• Hwankyungkyoyuk
• /
• v.13 no.1
• /
• pp.44-52
• /
• 2000

In this study, the effects of structured controversy strategy, individual learning, and traditional learning on the learning of environmental unit in ‘General Science’ were compared. One hundred and forty-three 10th-graders had been taught about environmental issues-self purification, biological concentration, acid rain, greenhouse effect, noise, and radioactivity-for 6 class hours. Prior to the instructions, environmental attitudes test and self-esteem test were administered. After the instructions, their achievements, critical thinking, environmental attitudes. self-esteem, and views on Science-Technology-Society were examined. The results of 2-way ANCOVA and/or Kruskal-Wallis test revealed that there were no significant main effects in the scores of the achievement test and the critical thinking test. The environmental attitudes test scores tended to be highest in the structured controversy group, and lowest in the traditional learning group. Self-esteem scores of the structured controversy group and the individual learning group were higher than those of the traditional learning group. Significant differences by students' prior achievement level in students' critical thinking, environmental attitudes, and views on Science-Technology-Society were also found.

• Communications for Statistical Applications and Methods
• /
• v.10 no.3
• /
• pp.879-894
• /
• 2003

We evaluated the efficiencies of applying attribute selection methods and prior discretization to supervised learning, modelled by C4.5 and Naive Bayes. Three databases were obtained from UCI data archive, which consisted of continuous attributes except for one decision attribute. Four methods were used for attribute selection : MDI, ReliefF, Gain Ratio and Consistency-based method. MDI and ReliefF can be used for both continuous and discrete attributes, but the other two methods can be used only for discrete attributes. Discretization was performed using the Fayyad and Irani method. To investigate the effect of noise included in the database, noises were introduced into the data sets up to the extents of 10 or 20%, and then the data, including those either containing the noises or not, were processed through the steps of attribute selection, discretization and classification. The results of this study indicate that classification of the data based on selected attributes yields higher accuracy than in the case of classifying the full data set, and prior discretization does not lower the accuracy.

• International journal of advanced smart convergence
• /
• v.11 no.2
• /
• pp.13-21
• /
• 2022

In this paper, we propose a learning based joint demosaicing and super-resolution framework which uses only the mosaiced color filter array(CFA) image as the input. As the proposed method works only on the mosaicied CFA image itself, there is no need for a large dataset. Based on our framework, we proposed two different structures, where the first structure uses one deep image prior network, while the second uses two. Experimental results show that even though we use only the CFA image as the training image, the proposed method can result in better visual quality than other bilinear interpolation combined demosaicing methods, and therefore, opens up a new research area for joint demosaicing and super-resolution on raw images.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.21 no.5
• /
• pp.1042-1048
• /
• 2017

Recently rapid changes in the industrial environment require new talents in companies. Flipped learning is drawing attention as an effective teaching-learning method. The existing traditional lecture teaching-learning method have various problems that the dropout rates of the student is high and the creative problem solving ability is hindered. In the case of the IT engineering college, most of the major theoretical courses require prior learning of the prerequisite coursework subjects. Therefore, effective teaching-learning methods must be developed to improve student participation and academic achievement. This paper proposes the flipped learning model consisting of five sets that combine the flipped learning and practice to improve student motivation and self - directed learning. Also, this paper analyzes the learning effect by applying it to the algorithm lecture of computer engineering and presents problem and utilization plan according to the result.

• Journal of Korean Elementary Science Education
• /
• v.38 no.1
• /
• pp.43-54
• /
• 2019

In order to organize various places for science experience study, this study gathered and analyzed prior research on science experience study and various science experience perated in school. To that end, a total of 162 relevant prior studies of literature published from 2000 to 2016 were collected and 2,201 cases of science experience study conducted in 2015 were collected and analyzed. The place where the science experiential learning was done is divided into three areas of natural ecology, cultural history, facility experiential learning study, and the characteristics of participating subjects are examined. In terms of the number of articles published in the field of science-related experiential learning areas, 83 ecological experience study sites (51.2%), facilities institution experience study sites 56 (34.6%), and cultural history experience study books 23 (14.2%). Through this study, it was found out that research tendency to analyze science - related attitudes became prominent by setting study subjects using natural objects around and learning to play while playing and playing in nature. There was also an analysis by subjects of participation in science related experience learning centers. Cultural history experiential learning field was significantly lower than previous studies. In the lower grades, nature ecological experience learning was mainly performed. Combining the above findings, it can provide implications for the development of science-related experience activities. First, it is necessary to develop a technology-related experience learning center using local community resources. Second, it is necessary to expand the culture and history experience learning center related to science. Third, we need an education support center to support the expansion and operation of such a technology-related cultural history learning center.

