• 한국가정과교육학회지
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• 제8권1호
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• pp.51-57
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• 1996

The purpose of this study were to examine the difference of the effect of CAI and students’attitude to Home Economics Class through CAI. 120 girl students of the first year were chosen at B middle school in Daegu. Among them each 30 students were classified into 4 groups； High Intelligence group/Individual learning pattern, High Intelligence group/Small group learning pattern, Low Intelligence group/Individual learning pattern, Low Intelligence group/Small group learning pattern. The task of learning was “management of washing”Unit of the second grade. The data were processed with Cronbach’s ${\alpha}$, t-test, ANOVA by SPSS/PC(sup)+. The research findings are as follows： 1. In the verification of CAI Learning effect according to student group pattern, there is no difference between Individual learning pattern and Small group learning pattern in Achivement and Retention of learning. 2. In the verification of CAI Learning effect according to student intelligence level, there is no difference between High Intelligence group and Low Intelligence group in Achivement and Retention of learning. 3. The result of students’attitude to Home Economics Class verificated is an follows. (1) Individual learning pattern is more attensive than Small group learning pattern, but there is no difference in Intelligence level. (2) Low Intelligence group is more positive than High Intelligence group, and Small group learning pattern is more positive than Individual learning pattern in a view of Home Economics Class after using CAI.

• 한국초등과학교육학회지:초등과학교육
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• 제40권1호
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• pp.66-80
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• 2021

This study is a case study that applies plant classification learning using machine learning to fourth graders in elementary school in online learning situations. In this study, a plant classification learning education program associated with 2015 revision science curriculum was developed by applying the Artificial Intelligence biological classification teaching Learning model. The study participants were 31 fourth graders who agreed to participate voluntarily. Plant classification learning using machine learning was applied six hours for three weeks. The results of this study are as follows. First, as a result of image analysis on artificial intelligence, participants were mainly aware of artificial intelligence as mechanical (27%), human (23%) and household goods (23%). Second, an artificial intelligence recognition survey by semantic discrimination found that artificial intelligence was recognized as smart, good, accurate, new, interesting, necessary, and diverse. Third, there was a difference between men and women in perception and emotion of artificial intelligence, and there was no difference in perception of the ability of artificial intelligence. Fourth, plant classification learning using machine learning in this study influenced changes in artificial intelligence perception. Fifth, plant classification learning using machine learning in this study had a positive effect on reasoning ability.

• 의학교육논단
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• 제15권1호
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• pp.46-53
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• 2013

The purpose of this study was to analyze the relationship among medical students' learning motivation, characteristics of multiple intelligence, and academic achievement. The participants were 144 medical students. The data were collected by administering learning motivation tests (self-confidence, self-efficacy, level of task, emotion of learning, learning behavior, failure tolerance, task difficulty, and academic self-efficacy), a multiple intelligence test (linguistic intelligence, logical-mathematical intelligence, musical intelligence, bodily-kinesthetic intelligence, spatial intelligence, interpersonal intelligence, intrapersonal intelligence, and naturalistic intelligence), and two semesters of grades. There is a correlation between multiple intelligences and learning motivation. Among academic self-efficacy of academic motivation, the self-control efficacy (0.28) and behavior (0.18) subscales are significantly positively correlated with academic achievement. However, the emotion subscale (-0.18) was significantly negatively correlated. Learning motivation was correlated with two of the eight multiple intelligence profiles: the intrapersonal intelligence (0.18) and bodily-kinesthetic intelligence (-0.19). The structural equation modeling analysis showed that the behavior and self-control efficacy subscales of intrapersonal intelligence had an impact on academic achievement. An analysis according to the academic achievement group showed significant differences in self-control efficacy and emotion subscales with intrapersonal intelligence. A positive relationship can be observed between learning motivation and some characteristics of multiple intelligence of medical school students. In light of the findings, it is worth examining whether we can control medical students' learning motivation through educational programs targeting self-control efficacy and intrapersonal intelligence.

