• 한국정보교육학회:학술대회논문집
• /
• 2004.01a
• /
• pp.177-186
• /
• 2004

단위 시간 동안 이루어지는 교수-학습 활동이 이루어질 때, 교육적으로 추구하는 최선의 목표는 학습자가 정해진 목표를 달성하는 것이다. 이를 위해서 학습자가 수업에 실제로 참여하는 시간을 확보하는 일은 무엇보다도 중요하다. 학습과 관련성이 없거나 높지 않은 여러 가지 변인들로 인해 학습자의 학습 시간이 침해받는 일을 최소화하기 위한 해결 방안 수립이 필요한데, 시간과 인력을 불필요하게 동원하지 않으면서 빠른 시간 내에 원하는 결과를 관찰할 수 있는 시뮬레이션의 활용이 효과적이다. 시뮬레이션 모델 정립을 통해 학습자의 실제학습시간(Academic Learning Time)을 증진시킬 수 있는 방안을 모색하고자 한다

• Annual Conference on Human and Language Technology
• /
• 2021.10a
• /
• pp.211-214
• /
• 2021

다수의 태스크를 처리 가능하면서 일반화된 성능을 제공할 수 있는 모델을 구축하는 자연어 이해 분야의 연구에서는 멀티태스크 학습 기법에 대한 연구가 다양하게 시도되고 있다. 또한, 자연어 문장으로 작성된 문서들에는 대체적으로 시간에 관련된 정보가 포함되어 있을 뿐만 아니라, 문서의 전체 내용과 문맥을 이해하기 위해서 이러한 정보를 정확하게 인식하는 것이 중요하다. NLU 분야의 태스크를 더욱 정확하게 수행하려면 모델 내부적으로 시간정보를 반영할 필요가 있으며, 멀티태스크 학습 과정에서 추가적인 태스크로 시간적 관계정보를 추출하여 활용 가능하다. 본 논문에서는, 한국어 입력문장의 시간적 맥락정보를 활용할 수 있도록 NLU 태스크들의 학습 과정에서 시간관계 추출 태스크를 추가한 멀티태스크 학습 기법을 제안한다. 멀티태스크 학습의 특징을 활용하기 위해서 시간적 관계정보를 추출하는 태스크를 설계하고 기존의 NLU 태스크와 조합하여 학습하도록 모델을 구성한다. 실험에서는 학습 태스크들을 다양하게 조합하여 성능 차이를 분석하며, 기존의 NLU 태스크만 사용했을 경우에 비해 추가된 시간적 관계정보가 어떤 영향을 미치는지 확인한다. 실험결과를 통하여 전반적으로 멀티태스크 조합의 성능이 개별 태스크의 성능보다 높은 경향을 확인하며, 특히 개체명 인식에서 시간관계가 반영될 경우에 크게 성능이 향상되는 결과를 볼 수 있다.

• Journal of KIISE:Software and Applications
• /
• v.30 no.10
• /
• pp.983-991
• /
• 2003

The Web-based instruction on the internet provides lots of learners with the related information and knowledge beyond time and space. But in the Web-based instruction, there is a problem that the teaming process statuses for learners can be known only through an exam. This paper introduces a web monitoring method to check whether the learner has some problems in learning process and to be able to find out the students with the problems. In the method this paper proposes a learning time prediction model for predicting the proper next study time intervals based on the learner`s learning times and grades on Previous learning units. This method provides the educator with the learning Process statuses for learners. The Loaming prediction model for web-based monitoring can be used to stimulate learners to take the good teaming processes by sending automatically alerting messages if their real teaming times exceeds on his predicted learning time interval. The results of the estimation through case study on the web-based monitoring to use the teaming time prediction model show that most of on-line learners with Poor teaming process statuses get poor grades. In addition, the results show that learner`s poor habits keep going on without change.

• Journal of Korean Home Economics Education Association
• /
• v.17 no.3 s.37
• /
• pp.123-138
• /
• 2005

The purposes of this study were to develop ICT time management program for middle school students using in the creative extra curricular activities and to test the effect of this program in the knowledge and attitude aspects of time management. The contents of a middle school Home Economics curriculum and nine different textbooks were analyzed Based on these analyses 5 ICT lesson plans on time management were developed. The ICT instructional method was used to develop 5 lesson plans. The second grade middle school students as an experimental group participated in 5 ICT time management classes during middle school creative extra curricular activities. The control group of students who had some condition with the experimental group were taught by traditional instructional methods. After experiment, the changes in attitude and knowledge of time management of both groups were analyzed using Analysis of Covaziance. The significant improvements of attitude and knowledge on time management were found among the experimental group of students compared with control group of students. Thus the following conclusion is made the ICT time management instruction conducted in this study was found loaming more effective than traditional one in attitudes and knowledge of time management

• Journal of Industrial Convergence
• /
• v.20 no.11
• /
• pp.157-164
• /
• 2022

This study attempted to understand the mediating effect of learning time in the effect of academic burnout on self-esteem of middle school students. To this end, a survey of 1,045 middle school students in Gyeongsangnam-do was conducted on academic burnout, learning time, and self-esteem. It was analyzed in four ways through questionnaire responses. First, as a result of analyzing the differences according to the collective characteristics of academic burnout, learning time, and self-esteem, there was no difference between groups, and self-esteem was significantly different by gender and grade. Second, as a result of correlation analysis, academic burnout and learning time showed a negative correlation with self-esteem, and learning time and self-esteem showed a positive correlation. Third, as a result of regression analysis, all learning times were partially mediated in the effect of academic burnout on self-esteem. This not only directly affects the self-esteem of middle school students, but also indirectly through learning time. Fourth, in the analysis by gender, it was confirmed that male students had no statistically significant effect on self-esteem, but female students had a significant statistical effect on self-esteem, so only female students had a partial mediating effect. As a result of the analysis by grade, the effect of learning time on self-esteem was significant in the 1st and 2nd graders of middle school, but the effect of learning time on self-esteem was not significant in the 3rd graders of middle school. Through the survey of this study, it was suggested that education and counseling should be conducted in the middle school period, which is a rapid growth period, considering that academic burnout has a different effect on learning time and self-esteem by grade as well as gender approach.

