• 대한공업교육학회지
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• v.34 no.2
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• pp.267-285
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• 2009

The collaborative learning has been considered as an efficient teaching model and under the recent basic learning environment, even face-to-face classroom circumstance rapidly increases the courses of blended learning which utilize the merits of e-learning environment. Nonetheless, the study on the strategy for systematic blended learning is quite scarce. In this study, the survey was done for developing the blended learning strategy, based on the collaborative learning model at the face-to-face environment and judging the satisfaction on the courses which the model was applied to. The survey consists of demographic questions, satisfaction in the whole courses, satisfaction in the collaborative learning under the blended learning environment and satisfaction in the blended learning strategy and support tools applied to each step of the learning. The result of this study is as follows. First, in response to the question that the blended learning can complement the face-to-face classroom courses, the respondents represented average 4.09 at 5-point Likert scale. And to the question whether the collaborative learning is more efficient under the blended learning environment than the face-to-face classroom, the response corresponds to 4.06 scale on the average. Second, as for the satisfaction in the blended learning strategy and support tools applied to the each step of the blended learning, the satisfaction degree is analyzed as high as over 4.0 on the average toward all the questions. Third, regarding the support tools used for the blended learning strategy, the learners consider the tools as most helpful in order of chatting, team community, mail & note and archive. Lastly, I would like to suggest that the study result should be highly reflected in constructing the collaborative learning module of learning control system in the future.

• The Journal of Korean Institute for Practical Engineering Education
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• v.2 no.1
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• pp.1-7
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• 2010

Recently, interest in u-learning to pursue effective learning by using ubiquitous environment in teaching and learning activities. In u-learning environment, learners should be able to push necessary information at the right time and the right place. Also calm technology oriented to, and this means that it can recognize learners' terminal information and to provide adaptive interface. In u-learning environment, main learning terminals would be mobile terminals which support mobility. However, learning in the existing PC environment should not be excluded. Thus, by providing adaptive interface according to various learners' terminal in LMS for u-learning, learners are able to learn through consistent and natural learning interface with any computer or any network at any place and at any time. The purpose of this study is to propose the interface adaptation based on terminal information focusing on the layout transformation process in the development environment.

• International Journal of Internet, Broadcasting and Communication
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• v.4 no.1
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• pp.8-12
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• 2012

The purpose of this study is to review the possible effect of the learning paradigm shift from traditional method to ubiquitous learning. What are the societal issues that need to be address in order to design a new pedagogical platform trending from e-learning to m-learning and now the u-learning? That without the proper study of how learning environment may affect the learning process of an individual will lead to poor quality of education. This new era of learning environment offer a big opportunity for "anytime, anywhere" learning. Thus, Lifelong learning is at hand of everyone. Maximizing the benefit of new trend will be a great help and addressing the limitations will lead to quality education.

• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.594-602
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• 2021

This study aims to identify the learning behavior patterns recognized by students to find effective tutoring operational methods, and further analyze the impact of learning behavior patterns on academic performance and learning satisfaction. To this end, 105 participants in the tutoring program at D University based in Busan Metropolitan City collected data and conducted descriptive statistics, correlation analysis and regression analysis according to research problems. First, the study found that students who participated in tutoring had the most environment-dependent and self-taught learning behavioral styles and environment-independent and self-taught learning behavioral style. Second, the correlation between learning behavioral styles and academic achievement and learning satisfaction shows that there is a high correlation between positive and cooperative learning behavioral styles and environment-independent and self-taught learning behavioral styles. Third, regression analysis on academic achievement and learning satisfaction showed that positive and cooperative learning behavioral styles significantly affects learning satisfaction, but environment-independent and self-taught learning behavioral style, environment-dependent and self-taught learning behavioral style, and passive learning behavioral style were not significant. These results suggest that from the school perspective, learning behavior can be recognized as an important factor in students' academic success and failure, so instructors need to check learners' learning behavior patterns and provide appropriate tutoring teaching and learning design plans.

• East Asian Journal of Business Economics (EAJBE)
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• v.10 no.3
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• pp.1-15
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• 2022

Purpose - This study explored factors of online education that affect student dissatisfaction and learning effectiveness in higher education during the COVID-19 pandemic. Research design, data, and methodology - This study combined qualitative and quantitative designs. The qualitative part of this study involved in-depth interviews using a criteria-based purposive sampling technique. The quantitative part of this study consisted of an online survey. Results - The qualitative results revealed that students faced significant problems related to online learning, including a lack of learning environment, interaction, and support from the school. The quantitative results indicated that the effects of transitioned-online courses on student dissatisfaction were higher with student support, the interaction between students and instructors, online learning environment, and course organization and evaluation based on the order, while the effects on learning effectiveness were higher with the online learning environment, interaction between students and instructors, course organization and evaluation, and student support based on the order. Conclusion - The results implied that online learning in the era of the COVID 19 pandemic negatively affects student satisfaction and learning effectiveness. Policymakers and school leaders should improve students' satisfaction and learning effectiveness when confronted with the pandemic. Better policies should be adopted to improve better way of teaching in the era of COVID19.

