• 유통과학연구
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• 제21권4호
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• pp.47-56
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• 2023

Purpose: the research aims to analyze the impact of the distribution of knowledge through online learning on the intellectual potential of PhD students and produce recommendations for policy to improve intellectual capacity. During the literature review, it was determined that a large number of studies examined the impact of online learning on the quality of education at different levels. Research design, data and methodology: the research methodology is based on subjective assessment and studying the students' opinions. The basis of the study was a comprehensive analysis of primary data obtained through a sociological survey of PhD students. 324 respondents from humanitarian, medical and natural faculties participated in the survey. Results: the study revealed that online learning helps increase students' intellectual potential. PhD students had a positive attitude towards the transition from traditional education to online learning. It should be noted that, according to the results, the most popular gadgets were laptops and smartphones, which were characterized by high mobility and ease of use. Based on the obtained results, recommendations were developed for the formation of online learning with a focus on increasing students' intellectual potential. Conclusions: based on the results of the assessment of educational and innovative potential, policy recommendations and further research in this area were proposed.

• Educational Technology International
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• 제17권2호
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• pp.253-271
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• 2016

This study investigated the effect of generative concept maps according to learning achievements and cognitive load. A total of 78 students in the first grade of middle school participated in this study. Before the experimental treatment was implemented, students had to fill out a questionnaire assessing prior knowledge. The study was designed where all the students were presented the same learning contents regarding photosynthesis; however, the two experimental groups were provided with different concept map methods: a learner-generative concept map (GCM) and an instructor-provided concept map (PCM). GCM students were asked to make a concept map by themselves in small groups while they are reading material. PCM students were instructed to study in small groups in order to read the material; however, they were provided a concept map developed by their teacher. The control group (CG) had the teacher present the learning contents in traditional lecture format with no accompanying concept map. The results show that there were significant differences in the achievements among the groups. CG showed higher achievement than both the experimental groups. There was also a significant difference in cognitive load. Although the GCM group did not obtain higher achievement than the other groups, the GCM group showed higher mental effort and lower physical fatigue than the other groups. The GCM group might have invested more effort to find and connect ideas when drawing their concept map with peers which is unlike the conditions for the PCM group and CG. In conclusion, we should consider applying GCM in teaching and learning design in order to increase learning achievement and decrease extraneous cognitive load.

• Journal of Korea Artificial Intelligence Association
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• 제2권1호
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• pp.25-30
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• 2024

Kodály hand signs are symbols that intuitively represent pitch and note names based on the shape and height of the hand. They are an excellent tool that can be easily expressed using the human body, making them highly engaging for children who are new to music. Traditional hand signs help beginners easily understand pitch and significantly aid in music learning and performance. However, Kodály hand signs have distinctive features, such as the ability to indicate key changes or chords using both hands and to clearly represent accidentals. These features enable the effective use of Kodály hand signs. In this paper, we aim to investigate the changes in recognition rates according to the complexity of scales by creating a device for learning Kodály hand signs, teaching simple Do-Re-Mi scales, and then gradually increasing the complexity of the scales and teaching complex scales and children's songs (such as "May Had A Little Lamb"). The learning device utilizes accelerometer and bending sensors. The accelerometer detects the tilt of the hand, while the bending sensor detects the degree of bending in the fingers. The utilized accelerometer is a 6-axis accelerometer that can also measure angular velocity, ensuring accurate data collection. The learning and performance evaluation of the Kodály learning device were conducted using Python.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권2호
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• pp.494-510
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• 2024

Internet users are exposed to sophisticated cyberattacks that intrusion detection systems have difficulty detecting. Therefore, research is increasing on intrusion detection methods that use artificial intelligence technology for detecting novel cyberattacks. Unsupervised learning-based methods are being researched that learn only from normal data and detect abnormal behaviors by finding patterns. This study developed an anomaly-detection method based on unsupervised machines and deep learning for a network intrusion detection system (NIDS). We present a hybrid anomaly detection approach based on unsupervised learning techniques using the autoencoder (AE), Isolation Forest (IF), and Local Outlier Factor (LOF) algorithms. An oversampling approach that increased the detection rate was also examined. A hybrid approach that combined deep learning algorithms and traditional machine learning algorithms was highly effective in setting the thresholds for anomalies without subjective human judgment. It achieved precision and recall rates respectively of 88.2% and 92.8% when combining two AEs, IF, and LOF while using an oversampling approach to learn more unknown normal data improved the detection accuracy. This approach achieved precision and recall rates respectively of 88.2% and 94.6%, further improving the detection accuracy compared with the hybrid method. Therefore, in NIDS the proposed approach provides high reliability for detecting cyberattacks.

