• Journal of The Korean Association For Science Education
• /
• v.25 no.5
• /
• pp.541-546
• /
• 2005

In order to suggest instructional strategy and learning guidance in science education, the purpose of this study was to classify middle school students by learning style and then examine student's science process skills via those learning styles. The Student Learning Style Questionnaire (SLSQ) and the Test of Science Process Skills (TSPS) were given to 340 ninth graders. Their learning styles were classified into three categories, that were divided into two opposing types: independent/ dependent, collaborative/ competitive, and participant/ avoidant. The results showed the following : 1) Students of the dependent, collaborative, and participant type out numbered ones of the independent, competitive, and avoidant type. 2) Gender differences showed that male students of the competitive, participant, dominant type totalled more than the female students of the collaborative, avoidant type. Furthermore, 3) For students of the independent, competitive, participant type, science process skills were higher than those of the dependent, collaborative, avoidant type.

• The Journal of Korean Academic Society of Nursing Education
• /
• v.19 no.4
• /
• pp.549-557
• /
• 2013

Purpose: The purpose of this study was to investigate the effects of self-directed learning ability and creativity on college adjustment in nursing students. Method: Data were collected by questionnaires from 148 nursing students in October, 2010. Collected data were analyzed using descriptive statistics, independent t-test, one-way ANOVA, Pearson's correlation coefficient and stepwise multiple regression. Results: A positive correlation was found for college adjustment with self-directed learning ability and creativity. Self-directed learning ability and major satisfaction were significant predictors of college adjustment. The model explained 44.1% of the valuables. Conclusion: The results of this study suggest that self-directed learning be considered when developing strategies to increase college adjustment in nursing students.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.173.5-173
• /
• 2001

Q-Learning is a most widely used reinforcement learning, which addresses the question of how an autonomous agent can learn to choose optimal actions to achieve its goal about any one problem. Q-Learning can acquire optimal control strategies from delayed rewards, even when the agent has no prior knowledge of the effects of its action in the environment. If agent has an ability using previous knowledge, then it is expected that the agent can speed up learning by interacting with environment. We present a novel reinforcement learning method using domain knowledge, which is represented by problem-independent features and their classifiers. Here neural network are implied as knowledge classifiers. To show that an agent using domain knowledge can have better performance than the agent with standard Q-Learner. Computer simulations are ...

• International Journal of Computer Science & Network Security
• /
• v.22 no.11
• /
• pp.115-120
• /
• 2022

The main purpose of the study is to identify the key aspects of the use of innovative distance learning technologies in the training of biology students. Currently, there is a modernization, the evolution of the education system from a classical university to a virtual one, from lecture material teaching to computer educational programs, from a book library to a computer one, from multi-volume paper encyclopedias to modern search databases. During studies in higher education, distance learning ensures the delivery of information in an interactive mode through the use of information and communication technologies. The main disadvantage of distance learning is the emotional interaction of the teacher with students. It is necessary to increase the level of methodological developments for independent studies of students. The methodology includes a number of theoretical methods. Based on the results of the study, the main elements of the use of innovative distance learning technologies in the training of biology students were identified.

• Journal of Engineering Education Research
• /
• v.13 no.6
• /
• pp.87-98
• /
• 2010

In this research, we analyzed the effects of the independent research program on the educational experience of undergraduate students in a research-centered university setting. The independent research program was developed to provide undergraduate students with opportunities to engage in self(student)-initiated, self-regulated and self-responsible research projects. We hypothesized that outcomes of the program would be utilized as a baseline information in formulating the strategies for improvement of the undergraduate curriculum. Eighty three undergraduate students participated in the program during the period of 2003-2009. In order to evaluate results of the program, we carried out survey and in-depth interviews with the participants. According to the participant reports, the independent research program has helped them to develop self-managed research abilities and problem solving skills. They also indicate that the program has offered them the opportunities to survey the various major fields transcending different domains, so as to help them to contemplate on their future career choices. We suggest that such information may provide an essential guideline for developing an innovative undergraduate curriculum.

• The Journal of the Acoustical Society of Korea
• /
• v.40 no.2
• /
• pp.148-154
• /
• 2021

Text-Independent speaker verification needs to extract text-independent speaker embedding to improve generalization performance. However, deep neural networks that depend on training data have the potential to overfit text information instead of learning the speaker information when repeatedly learning from the identical time series. In this paper, to prevent the overfitting, we propose a segment unit shuffling layer that divides and rearranges the input layer or a hidden layer along the time axis, thus mixes the time series information. Since the segment unit shuffling layer can be applied not only to the input layer but also to the hidden layers, it can be used as generalization technique in the hidden layer, which is known to be effective compared to the generalization technique in the input layer, and can be applied simultaneously with data augmentation. In addition, the degree of distortion can be adjusted by adjusting the unit size of the segment. We observe that the performance of text-independent speaker verification is improved compared to the baseline when the proposed segment unit shuffling layer is applied.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1997.04a
• /
• pp.68-75
• /
• 1997

This paper presents a new approach to the design of neural-fuzzy controller for the speed and azimuth control of a track vehicle. The proposed control scheme uses a Gaussian function as a unit function in the frzzy-neural network, and back propagaton algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a track vehicle driven by two independent wheels.

• Journal of the Korean Society for Precision Engineering
• /
• v.20 no.7
• /
• pp.155-162
• /
• 2003

We propose a new technique far real-tine controller design of a autonomous cruise mobile robot with three drive wheels. The proposed control scheme uses a Caussian function as a unit function in the fuzzy neural network. and a back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-foray. The control performance of the proposed controller is illustrated by performing the computer simulation for trajectory tracking of the speed and azimuth of a autonomous cruise mobile robot driven by three independent wheels.

• Journal of the Korean Society of Industry Convergence
• /
• v.17 no.2
• /
• pp.69-76
• /
• 2014

This paper proposes a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, and back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2001.04a
• /
• pp.250-254
• /
• 2001

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy-neural network, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.