• 제목/요약/키워드: Learning Functions

검색결과 1,194건 처리시간 0.023초

Analysis of Preservice Elementary Teachers' Lesson Plans

  • Hong, Jung-Lim
    • 한국과학교육학회지
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    • 제24권1호
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    • pp.171-182
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    • 2004
  • The purpose of this study is to analyze lesson plans from third to sixth grades of science and to find out teaching strategies in respects of learning functions provided by preservice elementary teachers in education university. On the whole, to control students' learning process preservice teachers used more shared-regulation strategy than strong teacher-regulation one. Teaching activities for regulative learning function were most used in strategy of strong teacher-regulation, and in strategy of shared-regulation those for cognitive learning functions were most used. But teaching activities for affective learning functions were used a little considered in both teaching strategies. In introduction step of instruction, affective and regulative learning functions were more instructed by strong teacher-regulation strategy and cognitive learning functions were more instructed by shared-regulation strategy. The affective, cognitive, and regulative learning functions were largely planned by shared-regulation teaching strategy in development. The regulative learning functions were planned by strong teacher-regulation strategy than by shared-regulation strategy and affective learning functions were considered a little bit in consolidation. There was a tendency that strong teacherregulation strategy was increased in lessons for fifth and sixth grade.

기업 내 e-learning 학습 환경에서 학습양식, 튜터기능, 학습성취도의 상관관계 (Interrelation among Learning Style, Tutoring Function, and Learning Achievement in an Enterprise e-learning Environment)

  • 유규식;최인준;한성년
    • 산업공학
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    • 제19권4호
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    • pp.324-332
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    • 2006
  • It is believed that each learner has a preferred method to acquire and manage knowledge according to her/his learning style which influences learning achievement directly. The purpose of this paper is to statistically analyze relationships among individual learning styles, tutoring functions, and learning achievement in an e-learning environment. 524 survey results from participants of enterprise e-learning classes are classified into total group and superior group. T-Test and ANOVA analyses are carried between learning style and learning achievement and between learning style and preferred tutoring functions. The analysis results show that individual learning styles do not contribute to learning achievement while they are strongly related to preferences for some of tutoring functions. These results can be used to identify limitation of current e-learning practice and design better e-learning systems, especially, supporting appropriate tutoring functions for different types of learners.

Function Approximation Based on a Network with Kernel Functions of Bounds and Locality : an Approach of Non-Parametric Estimation

  • Kil, Rhee-M.
    • ETRI Journal
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    • 제15권2호
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    • pp.35-51
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    • 1993
  • This paper presents function approximation based on nonparametric estimation. As an estimation model of function approximation, a three layered network composed of input, hidden and output layers is considered. The input and output layers have linear activation units while the hidden layer has nonlinear activation units or kernel functions which have the characteristics of bounds and locality. Using this type of network, a many-to-one function is synthesized over the domain of the input space by a number of kernel functions. In this network, we have to estimate the necessary number of kernel functions as well as the parameters associated with kernel functions. For this purpose, a new method of parameter estimation in which linear learning rule is applied between hidden and output layers while nonlinear (piecewise-linear) learning rule is applied between input and hidden layers, is considered. The linear learning rule updates the output weights between hidden and output layers based on the Linear Minimization of Mean Square Error (LMMSE) sense in the space of kernel functions while the nonlinear learning rule updates the parameters of kernel functions based on the gradient of the actual output of network with respect to the parameters (especially, the shape) of kernel functions. This approach of parameter adaptation provides near optimal values of the parameters associated with kernel functions in the sense of minimizing mean square error. As a result, the suggested nonparametric estimation provides an efficient way of function approximation from the view point of the number of kernel functions as well as learning speed.

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Design and Implementation of Operating Management System for e-Learning

  • Kwak, Young-Tae
    • Journal of the Korean Data and Information Science Society
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    • 제14권4호
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    • pp.863-875
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    • 2003
  • The existing e-learning systems have short functions for learners to lead their self-directed learning activities because those systems have not been integrated with functions supporting activities of learners, instructors and operators. Therefore, we designed and implemented an efficient e-learning system having fully integrated functions to let learners induce their active learning, instructors teach learners effectively and evaluate their learning activities, and operators handle curriculum affairs and system environments.