• 한국학교수학회논문집
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• 제4권2호
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• pp.125-134
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• 2001

It is necessary that at any rate we try to decrease underachievers by learning deficiency in mathematics to extreme limits under circumstances that mathematics becomes more requisite daily in the 21st century's informative society. However, the traditional teaching method causes a lot of problems in elevating the needed ability for the newly changing society. Accordingly, for the purpose of letting underachievers by learning deficiency have much interest in mathematics, seek the qualitative elevation, have the feelings of self-confidence and accomplishments, escape from desperation, and also teachers choose the activities of small groups, design teaching plans, apply those to teaching-learning activities and finally verify the effect, this researcher sets up a hypothesis as follows: 1. The teaching method through small groups will be effective for the accomplishments of underachievers in mathematics. 2. Its method will bring out the meaningful change in the emotional areas of mathematics. Therefore, so as to prove the above hypothesis, the results through the theoretical approach and practicing teaming by small groups have turned out to be positive.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 추계학술대회논문집
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• pp.23-27
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• 2007

Many trials have been used to model room impulse responses, all attempting to provide efficient representations of room acoustics. The traditional model designs for room impulse response seem to fail in accuracy, controllability, or computational efficiency. In time domain, a room impulse response is generally considered as the combination of three parts having different acoustic characteristics, initial time delay, early reflection, and late reverberation. This paper introduces new learning hybrid model for the room impulse response. In this proposed model, those three parts are modeled using different models with learning algorithms that determine the length or boundary of each model in the hybrid model. By the simulation with measured room impulse responses, it was examined that the performance of proposed model shows the best efficiency in views of both the parameter numbers and modeling error.

• 한국소음진동공학회논문집
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• 제18권3호
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• pp.361-367
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• 2008

Many trials have been used to model room impulse responses, all attempting to provide efficient representations of room acoustics. The traditional model designs for room impulse response seem to fail in accuracy, controllability, or computational efficiency. In the time domain, room impulse responses are generally considered as combination of the three Parts having different acoustic characteristics, initial time delay, early reflection, and late reverberation. This paper introduces new learning hybrid model for room impulse responses. In this proposed model, those three parts are modeled using different models with learning algorithms that determine the boundary of each model in the hybrid model. By the simulation with measured room impulse responses, the performance of proposed model shows the best efficiency in views of computational burden and modeling error.

• 컴퓨터교육학회논문지
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• 제6권2호
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• pp.165-173
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• 2003

웹 기반 교육은 시간적, 공간적으로 분산되어져 있는 학습자들이 웹을 통해 학습이 이루어지는 형태로써 전통적인 학습 환경과 달리, 학습자의 적극적인 참여의지가 필요하다. 여기에서 참여의지는 학습동기의 중요한 한 측면으로 볼 수 있다. 그러나 기존의 웹 기반 수업 설계는, 학습자의 인지적인 측면만을 고려하는 것이 대부분이다. 따라서 본 연구에서는 학습자의 학습동기를 촉진하기 위한 '감성게시판'의 설계 전략을 제시하고자 한다.

• IEIE Transactions on Smart Processing and Computing
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• 제3권4호
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• pp.234-239
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• 2014

This paper presents an empirical study on selecting a small amount of useful unlabeled data to improve the classification accuracy of semi-supervised learning algorithms. In particular, a hybrid method of unifying the simply recycled selection method and the incrementally-reinforced selection method was considered and evaluated empirically. The experimental results, which were obtained from well-known benchmark data sets using semi-supervised support vector machines, demonstrated that the hybrid method works better than the traditional ones in terms of the classification accuracy.

• 한국초등과학교육학회지:초등과학교육
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• 제29권4호
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• pp.474-483
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• 2010

In this study, we investigated preservice elementary school teachers' awareness of students' misconceptions about several science topics, and the variables influencing their awareness. Seniors (N=106) from an university of education were asked to predict elementary school students' misconceptions on science topics such as phase changes and dissolution. Their conceptions about teaching and learning were also measured. The results indicated that the preservice teachers' predictions about the kinds and/or the ratios of students' misconceptions were different from those reported in previous studies. The low level preservice teachers in terms of the degrees of possessing traditional conception about teaching and learning predicted more students' common misconceptions. The degrees of preservice teachers' constructivist conception about teaching and learning and their major, however, did not significantly influence the numbers of common misconceptions predicted.