• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.141-146
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• 2022

In modern educational practices, the issue of dependence on the experience of using multimedia by students and the adoption of technologies in education, the perception of their benefits and effectiveness in blended learning is little covered. The purpose of the academic paper lies in assessing the audiovisual context of multimedia technologies, its acceptance by students in practice on the example of using video lectures in blended learning. The methodology is based on an online survey of 120 students of Ukrainian universities who have assessed the experience level in using video lectures, as well as the constructs as follows: Technology Characteristics, Fit, Perceived Usefulness, Perceived Ease of Use, Attitude, Intention to Use, Actual Use. The results show that the majority of students use video lectures to a certain extent in their training (20,8% have used technology to a certain extent, 49,2% have often used technology in training, 20% are regular users of technology). It has been revealed that most students agree with the relevance of video lectures, the accuracy of lectures, the brevity of lectures, the clarity of lectures, as well as the high quality of lecture videos. It has been estimated that 42,5% believe that lecture videos are an effective tool towards supporting students in hybrid learning. 26,7% of students consider video lectures to be appropriate technologies for online / hybrid courses. In general, 37,5% of respondents find video lectures useful; however, 35,0% do not agree with this statement. 83,3% of students have rated the high level of ease of access to video. In total, 95% of students find lecture videos easy to use. In general, positive attitude of students to video lectures has been revealed.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.4
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• pp.55-65
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• 2022

The purpose of this study is to develop online educational contents and verify its effectiveness in order to strengthen the learning capabilities of college students. The theme of mind map online education contents is a mind map series for effective learning arrangement, and has been developed into a total of six contents. Each contents consisted of 20-30 minutes, and the details consisted of the concept, principle, learning case, how to write a mind map, and how to use a digital mind map. The results of the study are as follows. First, it was confirmed that the higher thinking ability of college students who took the mind map online education contents was improved. Second, it was confirmed that the self-directed learning attitude of college students improved after taking the mind map online education contents. Third, the reason why students' higher thinking ability and self-directed learning attitudes improved in this study is that they were developed in consideration of the composition of contents and appropriate video time. Therefore, in order to increase the effectiveness of online educational contents, it is necessary to examine specific cases using concepts from conceptual approaches to specific topics, and to faithfully reflect the procedure in which each learner can actually use the concept.

• Computers and Concrete
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• v.32 no.3
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• pp.263-286
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• 2023

Experimenting with concrete to determine its compressive and tensile strengths is a laborious and time-consuming operation that requires a lot of attention to detail. Researchers from all around the world have spent the better part of the last several decades attempting to use machine learning algorithms to make accurate predictions about the technical qualities of various kinds of concrete. The research that is currently available on estimating the strength of concrete draws attention to the applicability and precision of the various machine learning techniques. This article provides a summary of the research that has previously been conducted on estimating the strength of concrete by making use of a variety of different machine learning methods. In this work, a classification of the existing body of research literature is presented, with the classification being based on the machine learning technique used by the researchers. The present review work will open the horizon for the researchers working on the machine learning based prediction of the compressive strength of concrete by providing the recommendations and benefits and drawbacks associated with each model as determining the compressive strength of concrete practically is a laborious and time-consuming task.

• Journal of The Korean Association of Information Education
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• v.20 no.1
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• pp.1-12
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• 2016

The purpose of this study is to investigate and analyze the elementary teachers' use of smart-phone applications (apps) in teaching-learning activities. The range of study includes the current usage patterns of apps in teaching-learning activities, elementary school teachers' understanding about apps usage in their classroom and providing the guideline about how to use apps for each subject in the classroom. We surveyed 100 elementary school teachers who are interested in smart education in Seoul. These teachers have an experience of working in a smart research school or have a computer-related master's degree. We expect that the result of the study will helpful for the elementary school teachers to design teaching materials using apps.

• Cross-Cultural Studies
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• v.24
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• pp.170-183
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• 2011

This study explored how a Chinese college student who previously had not reached a threshold level of Korean proficiency used L1 (Chinese) and L2 (English) as a tool to socialize into Korean (L3) culture of learning over the course of study. From a perspective of language socialization, this study examined the cross-linguistic influence of L1 and L2 on the L3 acquisition process by tracing an approach to language learning and practices taken by the Chinese student as a case study. Data were collected through three methods; interview protocols, various types of written texts, and observations. The results showed that the student used English as a means to negotiate difficulties and expertise by empowering her L2 exposure during the classroom practices. Her ways of using L2 in oral practices could be characterized as the 'Inverse U-shape' pattern, under which she increased L2 exposure at the early stage of the study and shifted the intermediate language to L3 at the later stage of the study. When it comes to the language use in written practices, the sequence of "L2-L1-L3" use gradually changed to the "L2-L3" sequence over time, signifying the importance of interaction between L2 and L3. However, the use of her native language (L1) in a Korean-speaking classroom was limited to a certain aspect of literacy practices (i.e., vocabulary learning or translation). This study argues for L2 communication channel in cross-cultural classrooms as a key factor to determine sustainable learning growth.

