• Journal of Korean Elementary Science Education
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• v.40 no.3
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• pp.343-365
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• 2021

The purpose of this study was to clarify the effect of learner variables on triggering state curiosity and state anxiety in confronting scientific task situation for fifth to sixth grades of elementary school. Science curiosity, interest, need for cognition, science self-concept, science anxiety, prior knowledge, and perceived difficulty were selected as learner variables that are expected to affect state curiosity and state anxiety. As a result of this study, the variables that had a significant influence on evoking state curiosity in confronting scientific task situation were in the order of interest, need for cognition, science curiosity, and prior knowledge, and all of these variables had a positive effect. In addition, the variables that significantly affect on evoking state anxiety in confronting scientific task situation were in the order of science anxiety, perceived difficulty, need for cognition, science self-concept, and prior knowledge. Of these, only prior knowledge had a negative effect on evoking state anxiety, and the other variables had a positive effect. The results of this study are expected to broaden the comprehension of students' emotional states in science education, and provide a theoretical foundation for the studies of state curiosity and state anxiety in science learning.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.319-326
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• 2013

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. It is shown that it is possible to do asymptotic likelihood inference for software reliability models based on infinite failure model and non-homogeneous Poisson Processes (NHPP). Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, we proposed a control mechanism based on NHPP using mean value function of logarithmic hazard learning effects property.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.73-80
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• 2020

The OECD surveys the questionnaire on the background of ICT every three years since 2003. In this study, we compare and analyze the changes in ICT accessibility and ICT usability of Korean students in 2015 and 2018 using the ICT background data of OECD PISA. ICT accessibility refers to the degree of access to ICT equipment at school or at home. There are 10 items of accessibility surveys at schools used by PISA, and 11 items at home. ICT usability refers to how much ICT equipment is used at or outside of school for learning or non-learning purposes. There are ten items for surveying usability at school, and twenty-four items for surveying usability outside of school. In the analysis of this study, the arithmetic mean of the items is used. As a result, Korean students' accessibility at school improved from 25.48% in 2015 to 40.40% in 2018, and from the lowest group in 2015 to below-average group in 2018. In terms of students' usability at school, we analyzed the percentage of students who use the ICT equipment 'almost every day' and the students who use it 'everyday'. Both 2015 and 2018 are among the lowest. Accessibility at home is higher in 2018 than in 2015, and belongs to the average group of OECD countries in 2018. ICT Usability for learning purposes outside of school is the lowest group in both 2015 and 2018. ICT Usability outside of school for non-learning purposes is in the average group of OECD countries. As a result of this study, we can see that Korea's digital literacy education is weak compared to other OECD countries. Prior to education about the Fourth Industrial Revolution, investment in digital literacy education is needed.

• School Mathematics
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• v.15 no.2
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• pp.315-335
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• 2013

Probability has distinctive characteristics which are different from other areas of school mathematics. The critical change can be noticed in the domain, 'probability and statistics' of 2009 revised national curriculum for elementary school mathematics. This indicates that the concept of chance is supposed to be taught in the 5~6 grade band instead of the definition of probability which is moved to the middle school level. The purpose of this study is to seek desirable methods for teaching the concept of chance which reflect the achievement criteria and the attention point for teaching and learning of the curriculum at the point of time when textbooks haven't yet been developed. To do this, based on theoretical considerations and comparative analysis of the curricula in the longitudinal - latitudinal dimensions respectively, the validity of the latest curriculum change was confirmed and several learning activities were devised. And then two lessons were planned for applying these activities to eight fifth graders and were implemented along the plan. As a result, the relevance of the learning activities was examined and students' difficulties in learning the concept of chance with educational implications were discussed.

• Journal of Information Technology Applications and Management
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• v.25 no.1
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• pp.19-32
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• 2018

Fake news is defined as the news articles that are intentionally and verifiably false, and could mislead readers. Spread of fake news may provoke anxiety, chaos, fear, or irrational decisions of the public. Thus, detecting fake news and preventing its spread has become very important issue in our society. However, due to the huge amount of fake news produced every day, it is almost impossible to identify it by a human. Under this context, researchers have tried to develop automated fake news detection method using Artificial Intelligence techniques over the past years. But, unfortunately, there have been no prior studies proposed an automated fake news detection method for Korean news. In this study, we aim to detect Korean fake news using text mining and machine learning techniques. Our proposed method consists of two steps. In the first step, the news contents to be analyzed is convert to quantified values using various text mining techniques (Topic Modeling, TF-IDF, and so on). After that, in step 2, classifiers are trained using the values produced in step 1. As the classifiers, machine learning techniques such as multiple discriminant analysis, case based reasoning, artificial neural networks, and support vector machine can be applied. To validate the effectiveness of the proposed method, we collected 200 Korean news from Seoul National University's FactCheck (http://factcheck.snu.ac.kr). which provides with detailed analysis reports from about 20 media outlets and links to source documents for each case. Using this dataset, we will identify which text features are important as well as which classifiers are effective in detecting Korean fake news.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.3
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• pp.144-154
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• 2003

In this paper we present Logical Evolution method which is a new teaming algorithm for the concepts expressed as binary logic function. We try to solve some problems of Inductive Learning algorithms through Logical Evolution. First, to be less affected from limited prior knowledge, it generates features using the gained informations during learning process and learns the concepts with these features. Second, the teaming is done using not the whole example set but the individual example, so even if new problem or new input-output variables are given, it can use the previously generated features. In some cases these old features can make the teaming process more efficient. Logical Evolution method consists of 5 operations which are selected and performed by the logical evaluation procedure for feature generation and learning process. To evaluate the performance of the present algorithm, we make experiments on MONK data set and a newly defined problem.