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An Analysis of University Students' Needs for Learning Support Functions of Learning Management System Augmented with Artificial Intelligence Technology

  • Jeonghyun, Yun;Taejung, Park
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권1호
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    • pp.1-15
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    • 2023
  • The aim of this study is to identify intelligent learning support functions in Learning Management System (LMS) to support university student learning activities during the transition from face-to-face classes to online learning. To accomplish this, we investigated the perceptions of students on the levels of importance and urgency toward learning support functions of LMS powered with Artificial Intelligent (AI) technology and analyzed the differences in perception according to student characteristics. As a result of this study, the function that students considered to be the most important and felt an urgent need to adopt was to give automated grading and feedback for their writing assignments. The functions with the next highest score in importance and urgency were related to receiving customized feedback and help on task performance processed as well as results in the learning progress. In addition, students view a function to receive customized feedback according to their own learning plan and progress and to receive suggestions for improvement by diagnosing their strengths and weaknesses to be both vitally important and urgently needed. On the other hand, the learning support function of LMS, which was ranked as low importance and urgency, was a function that analyzed the interaction between professors and students and between fellow students. It is expected that the results of this student needs analysis will be helpful in deriving the contents of learning support functions that should be developed as well as providing basic information for prioritizing when applying AI technology to implement learner-centered LMS in the future.

도서관 이러닝 플랫폼 사례분석 연구 - 학습 내용 및 기능을 중심으로 - (Research on Case Analysis of Library E-learning Platforms: Focusing on Learning Contents and Functions)

  • 조상은;오경묵
    • 한국비블리아학회지
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    • 제34권1호
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    • pp.209-238
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    • 2023
  • 본 연구는 도서관의 이러닝 플랫폼 구축을 위한 주요 학습 내용과 기능 및 활성화 방안을 제안하고자 문헌연구와 사례분석 및 전문가 조사를 진행하였다. 문헌연구에서 도서관이 이러닝 생태계에 있는 이용자를 위해 질 높은 온라인 교육을 제공해야 함을 알 수 있었으며 선행연구를 통해 도서관의 이러닝 플랫폼 분석을 위한 학습기능 분석 도구를 도출하였다. 이를 기반으로 국내외 도서관 이러닝 플랫폼들의 학습 내용과 기능 및 특징을 분석하였으며 전문가 설문 조사 및 인터뷰를 수행하였다. 분석결과, 도서관의 지속 가능한 이러닝 서비스를 위해 학습 과정과 기술을 효과적으로 적용할 수 있는 플랫폼의 구축이 필수적이며 제공해야 할 학습 내용은 관 종에 상관없이 공통적으로 독서교육, 정보활용교육, 도서관이용교육, IT 최신기술 소개 등 도서관교육의 특성을 나타내는 주제가 도출되었다. 주요한 학습기능으로는 학습유형 중 영상강의와 실시간 수업을 진행할 수 있어야 하며 학습자료와 이용 가이드를 제공할 수 있는 학습활동지원 기능, 교육내용을 저장하고 공유할 수 있는 클라우드 플랫폼 지원 기능, 생애주기 맞춤형 콘텐츠를 제공할 수 있는 개인화 환경 지원 기능 등을 제시하였다. 또한, 도서관 사서의 기술력 향상을 위한 재교육, 이러닝 관련 팀의 구성과 전문사서의 도입을 제안하였다.