• Journal of the Korean Society of Radiology
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• v.11 no.4
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• pp.279-287
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• 2017

The purpose of this was to study and analyze smart learning the self directed learning, self efficacy, learning satisfaction about department of radiology in a college. For this study total students 74 in 2classes were surveyed at the end of semester. Compared to use smartphones one group and not use smartphones one group for study in a class. The research data was analyzed using SPSS also self directed learning, self learning efficacy, learning satisfaction analyzed t-test, general character was analyzed two group(one : Used smart learning other : not Used smart learning) ${\chi}^2-test$. First, Used smart learning group is more higher than not Used smart learning group in a self learning efficacy, self directed learning, learning satisfaction. Second, during the smart learning classes a students appeared a positive response. Suggest to change a paradigm in a radiology classes so we have to improve a teaching skills this solution recommend is two way communication. In conclusion, smart learning applied for classes of college is meaningful as a new teaching, which can be change gradually learning satisfaction by teaching methods.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.420-426
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• 2022

Breast cancer is among the cancers that may be healed as the disease diagnosed at early times before it is distributed through all the areas of the body. The Automatic Analysis of Diagnostic Tests (AAT) is an automated assistance for physicians that can deliver reliable findings to analyze the critically endangered diseases. Deep learning, a family of machine learning methods, has grown at an astonishing pace in recent years. It is used to search and render diagnoses in fields from banking to medicine to machine learning. We attempt to create a deep learning algorithm that can reliably diagnose the breast cancer in the mammogram. We want the algorithm to identify it as cancer, or this image is not cancer, allowing use of a full testing dataset of either strong clinical annotations in training data or the cancer status only, in which a few images of either cancers or noncancer were annotated. Even with this technique, the photographs would be annotated with the condition; an optional portion of the annotated image will then act as the mark. The final stage of the suggested system doesn't need any based labels to be accessible during model training. Furthermore, the results of the review process suggest that deep learning approaches have surpassed the extent of the level of state-of-of-the-the-the-art in tumor identification, feature extraction, and classification. in these three ways, the paper explains why learning algorithms were applied: train the network from scratch, transplanting certain deep learning concepts and constraints into a network, and (another way) reducing the amount of parameters in the trained nets, are two functions that help expand the scope of the networks. Researchers in economically developing countries have applied deep learning imaging devices to cancer detection; on the other hand, cancer chances have gone through the roof in Africa. Convolutional Neural Network (CNN) is a sort of deep learning that can aid you with a variety of other activities, such as speech recognition, image recognition, and classification. To accomplish this goal in this article, we will use CNN to categorize and identify breast cancer photographs from the available databases from the US Centers for Disease Control and Prevention.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.9-17
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• 2021

This is a descriptive investigative study which attempts to confirm the mediating effect of learning motivation in the relationship between self-directed learning, learning commitment, and learning persistence intention of university students in an online learning environment. The questionnaires were randomly distributed online and the agreed questionnaires were retrieved, with a total of 338 copies used for analysis. The following is the summary of the findings. First, there were significant differences in learning persistence intention according to general characteristics depending on age, major, part-time job, and academic level. Second, the results showed a positive correlation between self-directed learning, learning commitment, learning motivation, and learning persistence intentions of the subjects were statistically significant. Third, after checking the mediating effect of learning motivation in relation to self-directed learning, learning commitment and learning motivation, the learning motivation has a partial mediating effect on learning and 23% explanatory power, and the learning commitment was found to have a complete mediating effect on the impact of learning motivation on learning intentions with 21% explanatory power. Based on these results, it is necessary to provide a more diverse educational environment, such as operating a motivation semester program that can improve learning motivations along with learning commitment, and the use of a variety of contents that can focus the learner's interest or attention.

• Journal of information and communication convergence engineering
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• v.14 no.2
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• pp.97-105
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• 2016

With the increasing demand for interoperability among existing learning resource systems in order to enable the sharing of learning resources, such resources need to be annotated with ontologies that use different metadata standards. These different ontologies must be reconciled through ontology mediation, so as to cope with information heterogeneity problems, such as semantic and structural conflicts. In this paper, we propose an ontology-mapping technique using Semantic Web Rule Language (SWRL) to generate semantic mapping rules that integrate learning resources from different systems and that cope with semantic and structural conflicts. Reasoning rules are defined to support a semantic search for heterogeneous learning resources, which are deduced by rule-based inference. Experimental results demonstrate that the proposed approach enables the integration of learning resources originating from multiple sources and helps users to search across heterogeneous learning resource systems.

• Perspectives in Nursing Science
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• v.7 no.1
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• pp.36-42
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• 2010

Purpose: This study was done to identify the preferences for learning style and the degree of self-directed learning and influencing factors on it among nursing students working on a Bachelor of Science in a nursing program at Suwon. Methods: The study sample included 156 nursing students. A self-report questionnaire was used to assess the data. The data was analyzed using the SPSS/WIN program for descriptive and inferential statistics. Results: Most of the students preferred lectures rather than discussion or team projects as a teaching method. Students preferred deliberating, sensing, and the use of visuals for their learning style. In addition, they favored sequential learning over comprehensive learning. Self directed learning had better outcomes in 3rd and 4th year students than 1st or 2nd year students. Additionally, active learners and high achievers who had a good GPA showed higher self directed learning than the others. Conclusion: In order to maximize students' self-directed learning, study guidance will be necessary for freshmen and for some who experience difficulties in studying nursing courses. Nursing faculty members should pay close attention to facilitate student's self directed learning, and encourage more discussions in the classes.