• School Mathematics
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• v.18 no.3
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• pp.667-689
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• 2016

Value is an intellectual and an affective concept that influences behavior. It does not exist individually but is conveyed through generation with some system. Korean students showed high achievement scores in spite of low emotion in mathematics learning. The objects of value recognition ought to be extended to social value as well as mathematics for balancing intellectual and affective features. Since the value formed at the first step in mathematics learning keeps its influence even after learning, it is important to form a positive recognition in the value. The following conclusions were drawn. First, the mathematics learning value instrument developed in this study. It is appropriate to explain a students' imbalance of intellectual and affective characteristics. Second, it is possible that the intellectual achievement of Korean students are influenced by the others-oriented value in particular. Third, the recognition of the mathematics learning value of elementary school students would have an influence on secondary school learning. Therefore, education for parents of elementary school students is required. This study can provide a basis on the view of the mathematics learning value which influences the educational result of Korean elementary students as well. It is expected from the following studies that focus on improving affective characteristics on mathematics learning of Korean students is beneficial.

• Journal of the Korea Society of Computer and Information
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• v.22 no.9
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• pp.187-192
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• 2017

In this paper, we have studied scale tools for measure programming task value and learning persistence at elementary school students. In order to develop complete test tools, we have improved the completeness by revising tests through stepwise verification. The first scales were constructed based on the previous studies. As a result of the content validity test, 5 out of 14 items of the task value test tool and 1 out of 10 items of the learning persistence test were not suitable. The second test tools were constructed by revising and supplementing the first scale, and consisted of 13 items of task value and 8 items of learning persistence. As a result of the contents validity test, all the items included in the test tool proved to be valid. The reliability of the secondary testing tools were also found to be reliable at ${\alpha}=.970$ and ${\alpha}=.975$, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3966-3991
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• 2018

Due to the lack of visualization services and organic combinations between public and private buildings data, the usability of the basic map has remained low. To address this issue, this paper reports on a solution that organically combines public and private data while providing visualization services to general users. For this purpose, factors that can affect building prices first were examined in order to define the related data attributes. To extract the relevant data attributes, this paper presents a method of acquiring public information data and real estate-related information, as provided by private real estate portal sites. The paper also proposes a pretreatment process required for intelligent machine learning. This report goes on to suggest an intelligent machine learning algorithm that predicts buildings' value pricing and future value by using big data regarding buildings' spatial information, as acquired from a database containing building value attributes. The algorithm's availability was tested by establishing a prototype targeting pilot areas, including Suwon, Anyang, and Gunpo in South Korea. Finally, a prototype visualization solution was developed in order to allow general users to effectively use buildings' value ranking and value pricing, as predicted by intelligent machine learning.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.13-16
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• 2001

In reinforcement teaming, Q-learning converges quite slowly to a good policy. Its because searching for the goal state takes very long time in a large stochastic domain. So I propose the speedup method using the Q-value initialization for model-free reinforcement learning. In the speedup method, it learns a naive model of a domain and makes boundaries around the goal state. By using these boundaries, it assigns the initial Q-values to the state-action pairs and does Q-learning with the initial Q-values. The initial Q-values guide the agent to the goal state in the early states of learning, so that Q-teaming updates Q-values efficiently. Therefore it saves exploration time to search for the goal state and has better performance than Q-learning. 1 present Speedup Q-learning algorithm to implement the speedup method. This algorithm is evaluated. in a grid-world domain and compared to Q-teaming.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.713-715
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• 2022

Video learning through YouTube has emerged as one of the most widely used instructional methods, yet relatively little research has been conducted on YouTube video users' willingness to use or behavior, so it is important to examine how to make and keep users' willingness to continue learning and to improve their retention rate for effective online learning. With reference to perceived value theory and utilizing an ECM perspective, the authors construct a model of YouTube video continuous learning intention and investigate the influence of perceived value and satisfaction on users' willingness to use YouTube videos for continuous learning.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.163-174
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• 2021

The purposes of this study were to investigate the influence of perceived learning value on employees' learning outcomes and to explore the mediating roles of work-family enrichment(WFE) and supervisor support in the relationship between perceived learning value and learning outcomes. The data was collected with employees who currently enrolled in any educational programs. The total data set was 309. The results showed that there was a positive and statistically significant relationship between perceived learning value and learning outcomes, and supervisor support, WFE and FWE played as moderators in the relationship between perceived learning value and learning outcomes.

