ARCS학습동기 모델을 이용한 smart learning 학업성과 변인들간의 구조적 관계 분석 = Structural relation analyses between smart-learning performance variables based one ARCS learning motivation model

다국어 초록 (Multilingual Abstract)

The purpose of this study lies on investigating structural relations between variables affecting learning performance in the smart-Learning environment, a new e-Learning method that came from the recent spread of smart phones. This study suggested important variables that should be considered by regarding the direction of a teaching-learning strategy in the propulsion of smart-Learning on the government level. As learners have to continue to do self-driven learning in the smart-Learning environment, the motivation factor was considered the most important one. And an empirical analysis was underwent based on documentary research and existing research results by setting learners' efficacy for contents teachers and self-efficacy for smart-Learning using mobile devices as a mediation variable. The results from this study are as follows.
First, it was found that the hypothesis H1, H3, H4, H5 and H9 had a statistically significant effect at P<0.05. Second, the hypothesis H2, H6, H7 and H8 did not have a statistically significant effect at P<0.05. Third, analytical results showed that ARCS strategies with significant positive effects on learning absorption were Attention, Confidence and Satisfaction. An ARCS strategy affecting learning performance directly was found to be Satisfaction. Attention did not have a direct effect on learning performance, but had an indirect effect through learning absorption. And Satisfaction had a direct effect on learning performance and had an indirect positive effect through learning absorption.
According to the research results above, it is suggested that an ARCS motivation strategy should be considered more concretely during a smart-Learning contents development process as smart-Learning brings about different results depending on the characteristics of learners' recognition. Although a variety of studies have been conducted to raise the quality of e-Learning contents, it is very hard to develop the best contents in the e-Learning environment as efficient learning needs to consider learning subjects, learners' characteristics, learning methods and interactions among them. On the basis of such research results, several suggestions are made as follows. First, smart-Learning contents including ARCS motivation strategies recognized by learners should be developed so as to raise learners' learning efficiency.
Second, it was found that a group with a high efficacy for contents teachers recognized by learners and with a high self-efficacy for smart-Learning showed a higher learning performance. This implies that pre-education is required to improve the ability of contents teachers continuously and raise self-efficacy for smart-Learning devices. In addition, learning contents development needs to do a learning design in consideration of female students who showed low self-efficacy for smart-Learning. Third, follow-up studies considering various external environmental characteristics need to be done as this study investigated smart-Learning performance regarding motivation strategies by learners' gender and grade. In step with a continually changing ubiquitous environment in the future, various smart-Learning contents, strategies and methods meeting the demand of learners need to be developed to realize systematic smart-Learning.

목차 (Table of Contents)

• 제 1 장 서 론 1
• 제 1 절 연구의 배경 및 필요성 1
• 제 2 절 연구의 목적 4
• 제 3 절 연구의 범위 및 방법 5
• 제 4 절 연구의 구성 6
• 제 2 장 이론적 배경 7
• 제 1 절 Smart Learning의 이해 7
• 1. 교육환경의 변화 8
• 2. Smart Learning 개념 정의 11
• 3. 국내 Smart Learning 현황과 실태 조사 22
• 4. 국외 Smart Learning 현황과 전망 31
• 제 2 절 Smart Learning의 선행 연구 동향 37
• 1. ARCS 학습동기 모델의 개념 38
• 2. ARCS 학습동기 모델에 관한 연구 41
• 3. Smart Learning 자아효능감에 관한 연구 43
• 4. 학습자가 인식하는 콘텐츠 교사 효능감에 관한 연구 46
• 5. 학습 몰입에 관한 연구 48
• 6. 학업 성과에 관한 연구 51
• 제 3 장 연구방법 및 설계 54
• 제 1 절 연구모형의 설정 54
• 제 2 절 가설설정 및 연구문제 56
• 제 3 절 변수의 조작적 정의와 측정척도 62
• 제 4 절 연구설계 63
• 제 5 절 자료수집 및 분석방법 64
• 제 4 장 가설검증 및 통계분석 66
• 제 1 절 표본의 특성분석 66
• 제 2 절 측정모형 검증 69
• 제 3 절 구조모형의 분석 및 연구가설 검증 81
• 제 4 절 계층적 회귀모형을 통한 조절효과 검증 87
• 제 5 절 성별․학년별 및 효능감 구분에 따른 연구문제 검증 95
• 제 5 장 결 론 101
• 제 1 절 연구 결과의 요약 101
• 제 2 절 연구의 의의 및 시사점 106
• 제 3 절 연구의 한계점 및 향후 연구방향 108
• 참고문헌 또는 인용문헌 110
• 감사의 글 118
• 설문지 119