• Educational Technology International
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• v.25 no.1
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• pp.129-159
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• 2024

The purpose of this study was to examine changes in students' awareness of online classes in university education over the three years from 2020 to 2022 during the COVID-19 pandemic. To achieve this, various aspects of online classes, including self-directed learning, interaction (between instructors and learners, and among learners), evaluation of the learning process and outcomes, and the learning environment and control of learning, were analyzed for changes from 2020 to 2022. The study included 534 university students enrolled in University A who participated in online classes in both 2020 and 2021. The results indicated that there was no significant difference in the awareness of self-directed learning, but significant differences were found in the awareness of interaction, evaluation of the learning process and outcomes, and the challenge related to learning environment and control of learning in online classes, which were higher in 2021 and 2022 than in 2020. Additionally, detailed changes in awareness of online classes showed significant differences in specific aspects of awareness in university online classes. In summary, students' awareness of online classes improved in 2021 and 2022 compared to 2020, as learners adapted to online classes due to the COVID-19 pandemic. Moreover, it was observed that difficulties in the challenge related to learning environment and control of learning were overcome in 2021. Based on these research findings, several implications for improving the design and operating strategies of effective online classes in future university education were proposed.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.127-133
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• 2005

With the increasing use of the Internet improved Internet technologies as well as web-based applications, the uses of e-Learning have also increased the effectiveness of e-Learning has become one of the most practically and theoretically important issues in both Educational Engineering and Information Systems. This study suggests a research model, based on an e-Learning success model, the relationship of the e-leaner's self-regulated learning strategy and the quality perception of the e-Learning environment. This research model focuses on the learning environment and on self regulated learning strategy. The former consists of LMS, learning contents and interaction that are provided by e-Learning and the latter refers to the learners' self-regulated learning strategy. We will show the validity of the model empirically. As result, most of the hypotheses except for H6 suggested in this model were accepted.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.138-141
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• 2003

Recently reinforcement learning has attracted attention of many researchers because of its simple and flexible learning ability for any environments. And so far many reinforcement learning methods have been proposed such as Q-learning, actor-critic, stochastic gradient ascent method and so on. The reinforcement learning system is able to adapt to changes of the environment because of the mutual action with it. However when the environment changes periodically, it is not able to adapt to its change well. In this paper we propose the reinforcement learning system that is able to adapt to periodical changes of the environment by introducing the time-varying parameters to be adjusted. It is shown that the proposed method works well through the simulation study of the maze problem with aisle that opens and closes periodically, although the conventional method with constant parameters to be adjusted does not works well in such environment.

• Journal of The Korean Association of Information Education
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• v.8 no.3
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• pp.307-317
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• 2004

In web-based education environment, it is necessary to provide individually adjusting feedback according to learner's characteristic. Despite this necessity, it is a current state that there are difficulties in deriving the variables of learners' characteristics and lack in developing the systematic strategies and practical tools for providing individually adjusting feedback. This study analyzed the learners' learning patterns, one of learner's characteristic variables regarded as important in web-based teaching and learning environment by employing Apriori algorithm, and also grouped the learners by learning pattern. Under this framework, the e-SRM feedback system was designed and developed to provide learning content, learning channel, and learning situation, etc. for individual learners. The proposed system in this study is expected to provide an optimal learning environment complying with learner's characteristic.

• The Journal of Korea Robotics Society
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• v.16 no.1
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• pp.56-63
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• 2021

As the use of robots in service area increases, research has been conducted to replace human tasks in daily life with robots. Among them, this study focuses on the tidy-up task on a desk using a robot arm. The order in which tidy-up motions are carried out has a great impact on the success rate of the task. Therefore, in this study, a neural network-based method for determining the priority of the tidy-up motions from the input image is proposed. Reinforcement learning, which shows good performance in the sequential decision-making process, is used to train such a task planner. The training process is conducted in a virtual tidy-up environment that is configured the same as the actual tidy-up environment. To transfer the learning results in the virtual environment to the actual environment, the input image is preprocessed into a segmented image. In addition, the use of a neural network that excludes unnecessary tidy-up motions from the priority during the tidy-up operation increases the success rate of the task planner. Experiments were conducted in the real world to verify the proposed task planning method.