• 공학교육연구
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• 제26권6호
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• pp.19-29
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• 2023

This study aims to develop and apply a metaverse-based instructional design model for the education in science and technology. It analyzed the concept and characteristics of metaverse, existing non-contact education models, and major teaching strategies systematically. Based on the prior researches, an instructional design model using metaverse is developed that presents metaverse-related teaching strategies and design principles for the before-, during-, and after-lesson phases. Then, this model was applied to a project-based learning program, conducted a perception survey on instructors and learners, and revised the metaverse instructional design model based on the results of the survey. In the Metaverse Instructional Design Model, before-lesson phase is a physical and psychological preparation stage for class participation, which includes familiarization with the Metaverse learning environment, formation of expectations for education, and self-directed pre-learning. During the lesson, to effectively deliver the lesson content, it is necessary to build confidence in the learning environment, promote learning participation, provide reference materials, perform team projects and provide feedback, digest learning content, and transfer learning content. The after-lesson phase provides strategies for ongoing interaction between learners and mentors. This study introduces a new instructional design model that utilizes metaverse and shows the potential of metaverse-based education in science and technology. It also has important implications in that it provides practical guidelines for the effective design and implementation of metaverse-based education.

• International Journal of Computer Science & Network Security
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• 제24권4호
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• pp.67-76
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• 2024

Diabetic retinopathy is a threatening complication of diabetes, caused by damaged blood vessels of light sensitive areas of retina. DR leads to total or partial blindness if left untreated. DR does not give any symptoms at early stages so earlier detection of DR is a big challenge for proper treatment of diseases. With advancement of technology various computer-aided diagnostic programs using image processing and machine learning approaches are designed for early detection of DR so that proper treatment can be provided to the patients for preventing its harmful effects. Now a day machine learning techniques are widely applied for image processing. These techniques also provide amazing result in this field also. In this paper we discuss various machine learning and deep learning based techniques developed for automatic detection of Diabetic Retinopathy.

• 한국초등과학교육학회지:초등과학교육
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• 제28권2호
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• pp.178-186
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• 2009

The science writing is recognized for useful learning method to boost up scientific thinking for all class course as well as traditional lecture and experiment. Many researches say that science writing is helpful to extend students' science knowledge and scientific attitude. By the way, the researchers thought that science writing can also improve the science process skill if students participate in delicately organized learning program. In this study, we had contrived the teaching & learning strategy of science writing to improve science process skills. The learning program covers all field of Klopfer's process skills with various forms of writing; explaining writing, logical writing, critical writing, and creative writing. The learning program has been developed for 5th grade students in the regular classes in order to enhance science process skills as well as knowledge and scientific attitude. Not to miss any process skill or various kinds of writing, we used 3 dimensional frame. The axes of the frames are science process skills, forms of writing, and science curriculum contents. The students are given the final writing theme at the beginning of each chapter. They drill science process skills step by step during the classes, and have a chance to talk each other before the final writing. They practice writing skills from one sentence to full article by degrees. The effect of the program was examined by students' work and TSPS (Test of Science Process Skill). The result showed that 5th grade students had a meaningful progress in science process skills as well as knowledge and scientific attitude. we could confirm it with examining students' work in the class.

• 한국초등과학교육학회지:초등과학교육
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• 제32권2호
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• pp.198-205
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• 2013

For assessing classroom environment, numerous instruments were developed and reported the survey results for science students in science education. In this study I translated Constructivist Learning Environment Scales (CLES) were into Korean versions for elementary school teachers, and measured the reliability. The subjects were randomly selected from three departments of an University of Education in a metropolitan city. All of them were 110 students, who would be elementary school teachers. According to the survey results, pre-service teachers for elementary school have recognized constructivistly for learning environments in an actual forms. In a scale of student negotiation they have most constructivistly recognized learning environment, and moderately in scales of relevance, uncertainty and critical view while they have seldom constructivistly recognized in a scale of shared control. Also Korean version CLES would be an reliable instruments for constructivist assessing learning environments.

• 과학교육연구지
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• 제37권2호
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• pp.338-347
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• 2013

이 연구의 목적은 활동 중심 STEAM 교육 프로그램을 개발하고, 이 프로그램이 학생들의 과학 학습 흥미도에 미치는 효과를 알아보기 위한 것이다. 이 프로그램은 7학년 과학반을 대상으로 적용되었다. 이 연구는 단일집단 사전사후검사 설계로 이루어졌다. 검사도구로는 과학학습 흥미도 검사지를 활용했다. 대응표본 t 검정 결과 과학 학습 흥미에 대한 사전 검사와 사후 검사 사이에는 유의미한 차이가 나타났다. 또한 학습 흥미도의 하위 영역인 과학에 대한 태도, 과학학습 인식, 과학학습 전략면에서도 유의미한 차이가 나타났다. 이와 같은 결과는 STEAM 교육 프로그램이 학생들의 과학 학습 흥미도를 높이는데 효과적임을 나타낸 것이다. 따라서 앞으로 활동 중심 STEAM 교육 프로그램의 효과에 관한 연구들이 지속적으로 이루어져야 할 것이다.