• Journal of Korean Home Economics Education Association
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• v.26 no.3
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• pp.113-131
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• 2014

This study aimed to explore the effects of private tutoring expenses, parents' monitoring affection, their children's learning value and self-regulated learning abilities on middle-school boys' and girls' English Math academic achievement. The subjects were the 3rd middle-school 1,123 students taking the private tutoring of English and Math who participated in the Korea Child Youth Panel Surveys(KCYPS). The data were analyzed with descriptive statistics, correlations and hierarchical regressions. The main results of this study were as follows. Firstly, regardless of middle-school students' sex, as monthly average private tutoring expenses were more, the levels of parents' monitoring, and their children's learning value self-regulated learning abilities were higher, so middle-school students' academic achievement was higher. Secondly, regardless of middle-school students' sex, their self-regulated learning abilities were the highest predictors of English Math achievement. Also, their learning value and parents' monitoring influenced middle-school boys' English Math achievement in order. On the other hand, monthly average private tutoring expenses influenced middle-school girls' English Math achievement. Furthermore there were no moderating effects of parents' monitoring affection, their children's learning value and self-regulated learning abilities between monthly average private tutoring expenses and middle-school boys' and girls' English Math achievement. Finally, based on the results, the importance of parents and Home Economics was suggested in attaining middle-school students' higher academic achievement. Especially, Home Economics can play an important role of enhancing middle-school students' self-regulated learning abilities and learning value necessary for middle-school students' higher academic achievement.

• The Journal of Korean Association of Computer Education
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• v.15 no.4
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• pp.61-77
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• 2012

The purpose of this study was to examine the structural relationship among task value, self-efficacy, classroom goal structure, and academic emotions(enjoyment, fear, boredom) for promoting self-regulated learning in e-learning course. The results showed that task value, self-efficacy, class goal structure influenced academic emotions and self-regulated learning, and enjoyment had mediation effects among exogenous variables and self-regulated learning. The findings offer implications of facilitating self-regulated learning while considering academic emotions.

• Korea Trade Review
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• v.46 no.6
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• pp.191-209
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• 2021

In this paper, various time series analysis models and machine learning models are presented for long-term prediction of export growth rate, and the prediction performance is compared and reviewed by RMSE and MAE. Export growth rate is one of the major economic indicators to evaluate the economic status. And It is also used to predict economic forecast. The export growth rate may have a negative (-) value as well as a positive (+) value. Therefore, Instead of using the ReLU function, which is often used for time series prediction of deep learning models, the PReLU function, which can have a negative (-) value as an output value, was used as the activation function of deep learning models. The time series prediction performance of each model for three types of data was compared and reviewed. The forecast data of long-term prediction of export growth rate was deduced by three forecast methods such as a fixed forecast method, a recursive forecast method and a rolling forecast method. As a result of the forecast, the traditional time series analysis model, ARDL, showed excellent performance, but as the time period of learning data increases, the performance of machine learning models including LSTM was relatively improved.

• Journal of Elementary Mathematics Education in Korea
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• v.23 no.4
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• pp.405-435
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• 2019

Despite the recent emphasis on value research in mathematics education along with the significance of values from a new perspective, there has been a lack of research on the values perceived by teachers and students in Korea. This paper analyzes how fifth-grade students would perceive the values of a master teacher with expertise in elementary mathematics education after her teaching of mathematics and whether their values on mathematics learning would change. According to the study, the students recognized that the master teacher valued understanding, preview-review, picture, problem, and reason in mathematics learning. Among these, the value of understanding was perceived as the core value. An analysis of the students' values on general mathematics learning and personal mathematics learning showed that preview and review were the most important before and after the master teachers' teaching. An analysis of the changes in the values of students showed the greatest change in the value of understanding. Instead of accepting the values of the master teacher as it were, students actively reconstructed and maintained them. Based on these results, this paper has drawn implications regarding the consideration of students' values in mathematics learning.