• Journal of The Korean Association of Information Education
• /
• v.25 no.5
• /
• pp.813-824
• /
• 2021

To improve educational performance by analyzing the learning trends of adult learners of Open High Schools, various algorithm models using artificial intelligence were designed and performance was evaluated by applying them to real data. We analyzed Log data of 115 adult learners in the cyber education system of Open High Schools. Most adult learners of Open High Schools learned more than recommended learning time, but at the end of the semester, the actual learning time was significantly reduced compared to the recommended learning time. In the second half of learning, the participation rate of VODs, formation assessments, and learning activities also decreased. Therefore, in order to improve educational performance, learning time should be supported to continue in the second half. In the latter half, we developed an artificial intelligence algorithm models using Tensorflow to predict learning time by data they started taking the course. As a result, when using CNN(Convolutional Neural Network) model to predict single or multiple outputs, the mean-absolute-error is lowest compared to other models.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2000.10a
• /
• pp.281-284
• /
• 2000

시계열 예측에 있어서 과거의 측정치 보다 최근의 측정치가 미래의 측정치 예측에 중요한 영향을 미친다. 시계열 예측에 있어서 최근의 측정치와 과거의 측정치가 미래의 값을 예측하는 인자로서 차별화 되어 학습해야 할 것이다. 기존의 시계열에 대한 신경망 접근에서는 최근의 측정치에 대한 학습 패턴과 과거의 측정치에 대한 학습 패턴을 동일하게 학습하였다. 이 논문에서는 과거의 학습패턴과 최근의 학습 패턴을 학습 횟수 면에서 차별화 하였다. 이러한 학습을 이 논문에서는 차별학습이라 한다. 차별학습에서는 주어진 학습 패턴을 시간 순으로 나열하고 일정 개수로 분할한다. 시간의 역순에 의해 등차 또는 등비의 형태로 학습 횟수를 설정한다. 각 학습 패턴의 분말집단을 시간의 역순으로 일정 횟수를 감소시켜 학습 횟수를 설정하는 등차차별학습과 일정 비율로 감소시켜 학습횟수를 설정하는 등비차별학습을 소개한다. 기존의 신경망 접근 방법과 이 논문에서 제안한 신경망 접근방법을 비교하기 위해 Mackay-Galss 공식에 의해 인공적으로 생성된 시계열 데이터를 예로 사용하였다.

• The Journal of Korean Association of Computer Education
• /
• v.17 no.1
• /
• pp.65-73
• /
• 2014

The purpose of this study is to examine how time management, usefulness, and interest predict m-learning outcomes. For this study, 144 high school students participated in m-learning activities during science classes. After 5 week of classes, they responded the following surveys: time management, usefulness, interest, satisfaction, perceived achievement and learning persistence. Multiple regression analyses with correlation applied to this study as a data analysis method. The results showed that time management, usefulness, interest significantly predicted learning satisfaction and persistence. In addition, time management and usefulness significantly predicted perceived achievement, Therefore, these findings imply that time management, usefulness should be considered for designing m-learning activities in high school science class.

• Journal of Elementary Mathematics Education in Korea
• /
• v.11 no.2
• /
• pp.161-176
• /
• 2007

It is useless to say that time is precious and important. So it does when we emphasize the importance of studying the quality and efficiency of time in learning, especially in the learning of Mathematics. In this respect, this study aims to examine the overall structure of time application in the learning of Mathematics, understanding the state and problems of Mathematics education in respect of time application, and finally seeking to find the solutions for the problems. As a first step, the items below were examined for the solutions: First, the eight viewpoints of time in Mathematics education was examined and the meaning of each viewpoint was analysed. Second, the variables resulting from teachers was examined. The preconditions for mathematics education, the attitude towards Mathematics classes, viewpoints of mathematics, the forms of self-expression, the way of utterance can be considered as the variables mentioned above. Third, the variables resulting from students was examined. Learning attitude, specific activity(both meaningful and meaningless), practical uses of teaching tools, game activities, the ways of communication and problem solving can be examined as well. In conclusion, it needs to be stressed that Mathematics class should be the meaningful time for learners, parents, and teachers. The class should guarantee the satisfaction of the learners. In other words, even if physical time is applied the same to everyone, it may differ in degree of quality and value of time application according to the way one spends the time.

• KIPS Transactions on Computer and Communication Systems
• /
• v.10 no.5
• /
• pp.155-162
• /
• 2021

n-step TD learning is a combination of Monte Carlo method and one-step TD learning. If appropriate n is selected, n-step TD learning is known as an algorithm that performs better than Monte Carlo method and 1-step TD learning, but it is difficult to select the best values of n. In order to solve the difficulty of selecting the values of n in n-step TD learning, in this paper, using the characteristic that overestimation of Q can improve the performance of initial learning and that all n-step returns have similar values for Q ≈ Q^*, we propose a new learning target, which is composed of the maximum and the mean of all k-step returns for 1 ≤ k ≤ n. Finally, in OpenAI Gym's Atari game environment, we compare the proposed algorithm with n-step TD learning and proved that the proposed algorithm is superior to n-step TD learning algorithm.