학습 몰입의 구조: 척도, 성격, 조건, 관여 = The Structure of Learning Flow: Scale, Character, Condition, Involvement
The purpose of this study was to examine the structure of learning flow whether the flow in learning situation had different characteristics comparing with general flow. I have 4 sub-purpose: (1) First purpose is to develop the Learning Flow Scale that can measure flow level in real learning situation. (2) Second purpose is to examine the character of learning flow, (3) Third purpose is to examine variables of family and school influencing the learning flow experience and verify optimal conditions that can experience flow in learning situation. (4) Fourth purpose is to verify involvement of learning flow at the point that variables of family and school influence learning achievement. Through this purpose, I selected 4 research problem.
This study was administered to 980 6th grade and 181 5th grade elementary school students. Statistical methods were conducted item analysis, Exploratory Factor Analysis(EFA), Confirmatory Factor Analysis(CFA), and structural equation model in Study I. Analysis methods in Study II and Study III were conducted ANOVA, regression analysis, frequency analysis, t-test, correlation analysis, and post hoc test. And finally, path analysis was conducted in Study IV.
The result of this study was the follows. In Study I, I developed and validated the Learning Flow Scale, examined validation of high-order factor model for the Learning Flow Scale, and verified a causal relation among factors of the Learning Flow Scale.
To develop the Learning Flow Scale First, based on the results of literature review, I identified 9 components of Csikszentmihalyi's flow construct and developed the 200 pilot items. Analyzing the pilot test data, the result obtained 51 items, 8 factors except 'Transformation of Time' of Csikszentmihalyi's 9 flow factors. Based on theory, I added 19 items and conducted 70 items in main test. Analyzing the main test data, the result obtained 49 items, 9 factors. Conducting Confirmatory Factor Analysis(CFA), improving goodness of fit of the model, and modifying the model, the result obtained 35 items, 9 factors as the final learning flow scale. As a result of Confirmatory Factor Analysis(CFA), the goodness of fit indices(GFI, AGFI, CFI, RMSEA) demonstrated statistically significance and fitness of the model. The final Learning Flow Scale supported Csikszentmihalyi's 9 flow factors. The Learning Flow Scale can be used as a valid instrument to measure flow level in the learning situation.
To test validation of high-order factor model for the Learning Flow Scale, I conducted 2 order CFA. The result obtained 2 factor(affective domain and cognitive domain) 2 order factor model. The goodness of fit indices(GFI, AGFI, CFI, RMSEA) demonstrated statistically significance and fitness of the model. The affective domain was included concentration on task at hand, loss of self-consciousness, transformation of time, and autotelic experience factor. The cognitive domain was included challenge-skill balance, action-awareness merge, clear goals, unambiguous feedback, and sense of control factor.
To test the causal relation among factors of the Learning Flow Scale, I conducted structural equation model. As a result, if a activity has challenge-skill balance, clear goals, and unambiguous feedback, it is easy to appear action-awareness merge, transformation of time, sense of control, loss of self-consciousness, and concentration on task at hand. It is easy happen autotelic experience in terms of action-awareness merge, transformation of time, sense of control, loss of self-consciousness, and concentration on task at hand. Autotelic experience is a final result of 8 factors.
In Study II, I verified 4 sub-study: a relationship between learning motivation and learning flow, the relationship among learning motivation, learning flow, and learning achievement, the relationship between challenge and ability in learning flow state, and frequency of learning flow experience to subject matter. First, I examined a relationship between learning motivation and learning flow. As the result, The students who had intrinsic motivation had high level of learning flow significantly. Second, I examined the relationship among learning motivation, learning flow and learning achievement. As the result, those who had high level of learning flow and intrinsic motivation had high learning achievement.
Third, as the result of frequency analysis of learning flow on subject matters, the frequency of learning flow was high in physical education, mathematics, and science. Fourth, I conducted regression analysis to examine the relationship between challenge and ability in learning flow state. The result appeared that students experienced learning flow when one's ability was higher than challenge.
In Study III, I examined the follows: (1) the relationship between demographic variables and learning flow, (2) the relationship between family challenge-support and learning flow, (3) the relationship between learning place and learning flow, and (4) the relationship between school challenge-support and learning flow. First, I conducted ANOVA to examine level of learning flow on gender, the number of family, education level of parents, and economic level. Those who had high economic level had high level of learning flow. Second, As a result of examining the relationship between family challenge-support and learning flow, those who had high family challenge and high family support had high level of learning flow.
Third, I conducted frequency analysis to examine the relationship between learning place and learning flow. As the result, the students had the highest learning flow frequency in school. Fourth, As a result of examining the relationship between school challenge-support and learning flow, those who had high school challenge and support had high level of learning flow. In instructional formats, the frequency of learning flow was high in group work and individual work. The frequency of learning flow for the learning activity of students was high in physical activity and thinking activity.
In Study IV, I examined a causal relation among family, school, learning flow and learning achievement. The result appeared that the higher were family challenge and school support, the higher were the learning flow and learning achievement. The challenge and support of family and school didn't influence directly learning achievement. Through the results of this study, when school and family support and stimulate students to experience learning flow, they will enjoy learning and improve their ability. Furthermore, the self of students will grow.
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한국교육학술정보원은 정보주체의 자유와 권리 보호를 위해 「개인정보 보호법」 및 관계 법령이 정한 바를 준수하여, 적법하게 개인정보를 처리하고 안전하게 관리하고 있습니다. 이에 「개인정보 보호법」 제30조에 따라 정보주체에게 개인정보 처리에 관한 절차 및 기준을 안내하고, 이와 관련한 고충을 신속하고 원활하게 처리할 수 있도록 하기 위하여 다음과 같이 개인정보 처리방침을 수립·공개합니다.
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제16조(개인정보 처리방침의 변경)
제1조(개인정보의 처리 목적)
제2조(개인정보의 처리 및 보유 기간)
5년
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(「전자상거래 등에서의 소비자보호에 관한
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ID, 비밀번호, 이름, 주소 |
5년 |
제5조(개인정보의 제3자 제공)
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제10조(개인정보 자동 수집 장치의 설치·운영 및 거부)
제11조(개인정보 보호책임자)
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제12조(개인정보의 열람청구를 접수·처리하는 부서)
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