• Educational Technology International
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• v.6 no.1
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• pp.81-101
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• 2005

Campus-based universities have provided face-to-face instruction traditionally. But recently, it is becoming a trend that they provide blended learning which combines e-learning and f2f instruction. Therefore, traditional university has been installing the ICT related convenience for the faculty and students to use easily to their classes. The purpose of this study is to develop quality indicators of ICT-related support for proper blended learning in traditional campus-based universities. This indicators are used for measuring the quality of ICT-related services at university level for quality education. To this end, first, we reviewed literature about quality indicators of university evaluation and e-learning. Second,we did case study. We selected and analyzed one university for a case, And we identified what elements are perceived important to faculty for more efficient use of technology to their class. Third, we summarized all this data and established the quality indicators framework of ICT-related components for blended learning in campus-based universities. Then, these indicators were revised after the expert evaluation. And then 10 experts and practitioners scored importance rating. Finally, we sum them up to 17 indicators and 48 sub-indicators in three phases (input, process, output). Among them, e-learning related organization or body, usability of Learning Management System, and quality assessment system got the highest scores. These indicators are supposed to contribute to measure the quality of ICT-related environment for blended learning and to provide informations about what is required for efficient blended learning in the campus-based universities.

• Communications of Mathematical Education
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• v.24 no.1
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• pp.29-48
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• 2010

The purpose of this paper is to discuss about the use of technology in teaching-learning school mathematics. In this paper, we study the theoretical background of teaching-learning school mathematics by the use of technology. For the purpose of successful use of technology in teaching-learning school mathematics, we research the present states of it appeared in textbooks of high school mathematics And we give suggestions for the effective use of technology in teaching-learning school mathematics. Furthermore, we introduce models for teaching-learning school mathematics in areas of mathematics by the use of computer programs such as GSP, Maple, and GrafEq.

• Journal of Information Technology Applications and Management
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• v.16 no.1
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• pp.37-50
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• 2009

The benefits of an e-learning system will not be maximized unless learners use the system. This study proposed and tested models that seek to explain students' satisfaction withe-learning systems. A survey was performed at a women's college in Korea, where students experimentally could choose to register one same course either through e-learning or class-room learning. The questionnaire was filled up by students who took e-learning option. independent variables include expected benefits, familiarity with technology, social influence, and accessibility. Dependent variables include the level of satisfaction, academic achievement, and the amount of the use of systems.

• Korean Medical Education Review
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• v.23 no.3
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• pp.147-153
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• 2021

The coronavirus disease 2019 (COVID-19) pandemic made it necessary for medical schools to restructure their curriculum by switching from face-to-face instruction to various forms of flexible learning. Flexible learning is a student-centered approach to learning that has received interest in many educational sectors. It is a critical strategy for expanding access to higher education during the pandemic. As flexible learning includes online, blended, hybrid, and hyflex learning options, learners have the opportunity to select an instruction modality based on their needs and interests. The shift to flexible learning in medical education took place rapidly in response to the COVID-19 pandemic, and learners, instructors, and schools were not prepared for this instructional change. Through the lens of the technology acceptance model, human agency, and a social constructivist perspective, I examine students, instructors, and educational institutions' roles in successfully navigating the digital transformation era. The pandemic has also accelerated the use of advanced information and communication technologies, such as artificial intelligence and virtual reality, in learning. Through a review of the literature, this paper aimed to reflect on current flexible learning practices from the instructional design and educational technology perspective and explore emerging technologies that may be implemented in future medical education.

• Investigative Magnetic Resonance Imaging
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• v.23 no.2
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• pp.81-99
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• 2019

Recently, deep learning methods have shown great potential in various tasks that involve handling large amounts of digital data. In the field of MR imaging research, deep learning methods are also rapidly being applied in a wide range of areas to complement or replace traditional model-based methods. Deep learning methods have shown remarkable improvements in several MR image processing areas such as image reconstruction, image quality improvement, parameter mapping, image contrast conversion, and image segmentation. With the current rapid development of deep learning technologies, the importance of the role of deep learning in MR imaging research appears to be growing. In this article, we introduce the basic concepts of deep learning and review recent studies on various MR image processing applications.