• Korean Chemical Engineering Research
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• v.58 no.2
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• pp.224-229
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• 2020

We propose a machine learning-based method for proactively detecting faults in LDPE processes and predicting equipment lifespan. It is important to detect and prevent unexpected faults in chemical processes in order to maximize safety and productivity. Since LDPE process is a high-pressure process up to 3,000 kg/㎠g or more, once ESD occurs, it can result in productivity loss due to increased maintenance periods. By collecting key variables operation data of the process and using unsupervised machine leaning methods, we developed a fault detection model which detected 4 ESDs 2.4 days prior to the occurrence. In addition, it was confirmed that the life expectancy of a hyper compressor can be predicted by using the physically significant key variables.

• School Mathematics
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• v.18 no.4
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• pp.773-791
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• 2016

Teacher noticing ability has been considered as one of important elements influencing a quality of teaching. Noticing is closely related to teachers' in the moment decision making in a class, and teachers notice things as they create and interact with their classroom setting. Mathematics teachers as an expert should notice students' mathematics learning during a class. The aim of this study was to analyze how mathematics teacher's pre-noticing activity that the teacher anticipated students' typical strategies and difficulties in learning targeted mathematics knowledge and prepared appropriate responses worked in practice. As a result, the teacher conducted three types of noticing in her classes: noticing shaping students' understanding by using students' misconceptions or errors; noticing creating students' learning opportunities based on their prior knowledge; noticing improving students' informal reasoning. This study concluded with discussion about the positive effect of teacher's pre-noticing activity on her actual noticing in practice, as well as implications for teacher education.

• The Journal of Sustainable Design and Educational Environment Research
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• v.3 no.1
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• pp.1-14
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• 2003

This study attempts to review the present situations of rural schools in South Korea, to analyze problems regarding the educational environments for their students, and to present direction for improving toward better educational environments. All the data and information are based on using avaiable documents and personal macro observation and insights. The sharp decrease of rural population for recent decades has made lots of public schools unexceptionall much smaller by school number and students' number. Nearly five thousands of rural small schools have already been abolished and the rest are also endangered to be dosed. In order to tackIe such problem, the Government has been trying to provide rural students with better educational environment, but failed to attract them to stay in rural schools. Most of rural school students have poorer family environment, underprivilged school learning environment, and less civilized community environment. Those normal parents living in rural areas are likely to send their kids to urban schools for prior opportunities to enter better quality of higher level of schools and then the remained attending rural schools are those who live with grand parents or whose parents are very disadvantaged. The rural school teachers are teaching much less number of students compared to urban teachers, but their students are less achieved learners. Notwithstanding their abudant natural community learning environments, the rural school students are less making use of those resources and less benefited from more civilized life due to their underdeveloped community conditions. In order to improve such educational environments, incentives for young couples to safely reside in rural communities, incentives for better qualified teachers to preferably work for rural schools, better learning facilities for rural school students and for better vocational experiences, lifelong learning opportunities for all community people, and increased public support to rural development for rural people not to worry about their rural lives, need to be guarantyed.

• Clinical Psychopharmacology and Neuroscience
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• v.16 no.4
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• pp.449-460
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• 2018

Objective: Prior functional magnetic resonance imaging (fMRI) work has revealed that children/adolescents with disruptive behavior disorders (DBDs) show dysfunctional reward/non-reward processing of non-social reinforcements in the context of instrumental learning tasks. Neural responsiveness to social reinforcements during instrumental learning, despite the importance of this for socialization, has not yet been previously investigated. Methods: Twenty-nine healthy children/adolescents and 19 children/adolescents with DBDs performed the fMRI social/non-social reinforcement learning task. Participants responded to random fractal image stimuli and received social and non-social rewards/non-rewards according to their accuracy. Results: Children/adolescents with DBDs showed significantly reduced responses within the caudate and posterior cingulate cortex (PCC) to non-social (financial) rewards and social non-rewards (the distress of others). Connectivity analyses revealed that children/adolescents with DBDs have decreased positive functional connectivity between the ventral striatum (VST) and the ventromedial prefrontal cortex (vmPFC) seeds and the lateral frontal cortex in response to reward relative to non-reward, irrespective of its sociality. In addition, they showed decreased positive connectivity between the vmPFC seed and the amygdala in response to non-reward relative to reward. Conclusion: These data indicate compromised reinforcement processing of both non-social rewards and social non-rewards in children/adolescents with DBDs within core regions for instrumental learning and reinforcement-based decision-making (caudate and PCC). In addition, children/adolescents with DBDs show dysfunctional interactions between the VST, vmPFC, and lateral frontal cortex in response to rewarded instrumental actions potentially reflecting disruptions in attention to rewarded stimuli.