• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.345-347
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• 2021

본 연구는 최근 Horizon report 2020에서 소개하는 고등교육 분야에 영향을 줄 트렌드와 기술 사례들을 수집하여 고등교육의 미래 동향과 학습 분석적 측면에서 분석하였다. 고등 교육이 교수·학습을 중심으로 영향을 줄 트렌드로는 기술적 트렌드, 고등교육 트렌드, 경제적 트렌드 등이 있으며 기술 사례로는 적응형 학습, 인공지능/머신기능 기술의 교육적 활용, 학업 성취도 분석을 위한 학습 분석, 확장 현실 기술 등이 있다. 이 중 학습 분석 기술은 학습자의 학업 성취도를 높이기 위한 방법으로 사용되는 유용한 기술이기도 하며 고등교육에 영향을 줄 가장 핵심 트렌드이기도 하다. 그러나 현실 학습에 적용하는데는 데이터 격차, 품질 문제, 개인 정보보호에 대한 문제 등 윤리적 문제를 함께 고려해야한다. 본 연구를 기반으로 한 향후 학습 분석 시스템을 개발하고자 한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.3
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• pp.9-15
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• 1998

This paper presents an adaptive learning control method for unknown nonlinear systems by combining neuro control and iterative learning control techniques. In the present control system, an iterative learning controller (ILC) is used for a process of short term memory involved in a temporary adaptive and learning manipulation and a short term storage of a specific temporary action. The learning gain of the iterative learning law is estimated by using a neural network for an unknown system except relative degrees. The control informations obtained by ILC are transferred to a long term memory-based feedforward neuro controller (FNC) and accumulated in it in addition to the previously stored infonnations. This scheme is applied to a two link robot manipulator through simulations.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.17-25
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• 2006

An intelligent game has been studied for some time, and the main purpose of the study was to win against human by enhancing game skills. But some commercial games rather focused on adaptation of the user's behavior in order to bring interests on the games. In this study, we are suggesting an adaptive reinforcement learning algorithm, which focuses on the adaptation of user behavior. We have designed and developed the Othello game, which provides large state spaces. The evaluation of the experiment was done by playing two reinforcement learning algorithms against Min-Max algorithm individually. And the results show that our approach is playing more improved learning rate, than the previous reinforcement learning algorithm.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.255-260
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• 2021

This study tried to investigate the effects of the adaptation of middle-aged and elderly adult learners to college life on happiness. For this purpose, a questionnaire survey and analysis were conducted on 321 middle-aged and older adults studying at two-year and four-year colleges in Daegu and Gyeongbuk Province, and the results are as follows. First, college life adaptation according to the general characteristics of middle-aged and elderly learners are higher for those in their 50s and 2nd grade in good health condition. Happiness was the highest women, 60s and those in the form of households where only couples live. Second, there is a static correlation between the adaptation of middle-aged and elderly adult learners to college life and happiness, and the correlation between satisfaction with internal growth and satisfaction with meaning was the highest. Third, it was found that middle-aged and elderly adults' adaptation to college life influenced happiness, and the adaptation to adult student relationships, which is the lower part of the adaptation to college life, had the greatest impact on happiness. The above research results suggest that the various positive experiences experienced in university life can affect happiness by easing student relationships, psychological stability, and physical tension, and improving one's own satisfaction with internal growth.

• Journal of the International Relations & Interdisciplinary Education
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• v.4 no.1
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• pp.57-83
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• 2024

This study aimed to investigate the impact of scores on the Test of Proficiency in Korean (TOPIK) among foreign exchange students on academic adaptation. Recruited students, approved by the Institutional Review Board (IRB), totaled seven, and their interview contents were analyzed using a comprehensive analysis procedure based on pragmatic eclecticism (Lee, Kim, 2014), utilizing six stages. As a result, factors influencing academic adaptation of Korean language learners for academic purposes were categorized into three dimensions: academic, daily life, and psychological-emotional aspects. On the academic front, interviewees pointed out difficulties in adapting to specialized terminology and studying in their majors, as well as experiencing significant challenges with Chinese characters and Sino-Korean words. Next, from a daily life perspective, even participants holding advanced TOPIK scores faced difficulties in adapting to university life, emphasizing the necessity of practical expressions and extensive vocabulary for proper adjustment to Korean life. Lastly, within the psychological-emotional dimension, despite being advanced TOPIK holders, they were found to experience considerable stress in conversations or presentations with Koreans. Their lack of knowledge in social-cultural and everyday life culture also led to linguistic errors and contributed to psychological-emotional difficulties, despite proficiency in Korean. Based on these narratives, the conclusion was reached that in order to promote the academic adaptation of Korean language learners, it is essential to provide opportunities for Korean language learning. With this goal in mind, efforts should be directed towards enhancing learners' academic proficiency in their majors, improving Korean language fluency, and fostering interpersonal relationships within the academic community. Furthermore, the researchers suggested as a solution to implement various extracurricular activities tailored for foreign learners.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.37-44
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• 2021

