• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.2
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• pp.49-59
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• 2022

This study aims to understand the effects of perceived usefulness, perceived ease, and expected matching on user satisfaction and continuous use intention for the learning management system (LMS). To this end, an online survey was conducted on K University students located in Chungcheongbuk-do, and 488 data were analyzed and utilized. First, it was found that the expected match of the learning management system had an effect on perceived usefulness and perceived ease. Second, it was found that perceived usefulness, perceived ease, and expected matching had an effect on user satisfaction. Perceived usefulness, user satisfaction and perceived ease of use were found to have an effect on the intention to continue using. It can be seen that the improvement of the quality of the university education system has an effect on the improvement of learners' learning effects and satisfaction. Accordingly, it is necessary to seek various ways to continuously manage the quality of the learning management system.

• Journal of Information Science Theory and Practice
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• v.10 no.3
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• pp.24-39
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• 2022

Online learning is becoming ubiquitous worldwide because of its accessibility anytime and from anywhere. However, it cannot be successfully implemented without understanding constructs that may affect its adoption. Unlike previous literature, this research extends the Unified Theory of Acceptance and Use of Technology with three well-known theories, namely compatibility, online self-efficacy, and knowledge sharing and acquisition to examine online learning adoption. A total of 264 higher education students took part in this research. Partial Least Squares-Structural Equation Modeling was used to evaluate the proposed theoretical model. The findings suggested that performance expectancy and compatibility were significant predictors of behavioral intention, whereas behavioral intention, facilitating conditions, and compatibility had a significant and direct effect on online learning's actual use. The results also showed that knowledge acquisition, knowledge sharing, and online self-efficacy were determinates of performance expectancy. Finally, online self-efficacy was a predictor of effort expectancy. The proposed model achieved a high fit and explained 47.7%, 75.1%, 76.1%, and 71.8% of the variance of effort expectancy, performance expectancy, behavioral intention, and online learning actual use, respectively. This study has many theoretical and practical implications that have been discussed for further research.

• Journal of Korean language education
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• v.29 no.4
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• pp.65-92
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• 2018

This study explored how a particular social media can be used to supplement elementary-level Korean language course in the US public university. The researchers administered a survey measuring students' patterns and habits of social media use. Based on the survey results, researchers designed six different types of learning materials and uploaded them regularly to Instagram throughout the semester. At the end of the semester, a survey was conducted to find out students' satisfactory level. From the 44 students' responses, the study found out that using Instagram 1) is more accessible to students than any other learning management system, 2) is fun and students are willing to participate, 3) increased the target language exposure and authentic language use, 4) increased interaction between teachers, students and even other native speakers, and 5) is helpful to improve listening and other language skills. The study closes with the suggestion for further experimental studies.

• English Language & Literature Teaching
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• v.15 no.4
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• pp.37-54
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• 2009

This study investigated vocabulary learning strategies used by EFL middle school learners in Korea and examined the relationship between the middle school learners' vocabulary learning strategy (VLS) use and their vocabulary proficiency level. One hundred and forty-one students in a public middle school participated in the study and the data for this study were collected from a vocabulary learning strategy questionnaire and a vocabulary proficiency test. Based on the result of the vocabulary proficiency test, the participants were divided into three proficiency groups: high-, mid- and low- level proficiency groups. The overall findings of the study revealed that the participants used cognitive strategies most frequently and social strategies least frequently. The most frequently used individual strategies were 'using a bilingual dictionary,' 'studying the sound of a word' and 'practicing words through verbal repetition.' The least frequently used ones were 'interacting with native speakers' and 'studying or practicing the meaning of a word in a group.' The research results also showed that the vocabulary proficiency level has a significant influence on the vocabulary strategy use. The more proficient learners used vocabulary learning strategies more actively. More specifically, the high proficiency level group used metacognitive strategies the most. The middle and low proficiency groups used cognitive strategies the most. It is suggested that language teachers should facilitate the vocabulary learning process by helping learners develop appropriate strategies.

• Journal of the Korean School Mathematics Society
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• v.13 no.1
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• pp.89-104
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• 2010

In a rapidly changing and increasingly technological society. the use of technology should not be disregarded in issues of learning algebra. The use of technology in learning algebra raises many learning and pedagogical issues. In this article, previous research on the use of technology in learning algebra is synthesized on the basis of the four issues: conceptual understanding, skills, instrumental genesis, and transparency. Finally, suggestions for future research into technological pedagogical content knowledge (TPCK) are made.

