• The KIPS Transactions:PartB
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• v.9B no.2
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• pp.155-162
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• 2002

Reinforcement learning is a learning method that uses trial-and-error to perform Learning by interacting with dynamic environments. It is classified into online reinforcement learning and delayed reinforcement learning. In this paper, we propose an online reinforcement learning system (ONRELS : Outline REinforcement Learning System). ONRELS updates the estimate-value about all the selectable (state, action) pairs before making state-transition at the current state. The ONRELS learns by interacting with the compressed environments through trial-and-error after it compresses the state space of the mage environments. Through experiments, we can see that ONRELS can search the shortest path faster than Q-learning using TD-ewor and $Q(\lambda{)}$-learning using $TD(\lambda{)}$ in the maze environments.

• Journal of The Korean Association For Science Education
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• v.32 no.9
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• pp.1452-1469
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• 2012

This study examined the science learning environments experienced by Korean and U.S. preservice elementary science teachers during their 3-week clinical experience. Observational experiences of 97 Korean and 112 U.S preservice teachers were surveyed with an instrument that we developed for the study. Follow-up interviews provided a clearer picture of what preservice teachers observed and experienced in science classrooms during their clinical experiences. Korean preservice teachers experienced a variety of science teaching environments, whereas the U.S. preservice teachers reported limited opportunities to observe science teaching and learning in terms of 6 identified facets that we posed. Along with our interpretation of the contrast in findings, some of the challenges are discussed in providing preservice teachers with opportunities to observe, experience, and teach in effective science learning environments during the clinical experience.

• International Journal of Control, Automation, and Systems
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• v.5 no.6
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• pp.674-680
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• 2007

The probabilistic roadmap (PRM) method, which is a popular path planning scheme, for a manipulator, can find a collision-free path by connecting the start and goal poses through a roadmap constructed by drawing random nodes in the free configuration space. PRM exhibits robust performance for static environments, but its performance is poor for dynamic environments. On the other hand, reinforcement learning, a behavior-based control technique, can deal with uncertainties in the environment. The reinforcement learning agent can establish a policy that maximizes the sum of rewards by selecting the optimal actions in any state through iterative interactions with the environment. In this paper, we propose efficient real-time path planning by combining PRM and reinforcement learning to deal with uncertain dynamic environments and similar environments. A series of experiments demonstrate that the proposed hybrid path planner can generate a collision-free path even for dynamic environments in which objects block the pre-planned global path. It is also shown that the hybrid path planner can adapt to the similar, previously learned environments without significant additional learning.

• International Journal of Contents
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• v.4 no.4
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• pp.18-23
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• 2008

With the development of information communication and network technologies, ubiquitous era that supports various services regardless of places and time has been advancing. The development of such technologies has a great influence on educational environments. As a result, e-learning concepts that learners use learning contents in anywhere and anytime have been proposed. The various learning contents authoring systems that consider the e-learning environments have also been developed. However, since most of the existing authoring systems support only PC environments, they are not suitable for various ubiquitous mobile devices. In this paper, we design and implement a contents authoring system based on learning activities for u-learning environments. Our authoring system significantly improves the efficiency for authoring contents and supports various ubiquitous devices as well as PCs.

• Journal of The Korean Association For Science Education
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• v.20 no.1
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• pp.12-19
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• 2000

The relationships among students' perceptions of computerized science learning environments, computer-related attitudes. and computer experiences were investigated with a sample of 164 9thgraders (80 boys and 84 girls) from two middle schools. The Computerized Science Learning Environment Inventory (CSLEI) and the Computer-Related Attitudes Scale (CRAS) were administered, and students' computer experiences were examined. Students' perceptions of preferred learning environments were also studied with the preferred form of the CSLEI, and compared with those of actual learning environments. Gender differences in the perceptions of computerized science learning environments, computer-related attitudes, and computer experiences were also studied. Students' perceptions of preferred learning environments were significantly better than those of actual learning environments in all subscales of the CSLEI except gender equity. There was no gender difference in the perceptions of computerized science learning environments. However, boys were found to have more positive computer-related attitudes and more computer experiences than girls. Students' perceptions of computerized science learning environments were significantly correlated with computer-related attitudes in resource adequacy subscale, but not with computer experiences. Significant relationships between computer-related attitudes and computer experiences were also found.