• 융합정보논문지
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• 제10권1호
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• pp.120-127
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• 2020

본 연구의 목적은 대학생의 협력학습에서 학습성과를 향상시키는 변인을 살펴보기 위해 학습자 변인으로 감성지능, 학습과정 변인으로 의사소통능력과 집단지성, 학습성과 변인으로 학습만족도와 학습지속의향을 선정하여 각 변인간의 구조적 관계를 규명하였다. 수도권 소재 A대학교 3,475명의 자료를 활용하였으며 자료는 구조방정식을 활용하여 분석하였다. 연구결과, 감성지능은 의사소통능력, 집단지성, 학습만족도, 학습지속의향에 정적 영향을 미쳤으며, 의사소통능력은 집단지성과 학습지속의향에 정적 영향을 미쳤다. 집단지성은 학습만족도와 학습지속 의향에 정적 영향을 미쳤으며 학습만족도는 학습지속의향에 정적 영향을 미쳤다. 본 연구결과는 대학생의 협력학습에서 학습성과를 향상시키는 변인들 간의 구조적 관계를 밝힘으로써 협력학습의 기초자료를 제공할 수 있을 것이다.

• 대한공업교육학회지
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• 제30권2호
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• pp.72-81
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• 2005

The purpose of this study is to do research on correlation between multiple intelligence and e-Learning strategy, which can be used to develop and strengthen e-Learning strategy. The subject was 183 college students of engineering at C university who had ever taken a lesson through e-Learning. Two items are investigated in these college students. One is whether there is a gap and any gender-related difference in multiple intelligence and e-Learning strategy, and the other is what multiple intelligences have an effect on e-Learning strategy. The e-Learning strategy developed by In-Sock Lee and the instrument by Yong-Lin Moon were used. The results of this study are as follows. First, it appeared that there was a difference between gender in musical intelligence and naturalistic intelligence. The average of musical intelligence was higher in female collegian, while the average of naturalistic intelligence was higher in male collegian. But there was no gender-related difference in using e-Learning strategy. Second, it appeared that multiple intelligence gave an explanation of self-direction intelligence up to 31.1%, expression strategy 20.35%, and information processing strategy 16.6%. The results of this study showed that logical-mathematical intelligence affected all of three e-Learning strategies. So, new curriculum which can make use of logical-mathematical intelligence needs to be developed so as to devise efficient e-Learning strategies.

• 디지털산업정보학회논문지
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• 제19권1호
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• pp.153-172
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• 2023

We look into the theory of experiential learning, which allows learners to design and organize their own lives, as well as to develop the necessary competencies for students who will be living in intelligent information society. We also investigate the teaching and learning methods, as well as the educational contents of artificial intelligence education, and develop an approach to artificial intelligence education that will develop learners' capabilities. As a result, we have investigated the pedagogical needs for artificial intelligence education in elementary and secondary schools, critically reviewed the discussions on experiential learning-based education for artificial intelligence education in elementary and secondary schools, and proposed a plan. Experiential learning achieves comprehension and knowledge acquisition naturally, as well as subject connection and integration. When preparing for artificial intelligence education, practical methods and procedures for developing capabilities in artificial intelligence education, focusing on in-depth learning, inter-subject linkage and integration, life-related learning, and reflection on the learning process, should be considered unavoidable.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2022년도 춘계학술대회
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• pp.177-179
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• 2022

Google Deepmind Challenge match에서, Alphago가 바둑 대결에서 4승1패로 한국의 이세돌(인간)에 승리하였다. 드디어, 인공지능은 인간 지능의 활용을 넘어서고 있는 것이다. 한국 정부의 디지털뉴딜의 사업예산은 2022년 9조원이며, 인공지능 학습용 data 구축사업은 301종을 추가로 확보한다. 2023년부터는 산업의 전 분야에서 인공지능의 학습의 활용과 적용으로 산업 패러다임이 변화될 것이다. 본 논문은 인공지능 알고리즘을 활용하기 위한 연구를 한다. 인공지능 학습에서 data의 분석과 판단을 중심으로, 인공지능 머신러닝과 딥러닝 학습에서의 알고리즘의 적절한 활용 대상과 활용 범위에 대한 연구를 한다. 본 연구는 4차산업혁명기술의 인공지능과 5차산업혁명기술의 인공지능로봇 활용의 기초자료를 제공할 것이다.