• Korean Journal of Radiology
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• v.22 no.12
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• pp.2073-2081
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• 2021

Deep learning-based applications have great potential to enhance the quality of medical services. The power of deep learning depends on open databases and innovation. Radiologists can act as important mediators between deep learning and medicine by simultaneously playing pioneering and gatekeeping roles. The application of deep learning technology in medicine is sometimes restricted by ethical or legal issues, including patient privacy and confidentiality, data ownership, and limitations in patient agreement. In this paper, we present an open platform, MI2RLNet, for sharing source code and various pre-trained weights for models to use in downstream tasks, including education, application, and transfer learning, to encourage deep learning research in radiology. In addition, we describe how to use this open platform in the GitHub environment. Our source code and models may contribute to further deep learning research in radiology, which may facilitate applications in medicine and healthcare, especially in medical imaging, in the near future. All code is available at https://github.com/mi2rl/MI2RLNet.

• The Mathematical Education
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• v.56 no.2
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• pp.193-212
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• 2017

This study focuses on cuisenaire rods that can be used when teaching fractions to elementary school students. First of all, this study critically examines the use of cuisenaire rods in learning of fraction proposed by various researches. Then, based on this review, this study explores in detail the use of cuisenaire rods in teachers' manuals developed from the revised curriculum by 2009 and in lessons related to fraction. The results of this study show that there are subtle differences in how to use cuisenaire rods in learning fractions and these subtle differences have a significant impact on students' understanding of the fractions. Therefore, the teachers should be able to accurately grasp the differences and utilize appropriate methods for teaching purpose. The followings are some of the implications for teachers or textbook developers when using cuisenaire rods in fraction learning: First, we should use cuisenaire rods in ways that can fully exploit the interpretations of the fraction as a part-whole and the fraction as a ratio. Second, we should focus on quantitative reasoning with unit to determine what each cuisenaire rod refers to. Third, it is necessary to take a more careful and sensitive approach to the use of cuisenaire rods. Teachers and textbook developers should constantly explore ways to make good use of mathematical manipulatives to help students understand conceptually in fractional learning. Furthermore, when teaching various mathematical topics using different manipulatives, I expect that there will be sufficient discussions and specific studies on how to use each of these manipulatives.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.1
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• pp.55-67
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• 2015

This study examines innovation resistance to smart learning, an emerging innovative technology for startups and corporate ventures in the education market. The study explores whether the relative advantage, compatibility and complexity of an innovation, attitudes toward existing learning method(s), and perceived self-efficacy significantly affect innovation resistance. Additionally, the effects of such innovation resistance on future use and the moderating effect according to demographic characteristics are examined. The results of the analysis using a structural equation model showed that all the factors considered (except relative advantage) affects innovation resistance, innovation resistance significantly affects intention to use.

• Journal of the Korean Society for information Management
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• v.20 no.4 s.50
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• pp.135-158
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• 2003

The Purpose of this study is to investigate how information use contributes to learning. Conducted as part of a larger study, this study focuses on learning by analyzing students' use of cognitive skills during the Process of using information. Within the broad methodological framework of qualitative research in constructivist paradigm (Guba and Lincoln, 1998), the study applied the revised Bloom's taxonomy (Anderson and Krathwohl, 2000) as a particular framework to understand the Phenomenon. Participants included 21 high school juniors in an honors' class of persuasive speech. The study's combinational use of two techniques -concept mapping and individual interview - in a naturalistic setting Proved to be the unique methods for researching the reflection of information use in learning Products. The results revealed that changes in students' understanding occured in four types - simple, analytic, organizational, and holistic changes. The analysis using the revised Bloom's taxonomy showed that a variety of cognitive skills were used during the whole process of information use and that the use of higher levels of cognitive skills is particularly crucial.

• Journal of Korean Society for Quality Management
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• v.52 no.1
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• pp.77-93
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• 2024

Purpose: The purpose of this study is to examine machine learning use cases in manufacturing companies from a digital quality management (DQM) perspective and to analyze and present machine learning research patterns from a quality management perspective. Methods: This study was conducted based on systematic literature review methodology. A comprehensive and systematic review was conducted on manufacturing papers covering the overall quality management process from 2015 to 2022. A total of 3 research questions were established according to the goal of the study, and a total of 5 literature selection criteria were set, based on which approximately 110 research papers were selected. Based on the selected papers, machine learning research patterns according to quality management were analyzed. Results: The results of this study are as follows. Among quality management activities, it can be seen that research on the use of machine learning technology is being most actively conducted in relation to quality defect analysis. It suggests that research on the use of NN-based algorithms is taking place most actively compared to other machine learning methods across quality management activities. Lastly, this study suggests that the unique characteristics of each machine learning algorithm should be considered for efficient and effective quality management in the manufacturing industry. Conclusion: This study is significant in that it presents machine learning research trends from an industrial perspective from a digital quality management perspective and lays the foundation for presenting optimal machine learning algorithms in future quality management activities.