• Human Ecology Research
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• v.61 no.4
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• pp.663-671
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• 2023

This study aimed to determine whether the achievement motivation of adolescents from multicultural families in their third year of middle school influenced their adaptation to school learning activities. It also explored the mediating effect of career attitude on achievement motivation and adaptation to school learning activities. An analysis was performed on data obtained from students in the third grade of middle school who participated in the sixth wave of the Multicultural Adolescents Panel Study (MAPS). The main findings were as follows. Firstly, achievement motivation exhibited a positive correlation with both career attitude and adaptation to school learning activities. Secondly, the achievement motivation of adolescents from multicultural families and their career attitude both exerted a positive effect on their adaptation to school learning activities. Thirdly, the mediating effect of career attitude on the relationship between adaptation to school learning activities and achievement motivation of adolescents from multicultural families was verified.

• Journal of Convergence for Information Technology
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• v.9 no.6
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• pp.104-111
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• 2019

In this study, we examined the effects of University adaptation on career adaptation through self-leadership and learning commitment, and identified the regulatory effects of demographic characteristics (sex, grade, grade level, and willingness to work). To this end, we analyzed the data for 289 college students. The results of the study are as follows. First, adaptation to University life has a significant impact on learning commitment and self-leadership. However, adaptation to University life has an indirect effect on learning commitment and self-leadership rather than directly affecting career adaptation. Second, demographic characteristics have a regulatory effect on the path through which University adaptation affects career adaptation through self-leadership and learning commitment. The factors that were regulated were age, grade, and willingness to work. Therefore, in order to adapt to university life and adapt to career, we developed a program to improve self-leadership and learning commitment, and suggested that customized guidance is needed considering the differences in personal characteristics such as gender and academic background in university life and career counseling.

• Journal of Engineering Education Research
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• v.16 no.6
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• pp.11-18
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• 2013

The purpose of this study is to verify the effects of self-respect, academic self-efficacy, and career maturity on student adaptation to college and learning persistence. For this study, a web survey was conducted on the students who were in college of engineering at D college in Seoul. A total of 702 samples were analyzed for this research. The major findings of this study are as follows. First, all variables (self-respect, academic self-efficacy, career maturity) had positive effects on student adaptation to college significantly. Secondly, self-respect and academic self-efficacy had positive effects on learning persistence except career maturity. Thridly, the mediation analyses revealed that the relations between learning persistence and self-respect, academic self-efficacy, and career maturity were partially mediated by student adaptation to college. Finally, student adaptation to college had also positive effects on learning persistence. The results indicate a need to enhance student adaptation to college and design programs that support learning persistence for university students.

• Journal of Korea Multimedia Society
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• v.6 no.4
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• pp.676-684
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• 2003

eLearning can be defined as an approach to teaching and teaming that utilises Internet technologies to communicate and collaborate in an educational context. This includes technology that supplements traditional classroom training with web-based components and learning environments where the educational process is experienced online. The use of hypertext as an educational tool has a very rich history. The advent of the internet and one of its major application, the world wide web (WWW), has given a tremendous boost to the theory and practice of hypermedia systems for educational purposes. However, the web suffers from an inability to satisfy the heterogeneous needs of a large number of users. For example, web-based courses present the same static teaming material to students with widely differing knowledge of the subject. Adaptive hypermedia techniques can be used to improve the adaptability of eLearning. In this paper we report an approach to the design a unified implementation framework suitable for web-based eLearning that accommodates the three main dimensions of hypermedia adaptation: content, navigation, and presentation. The framework externalises the adaptation strategies using XML notation. The separation of the adaptation strategies from the source code of the eLearning software enables a system using the framework to quickly implement a variety of adaptation strategies. This work is a part of our more general ongoing work on the design of a framework for adaptive content delivery. parts of the framework discussed in this paper have been imulemented in a commercial eLearning engine.

• Journal of Broadcast Engineering
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• v.27 no.4
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• pp.511-518
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• 2022

Supervised learning based on deep learning has made a leap forward in various application fields. However, many supervised learning methods work under the common assumption that training and test data are extracted from the same distribution. If it deviates from this constraint, the deep learning network trained in the training domain is highly likely to deteriorate rapidly in the test domain due to the distribution difference between domains. Domain adaptation is a methodology of transfer learning that trains a deep learning network to make successful inferences in a label-poor test domain (i.e., target domain) based on learned knowledge of a labeled-rich training domain (i.e., source domain). In particular, the unsupervised domain adaptation technique deals with the domain adaptation problem by assuming that only image data without labels in the target domain can be accessed. In this paper, we explore the unsupervised domain adaptation techniques.