• 동의신경정신과학회지
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• 제25권4호
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• pp.333-350
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• 2014

Objectives: The purpose of this study was to research learning based on brain science and the learning methodology of Korean Medicine according to disparity of age. Through this, the study aimed to provide a guideline to related Korean Medicine treatments as well as the common nurturing/educational institutions. Methods: All journals and dissertations on brain science based learning methods studied in Korea to date that could be found in the National Assembly Library and the RISS were implemented in the analysis. The terminology used for search was as follows: 1st search, 'Brain'; 2nd search, 'Learning', 'Education'; 3rd search, 'Baby, 'Infant', 'Child'. For the learning methodology of Korean Medicine according to disparity of age, the related contents were extracted from Donguibogam and Liuyi, Sasang constitutional medicine. Results: A total of 30 studies, were collected as data. In the baby stage, the development and myelination of brain neurons are accelerated by experience and learning, highly influenced by social, cognitive and emotional movement. In infancy, the frontal lobe actively develops, so education for development of the prefrontal cortex is suggested. The brain of the infant at this stage can be developed by arts and physical education. In the child stage, the parietal and temporal lobe develop actively. Thus, programs to stimulate brain activity including brain respiration would be helpful in enhancing learning ability, concentration, etc. As evidence for learning and nurturing methodology according to disparity of age from Korean Medicine prospective, the following are listed: Location and time for sexual intercourse before pregnancy, stabilization during pregnancy, baby nurturing methods for nurturing from Donguibogam. Also Liuyi and Sasanag constitutional medicine can be the learning methodology according to disparity of age. And there are acupuncture points on each head section according to age in Donguibogam. Conclusions: Studies on 'brain-science based learning' are continuously being conducted. Based on these studies, diverse new brain-science based learning will be developed in the future. There is also a need to develop the learning methodology of Korean Medicine according to disparity of age in a more systematic and diverse way.

• 과학교육연구지
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• 제39권1호
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• pp.28-43
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• 2015

본 연구의 목적은 과학과 자기주도학습에 대한 학생의 관심수준 및 실행수준을 관심에 기초한 교육과정 실행 모형(Concerns-Based Adoption Model: CBAM)을 바탕으로 분석하고 이들 간의 상관성을 조사하여 학생 개인의 관심수준에 맞는 자료를 제공하고 보다 높은 실행수준으로 향상될 수 있도록 지원책을 제시하고자하는 데 있다. 선행 연구들을 분석하여 학생의 과학과 자기주도학습에 대한 관심수준과 실행수준을 분석하기 위한 분석틀을 개발하고 이를 바탕으로 측정 도구를 개발하였다. 중 고등학생을 대상으로 설문조사한 결과를 통계적으로 분석하고 그 결과를 집단(지역, 학년, 성별)별로 나누어 비교 분석하였다. 과학과 자기주도학습에 대한 학생의 관심수준은 단계0 무관심이 가장 많았고, 실행수준은 수준 II 준비 단계가 가장 많았다. 집단 간의 비교에서는 관심수준은 성별에서 통계적으로 여학생이 남학생보다 높은 관심수준을 보였고, 실행수준은 중학생보다 고등학생이 높은 실행수준을 보이고 남학생보다 여학생이 높은 실행수준을 보였다. 마지막으로 관심수준과 실행수준의 상관성 분석에서 통계적으로 유의한 차이를 보였다.

• 한국초등과학교육학회지:초등과학교육
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• 제22권2호
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• pp.131-137
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• 2003

The students can search and solve the problems for themselves, improve the scientific inquiry skill through the distance learning in the WWW. It also enable them to construct the wide recognition of the STS which is emphasized in the 7th national curriculum. In addition, due to the one-to-one contact in the distance learning the diverse differentiated education can be run. In this paper, we develop the web-based distant learning model which is suitable in the elementary science and emboss those merits of the distance learning.

• International Journal of Computer Science & Network Security
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• 제21권6호
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• pp.77-88
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• 2021

Heart Failure represents a critical pathological case that is challenging to predict and discover at an early age, with a notable increase in morbidity and mortality. Machine Learning and Neural Network techniques play a crucial role in predicting heart attacks, diseases and more. These techniques give valuable perspectives for clinicians who may then adjust their diagnosis for each individual patient. This paper evaluated neural network models for heart attacks predictions. Several online learning methods were investigated to automatically and accurately predict heart attacks. The UCI dataset was used in this work to train and evaluate First Order and Second Order Online Learning methods; namely Backpropagation, Delta bar Delta, Levenberg Marquardt and QuickProp learning methods. An optimizer technique was also used to minimize the random noise in the database. A regularization concept was employed to further improve the generalization of the model. Results show that a three layers' NN model with a Backpropagation algorithm and Nadam optimizer achieved a promising accuracy for the heart attach prediction tasks.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.138-141
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• 2003

Recently reinforcement learning has attracted attention of many researchers because of its simple and flexible learning ability for any environments. And so far many reinforcement learning methods have been proposed such as Q-learning, actor-critic, stochastic gradient ascent method and so on. The reinforcement learning system is able to adapt to changes of the environment because of the mutual action with it. However when the environment changes periodically, it is not able to adapt to its change well. In this paper we propose the reinforcement learning system that is able to adapt to periodical changes of the environment by introducing the time-varying parameters to be adjusted. It is shown that the proposed method works well through the simulation study of the maze problem with aisle that opens and closes periodically, although the conventional method with constant parameters to be adjusted does not works well in such environment.