• 대한통합의학회지
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• 제4권1호
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• pp.65-72
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• 2016

Purpose : This study was carried out to find out the relationship between emotion intelligence, learning flow and career stress of nursing students and influence factors for career stress. Methods : This study targeted 197 university students in their freshman-senior year attending College of Nursing located in P Metropolitan City. For collected data, real numbers and percentage, mean and standard deviation and multiple regression analysis were carried out by using PASW 21.0 program and the correlation between emotion intelligence, learning flow and career stress was analyzed with Pearson's correlation coefficients. Results : Emotional self-awareness(M=3.80, SD =.71), clear goals(M=3.39, SD=.90) and school environment stress(M=2.97, SD=.96) were found to be high in the degree of emotion intelligence, learning flow and career stress of the subjects. The relationship between emotion intelligence and learning flow showed a positive correlation(r=.489, p<.01) in the correlation between emotion intelligence, learning flow, career stress and emotion intelligence showed a negative correlation with career stress(r=-.204, p<.01). Emotion intelligence and learning flow show that career stress is predicted significantly (${\beta}$ =-.15, p < .01) and explained a career stress variate as 18%(F = 24.5, p < .01). Conclusion : Emotion intelligence of nursing students was found to be very influential on the degree of learning flow or career stress. Based on the results of this study, replication studies on emotion intelligence and career stress are needed and the development of intervention programs to increase emotion intelligence is needed.

• 정보교육학회논문지
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• 제26권5호
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• pp.353-360
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• 2022

본 연구는 인간 지능의 가장 중요한 요소인 스토리텔링을 기반으로 한 인공지능 학습을 돕기 위해 구안된 인공지능 스토리텔링 교육 프로그램이 학습 몰입도에 미치는 영향을 검증하는 데 목적이 있다. 이를 위해 16차시 분량의 인공지능 교육 프로그램을 설계하여 개발하고, 초등학교 5~6학년군 영재 학생 19명을 대상으로 8주에 걸쳐 적용하였다. 인공지능 스토리텔링 교육 프로그램은 차시별 교수·학습과정안과 이야기책의 형태로 개발되었다. 인공지능 스토리텔링 교육 프로그램 적용 결과, 도전과 능력의 조화, 행위와 의식의 통합, 명확한 목표, 구체적인 피드백, 과제에 대한 집중, 통제감, 자의식의 상실, 시간 감각의 왜곡, 자기 목적적 경험 등 학습 몰입도의 9가지 모든 하위 요소에서 평균 점수에 유의미한 향상이 나타났다. 즉, 인공지능 스토리텔링 교육 프로그램은 학습 몰입도 향상에 효과적임을 확인할 수 있었다.

• 지식경영연구
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• 제19권3호
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• pp.173-187
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• 2018

This study was aimed at suggesting an integrative framework for creating collective intelligence and enhancing group performance after reviewing previous studies including those related to learning organizations, organizational learning, knowledge management, and collective intelligence. In the first, we examined that the similarities and differences between collective intelligence and other similar concepts, such as learning organizations, organizational learning, and knowledge management. Next, an integrative framework for creating collective intelligence and channeling it into strong group performance were suggested. In this process, we reviewed conditions for creating collective intelligence and segmented the major variables as expectancy, valence, and instrumentality, according to Vroom's (1964) expectancy theory. Characteristics of problems and the roles of leaders were respectively considered as valence for inducing collaboration and expectancy for managing probability to achieve goals. Instrumental factors were also adopted from conditions for creating group intelligence suggested from several researchers, such as creativity, openness, willingness for working together, horizontal communication, centralization in decision making, and building effective information and communication technology system and active usage of it. We discussed two potentially disputable matters about the scope and level of collective intelligence and group performance and suggest several theoretical and practical implications in the Discussion.