• Journal of Practical Engineering Education
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• v.15 no.2
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• pp.351-356
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• 2023

This study was conducted to identify the structural causal relationship between the quality of college education service, college life adaptation, and learning competency perceived by undergraduate probation students. To achieve this research purpose, data were collected and analyzed through the development of questionnaires for undergraduate students and online questionnaires. The research results are as follows. First, it was found that university administrative service had a negatively significant effect on college life adaptation and learning competency. Second, it was found that the curriculum had a positive and significant effect on learning competencies through college life adaptation. Third, it was found that adaptation to college life had a statically significant effect on learning competency. These research results suggest that it is necessary to support the improvement of college life adaptation ability through the operation of university administrative services and curriculum tailored to students with academic probation.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.245-254
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• 2022

This study is a study to empirically verify the mediating effect on college life adaptation and career preparation behavior of college students. The purpose of this study is to empirically analyze the multi-mediated effects of major satisfaction, job stress, and self-directed learning. For this study, 216 university students were enrolled. For the collected data, SPSS Process macro was used. The result is as follows. First, there were multiple parallel mediating effects and multiple serial mediating effects on major satisfaction, job stress, and self-directed learning between college life adaptability and career preparation behavior. Second, the path of simple mediation and double mediation effect was found between college life adaptation and career preparation behavior. Based on the research, the necessity of revitalizing the program for revitalization of teaching activities and industry-academic cooperation activities in the major field and improvement of career preparation behavior and university life adaptation ability and follow-up research were suggested.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.326-328
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• 1994

A modified Kohonen's simple Competitive Learning(SCL) algorithm which has binary reinforcement function and a constant adaptation gain is proposed. In contrast to the time-varing adaptation gain of the original Kohonen's SCL algorithm, the proposed algorithm uses a constant adaptation gain, and adds a binary reinforcement function in order to compensate for the lowered learning ability of SCL due to the constant adaptation gain. Since the proposed algorithm does not have the complicated multiplication, it's digital hardware implementation is much easier than one of the original SCL.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.5
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• pp.407-415
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• 2016

Recent wireless communication trends have emphasized the importance of energy-efficient transmission. In this paper, link adaptation with machine learning mechanism for maximum energy efficiency in multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM) wireless system is considered. For reflecting frequency-selective MIMO-OFDM channels, two-dimensional capacity(2D-CAP) feature space is proposed. In addition, machine-learning-based bit and power adaptation(ML-BPA) algorithm that performs classification-based link adaptation is presented. Simulation results show that 2D-CAP feature space can represent channel conditions accurately and bring noticeable improvement in link adaptation performance. Compared with other feature spaces, including ordered postprocessing signal-to-noise ratio(ordSNR) feature space, 2D-CAP has distinguished advantages in either efficiency performance or computational complexity.

• International journal of advanced smart convergence
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• v.8 no.4
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• pp.68-74
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• 2019

Along with the deeper architecture in the deep learning approaches, the need for the data becomes very big. In the real problem, to get huge data in some disciplines is very costly. Therefore, learning on limited data in the recent years turns to be a very appealing area. Meta-learning offers a new perspective to learn a model with this limitation. A state-of-the-art model that is made using a meta-learning framework, Meta-SGD, is proposed with a key idea of learning a hyperparameter or a learning rate of the fast adaptation stage in the outer update. However, this learning rate usually is set to be very small. In consequence, the objective function of SGD will give a little improvement to our weight parameters. In other words, the prior is being a key value of getting a good adaptation. As a goal of meta-learning approaches, learning using a single gradient step in the inner update may lead to a bad performance. Especially if the prior that we use is far from the expected one, or it works in the opposite way that it is very effective to adapt the model. By this reason, we propose to add a weight term to decrease, or increase in some conditions, the effect of this prior. The experiment on few-shot learning shows that emphasizing or weakening the prior can give better performance than using its original value.