This study is about a strategy to analyze learning activities in an intelligent learning system. To this end, the conceptual definition of the intelligent learning system and the type of learning using the intelligent learning system were analyzed. The learning types were presented as individual, adaptive, competency-based, and blended learning, and although there are some differences, most of them have similar characteristics. In addition, learning activity analysis is based on data such as mouse clicks, keyboarding, and uploads generated by the system. Through this, basic analysis such as viewing time and number of uploads can be performed. However, more diverse learning analysis is needed for personalization and adaptation. It can judge not only learning attitude and achievement level, but also metacognitive level and creativity level. However, since the level of metacognition includes complex human cognitive activities, the teacher's intervention is required in the judgment of the intelligent learning system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.12
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• pp.1895-1902
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• 2001

This paper gives an overview of the relationships between methods of loaming and adaptive control. It is the objective of this paper to develop adaptive learning control algorithms that combine the advantages of adaptive control with those of leaning control to the extent possible for the type of system model used. The robustness of this adaptive loaming control with respect to reinitialization errors and fluctuation of dynamics from disturbance is analyzed extensively. Simulation results have shown to verify the effectiveness of the proposed control algorithm.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.390-396
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• 1998

본 논문은 퍼지 논리 제어기(FLC)의 근사화 능력과 제어 성능을 동시에 향상시키는 정확한 무게 중심(Center Of Gravity; COG) 비퍼지화기를 제안한다. 본 논문은 비퍼지화 과정이 최적 선택의 한 과정이며 비퍼지화 방법의 적절한 선택이다. 제안한 COG 비퍼지화기의 정확성은 출력 소속 함수를 여러 개의 설계 파라메터(중신, 폭, 변경자(modifier))로 나타내고 이들 설계 파라메터들을 학습과 진화의 Lamarckian 상호 적응에 의하여 갱신함으로써 얻어진다. 이러한 학습과 진화의 상호 적응은 학습하지 않는 경우 보다 빠르게 최적 COG 비퍼지화기를 얻도록 하며, 보다 넓은 범위의 탐색으로최적해를 찾을 가능성을 높여 준다. 제안한 설계 방법은 목적 함수의 가중치를 조절하여 높은 근사화 능력, 높은 제어 성능, 또는 이들간의 균형된 성능을 갖는 다양한 특정 응용형(Application-specific)COG 비퍼지화기를 제공한다. 제안한 상호적응 COG 비퍼지화기의 설계방법을 트럭 후진 주차 제어 문제에 적용하여, 각각 시스템 오차와 평균 추적 거리로 나타내어진 근사화 능력과 제어 성능을 기존의 COG 비퍼지화기와 비교한다.

• The Journal of the Acoustical Society of Korea
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• v.13 no.1E
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• pp.25-36
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• 1994

A problem of making a neural network learning self-adaptive to the training set supplied is addressed in this paper. This arises from the aspect in choice of an adequate stepsize for the update of the current weigh vectors according to the training pairs. Related issues in this attempt are raised and fundamentals in neural network learning are introduced. In comparison to the most popular back-propagation scheme, the usefulness and superiority of the proposed weight update algorithm are illustrated by examing the identification of unknown nonlinear systems only from measurements.

• The Journal of Information Technology
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• v.5 no.2
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• pp.55-67
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• 2002

This paper presents an adaptive back propagation algorithm that update the learning parameter by the generated error, adaptively and varies the number of hidden layer node. This algorithm is expected to escaping from the local minimum and make the best environment for convergence to be change the number of hidden layer node. On the simulation tested this algorithm on two learning pattern. One was exclusive-OR learning and the other was $7{\times}5$ dot alphabetic font learning. In both examples, the probability of becoming trapped in local minimum was reduce. Furthermore, in alphabetic font learning, the neural network enhanced to learning efficient about 41.56%~58.28% for the conventional back propagation. and HNAD(Hidden Node Adding and Deleting) algorithm.