• International Journal of Advanced Culture Technology
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• v.8 no.2
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• pp.42-47
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• 2020

This study is to develop Korean version of the 7 Learning Style Inventory(LSI) for IT major Students by systematic translation process and to test learning style of IT major University students. Translated and developed Korean version of LSI was verified of validity by comparing with existing V.A.K. learning style model. We can develop various tactics for 7 learning styles of students. Once the learning style of each student is confirmed, customized teaching for individual and team can be done more efficiently through teaching and learning strategies according to each learning style. Developed LSI was applied to the IT major students of two classes from Chungwoon University in Incheon. Results of LSI survey show that learning styles of 24 students out of 35 students from two classes are matched with V.A.K. learning styles of same students. It was 68.6% match in learning style, and shows that validity of 7 LSI. We need to elaborate Korean questionnaires of the LSI more, and extend and apply to the non-IT major students group.

• Journal of Information Technology Applications and Management
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• v.13 no.4
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• pp.197-214
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• 2006

This study explores factors to facilitate web-based collaborative learning and the effect of learning, based on the PBL(Problem Based Learning) from the constructivist approach in e-learning. A research model, using the key variables such as situations, interactions, and systems, was developed. In order to test this proposed model, experimental design and post-survey was conducted to the learners who took on-line and off-line course with team project. In the research model, situation category was divided into instructor's support, unstructured problem, and self-directed learning. Interaction category was divided into three factors; 'interaction between learners', 'interaction between learner and instructor', and 'interaction between learner and technology'. System category was divided into.monitoring and incentives. As a result, it was found that collaborative learning can be improved by situations, interactions, and systems, and the effectiveness of learning can be improved by situations and interactions in PBL.

• Educational Technology International
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• v.16 no.2
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• pp.85-110
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• 2015

This study investigated whether college students' self-efficacy, learning strategy utilization, academic burnout, and school support predict course satisfaction and learning persistence. To this end, self-efficacy, learning strategy utilization, academic burnout, and school support were used as prediction variables; and course satisfaction and learning persistence, as criterion variables. The subjects were 178 students who registered for online and mobile "Culture and Art History" courses at K online university. They participated in an online survey. Multiple regression analysis revealed that self-efficacy and learning strategy utilization positively predicted course satisfaction and learning persistence, academic burnout negatively predicted them, and school support predicted neither. Accordingly, we suggest that raising self-efficacy and learning strategy utilization, and reducing academic burnout in the learning environment will improve the course satisfaction and learning persistence of online learners.

• International Journal of Advanced Culture Technology
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• v.12 no.3
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• pp.336-344
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• 2024

The purpose of this study is to analyze the need of college students for experiential learning, collaborative learning, and enquiry-based learning. To achieve this goal, a survey was conducted with 308 college students. The need for experience, collaboration, and enquiry-based learning was comprehensively analyzed through t-tests, Borich needs analysis, and priority determination using The Locus for Focus model. The research findings are as follows: First, in Borich need analysis, the highest needs were identified for deep learning, self-directed learning, connecting theoretical knowledge with practical application, immersion, and application to real-life situations. Second, in The Locus for Focus model, the highest needs were found for abstract conceptualization, interest, conflict management, self-directed learning, and curiosity. In summary, since self-directed learning showed the highest priority simultaneously in Borich need analysis and The Locus for Focus model, it should be considered as the most prioritized item.

• Journal of Practical Engineering Education
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• v.14 no.1
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• pp.219-224
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• 2022

Q-Learning is a technique widely used as a basic algorithm for reinforcement learning. Q-Learning trains the agent in the direction of maximizing the reward through the greedy action that selects the largest value among the rewards of the actions that can be taken in the current state. In this paper, we studied a policy that can speed up agent training using Q-Learning in Frozen Lake 8×8 grid environment. In addition, the training results of the existing algorithm of Q-learning and the algorithm that gave the attribute 'direction' to agent movement were compared. As a result, it was analyzed that the Q-Learning policy proposed in this paper can significantly increase both the accuracy and training speed compared to the general algorithm.