고속도로 자율주행 시 보상을 최대화하기 위한 강화 학습 활성화 함수 비교 (Comparison of Reinforcement Learning Activation Functions to Maximize Rewards in Autonomous Highway Driving)

  • 이동철
    • 한국인터넷방송통신학회논문지
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    • 제22권5호
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    • pp.63-68
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    • 2022
  • 자율주행 기술은 최근 심층 강화학습의 도입으로 큰 발전을 이루고 있다. 심층 강화 학습을 효과적으로 사용하기 위해서는 적절한 활성화 함수를 선택하는 것이 중요하다. 그 동안 많은 활성화 함수가 제시되었으나 적용할 환경에 따라 다른 성능을 보여주었다. 본 논문은 고속도로에서 자율주행을 학습하기 위해 강화 학습을 사용할 때 어떤 활성화 함수를 사용하는 것이 효과적인지 12개의 활성화 함수 성능을 비교 평가한다. 이를 위한 성능 평가 방법을 제시하였고 각 활성화 함수의 평균 보상 값을 비교하였다. 그 결과 GELU를 사용할 경우 가장 높은 평균 보상을 얻을 수 있었으며 SiLU는 가장 낮은 성능을 보여주었다. 두 활성화 함수의 평균 보상 차이는 20%였다.

The Learning and Teaching of Transcendental Functions through Sound and Music

  • Choi, Jong-Sool;Kim, Hyang-Sook
    • 한국수학교육학회지시리즈D:수학교육연구
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    • 제7권3호
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    • pp.191-209
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    • 2003
  • In this paper, we present a new environment of learning and teaching of trigonometric, exponential and logarithmic functions, the most difficult parts for students to learn among functions, through sound and music, students like the most. First, by using sound and music, we try to arouse student's interest. Second, we let students see and hear properties of transcendental functions so that students can understand and remember them easily. Finally we encourage students to compose their favorite song using transcendental functions so that they can experience the practicality of transcendental functions.

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교육과정 재구성을 위한 디지털교과서 기능 개선 방안 연구 (The Improvement of Digital Textbook Functions Required for Curriculum Reorganization)

  • 김홍선;정영식
    • 정보교육학회논문지
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    • 제26권1호
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    • pp.23-34
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    • 2022
  • 교사가 학생 수준에 맞게 교육과정을 재구성하여 교과서를 자유롭게 재구성하여 학생들에게 배포할 수 있어야 한다. 그러나 현행 서책 교과서는 일부 내용을 수정하거나 편집하여 학생들에게 나눠주기 어렵고, 현행 디지털교과서 역시 단원 단위로 묶여 있어 교과 내용의 순서나 자료를 재구성할 수 없다. 또한, 외부 링크나 최신 자료를 업데이트하는 데 어려움이 있고, 용량 제한으로 다양한 멀티미디어 자료나, 고화질 실감형 콘텐츠를 담기가 어렵다. 따라서 본 연구에서는 교사들이 디지털교과서를 활용하여 학생들에게 수준별 맞춤학습을 제공할 수 있도록 교수·학습 및 평가 기능, 자료 검색 및 공유 기능, 학습 기록 및 분석 기능, 화면 출력 및 인쇄 기능을 제시하였다. 또한, 전문가 델파이 조사를 통해 영역별 세부 기능을 교사용과 학생용으로 구분하였다. 아울러, 디지털교과서를 다양한 교과로 확대하여 개발하고, 디지털교과서를 활용한 다양한 교수·학습 모형을 개발하여 보급할 것을 제안하였다.

Comparison of Reinforcement Learning Activation Functions to Improve the Performance of the Racing Game Learning Agent

  • Lee, Dongcheul
    • Journal of Information Processing Systems
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    • 제16권5호
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    • pp.1074-1082
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    • 2020
  • Recently, research has been actively conducted to create artificial intelligence agents that learn games through reinforcement learning. There are several factors that determine performance when the agent learns a game, but using any of the activation functions is also an important factor. This paper compares and evaluates which activation function gets the best results if the agent learns the game through reinforcement learning in the 2D racing game environment. We built the agent using a reinforcement learning algorithm and a neural network. We evaluated the activation functions in the network by switching them together. We measured the reward, the output of the advantage function, and the output of the loss function while training and testing. As a result of performance evaluation, we found out the best activation function for the agent to learn the game. The difference between the best and the worst was 35.4%.