• Journal of Information Technology Services
• /
• v.20 no.4
• /
• pp.129-140
• /
• 2021

Recently, interest in AI tutors is rising as a way to bridge the educational gap in school settings. However, research confirming the effectiveness of AI tutors is lacking. The purpose of this study is to explore how effective learner characteristics and recommended item learning activities are in predicting learner's academic performance in an adaptive online learning environment. This study proposed the hypothesis that learner characteristics (prior knowledge, midterm evaluation) and recommended item learning activities (learning time, correct answer check, incorrect answer correction, satisfaction, correct answer rate) predict academic achievement. In order to verify the hypothesis, the data of 362 learners were analyzed by collecting data from the learning management system (LMS) from the perspective of learning analytics. For data analysis, regression analysis was performed using the regsubset function provided by the leaps package of the R program. The results of analyses showed that prior knowledge, midterm evaluation, correct answer confirmation, incorrect answer correction, and satisfaction had a positive effect on academic performance, but learning time had a negative effect on academic performance. On the other hand, the percentage of correct answers did not have a significant effect on academic performance. The results of this study suggest that recommended item learning activities, which mean behavioral indicators of interaction with AI tutors, are important in the learning process stage to increase academic performance in an adaptive online learning environment.

• Journal of Korean Elementary Science Education
• /
• v.25 no.2
• /
• pp.191-205
• /
• 2006

The purpose of this study was to explore strategies used by pre-service elementary science teachers in planning a science lesson. The participants were six senior students from a national university of education located in the midwestern area of Korea. Data regarding their planning strategies were gathered through both thinking-aloud and observation. Research findings suggest that: three of the teachers had little understanding of the necessity of reviewing unit contents or prior learning for planning a science lesson; five student teachers relied heavily on learning objectives presented in teachers' guidebooks without considering their appropriateness; all teachers exhibited an intention of composing different activities or teaching approaches from teachers' guidebooks; only two teachers thought about learners' prior knowledge or understanding levels; five and three teachers had poor understanding of discovery learning models and importance of teacher's questioning, respectively; and five teachers paid little attention to assessment.

• Journal of Digital Convergence
• /
• v.10 no.10
• /
• pp.439-445
• /
• 2012

The aim of the work that is presented in this paper is to develop the new prior educational materials which use the field trip and to present educational possibilities. The QR codes were used to develop the prior materials. The developed materials applied to elementary students who attended to filed trips in 2012. This was practically achieved by the use of smartphone which enhance the learning experience of a physical visit by providing personalized information with QR codes. The results demonstrate the technology supported physical field trips provides significantly improved learning outcomes, increases students curiosity. Furthermore the findings of the study demonstrate that the application of the specific emerging technologies could facilitate the development of advanced learning experiences in field trips, increasing at a significant level the learning outcomes and the motivation of the participating students.

• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10a
• /
• pp.218-223
• /
• 1992

This paper describes a learning method of neural network controllers. The learning method improves the performance of indirect learning mechanism in the neuro-control of nonlinear systems. To precisely identify dynamic characteristics of the plant by utilizing a limited prior information we propose a new energy function which takes advantage of the proportional relationship between outputs of the plant and those of neural networks.

• The Journal of the Acoustical Society of Korea
• /
• v.41 no.2
• /
• pp.199-209
• /
• 2022

Typical anomaly detection algorithms are trained by using prior data. Thus the batch learning based algorithms cause inevitable performance degradation when characteristics of newly incoming normal data change over time. We propose an online anomaly detection algorithm which can consider the gradual characteristic changes of incoming normal data. The proposed algorithm based on one-class classification model includes both offline and online learning procedures. In offline learning procedure, the algorithm learns the prior data to be close to centroid of the latent space and then updates the centroid of the latent space incrementally by new incoming data. In the online learning, the algorithm continues learning by using the updated centroid. Through experiments using public underwater acoustic data, the proposed online anomaly detection algorithm takes only approximately 2 % additional learning time for the incremental centroid update and learning. Nevertheless, the proposed algorithm shows 19.10 % improvement in Area Under the receiver operating characteristic Curve (AUC) performance compared to the offline learning model when new incoming normal data comes.