• Educational Technology International
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• v.15 no.2
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• pp.49-69
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• 2014

The purpose of this study was to investigate the effect of co-regulated learning on the improvement of self-regulated learning skills in collaborative learning environments. One group pretest-posttest design was used in this study. The subjects were 49 undergraduate students who enrolled in 'Educational Evaluation' course. To facilitate students' co-regulated learning activities, group worksheets were developed. Students performed collaborative tasks in group by using the group worksheets over the 6 weeks. The results showed that the difference between means of the pretest and posttest was no statistically significant. It indicates that co-regulated learning activities did not have a significant effect on the improvement of self-regulated learning skills in collaborative learning environments. However, the results of additional analysis revealed that the difference between means of the pretest and posttest in case of 19 students with low self-regulated learning level was statistically significant. On the other hand, there was no statistically significant difference between means of the pretest and posttest in case of 19 students with high self-regulated learning level. It is interpreted that co-regulated learning activities positively affected the improvement of self-regulated learning skills of students with low self-regulated learning level.

• Journal of The Korean Association For Science Education
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• v.29 no.5
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• pp.492-500
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• 2009

The purpose of the study was to investigate middle school students' and teachers' perception of psychological learning environments as well as the differences between them. This study sampled 503 middle school students and the 16 teachers who taught them. 'Psychological Learning Environment Instrument by Science Teacher' was implemented to collect data. Frequency analysis and descriptive statistics, as well as t-test, ANOVA were used for basic analysis of data. There were statistically meaningful differences in students' perception of psychological learning environments by gender, science achievement, science preference and self-efficacy in science. However, there are no differences in teachers' perceptions of psychological learning environments by gender, age, career year and major. The difference between teachers' and students' perception of psychological learning environments was not large, showing no statistical significance. However, teachers' perceptions of psychological learning environments was a little higher than that of students.

• Educational Technology International
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• v.11 no.2
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• pp.149-172
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• 2010

Knowledge can be more meaningful when it is shaped and personalized through interaction with others. Implementation of open learning environments such as open courseware or shared knowledge communities has gradually become more common. A case study which investigated instructors' experiences and perceptions of publishing and using open courseware in the classroom was conducted at a university in Korea. Responses from participating students and an evaluation group regarding how they perceived open learning environments were also examined. Based on the inductive analysis of the data, this study discusses advantages and challenges of publishing open courseware and collaborative learning environments. Also, practical guidelines for developing reusable learning materials are suggested.

• The Journal of Korean Association of Computer Education
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• v.14 no.2
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• pp.33-45
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• 2011

According to recent needs for 'smart learning', the concept of smart learning was reviewed by device, environmental, and theoretical approaches. The principle of smart learning includes three elements: First, rich instructional resources as learning contents. Second, participatory learning environments with interactions among teachers and learners as learning methods. Third, practical and realistic contexts as learning environments. Based on those characteristics, instructional designs for smart learning can be summed up as learning objectives, learning resources, instructional environments, instruction process design, instruction method development, implementation, and evaluation. As a conclusion, it is required to systematically develop instructional designs addressing specific learning settings to facilitate smart learning.

• Educational Technology International
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• v.17 no.2
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• pp.175-202
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• 2016

Most of the learning analytics research has investigated how quantitative data can affect learning. The information that is provided to learners has been determined by teachers and researchers based on reviews of the previous literature. However, there have been few studies on standard learning activities that are performed in e-learning environments independent of the teaching methods or on learning behavior data that are obtained through learning analytics. This study aims to explore the general learning activities and learning behaviors that can be used in the analysis of learning data. Learning activities and learning behavior are defined in conjunction with the concept of learning analytics to identify the differences between teachers' and learners' learning activities. Learning activities and learning behavior were verified by an expert panel review in an e-learning environment. The differences between instructors and learners in their usage were analyzed using a survey method. As results, 8 learning activities and 29 learning behaviors were validated. The Research has shown that instructors' degree of utilization is higher than that of the learners.