infrastructure', 'Efficient administrative operation', and 'Supply of professional after-school instructors' were identified as the prior needs in metropolitan area. On the other hand, non-metropolitan area, 'Supply of professional after-school instructors', 'Quality educational contents', and 'Online educational infrastructure' were identified as the prior requisites to be addressed. Based on research findings, the study suggested implications in developing and implementing related policies. Research findings will be expected to refer as baseline data for activating after-school online program operations and improving its programs to meet with the different needs of regions.