본 연구의 목적은 가정과교육에서 창의 인성 교육에 대한 가정과 교사의 관심 단계와 실행 수준, 그리고 실행 실태를 알아보는데 있다. 연구 자료는 전국의 중학교 가정과 교사를 대상으로 체계적 표집과 편의 표집을 하여 우편과 이메일을 통해 설문지를 배포하고 회수된 187부를 최종 분석에 사용하였다. 조사 도구는 주로 Hall(1987)이 개발한 혁신에 대한 교사의 관심도와 실행 수준에 대한 질문지를 수정 보완하여 사용하였고 그 외는 선행연구를 기초하여 개발하였으며 타당도와 신뢰도를 검증하였다. 자료는 SPSS/window(12.0) 프로그램을 이용하여 빈도, 백분율, 평균, 표준편차, t-test, ANOVA를 실시하였다. 본 연구를 통해 밝혀진 결과를 요약하면 다음과 같다. 첫째, 창의 인성 교육에 대한 가정과 교사의 관심 단계는 정보적 관심 단계(85.51)가 가장 높았으며 다음으로 개인적 관심 단계(85.18), 운영적 관심 단계(81.88), 지각적 관심 단계(82.15), 강화적 관심 단계(68.80), 협동적 관심 단계(61.97), 그리고 결과적 관심단계(59.76)의 순으로 나타났다. 둘째, 창의 인성 교육에 대한 가정과 교사의 실행 수준은 기계적 실행 수준(수준 3; 21.4%)이 가장 많았으며, 다음으로 탐색 수준(수준 1; 20.9%), 정교화 수준(수준 5; 17.1%), 사용하지 않는 수준(수준 0; 15.0%), 준비 수준(수준 2; 10.2%), 통합 수준(수준 6; 5.9%), 갱신 수준(수준 7; 4.8%), 일상화 수준(수준 4; 4.8%) 순이었다. 셋째, 창의 인성 교육에 대한 가정과 교사의 실행 실태를 조사한 결과, 반 이상의 가정과 교사(56.1%)는 가정과 수업에서 인성 교육에 치중하고 있으며, 31.0%의 교사는 창의 인성 교육을 모두 실행한다고 응답하였다. 반면 소수의 교사(6.4%)는 창의성 교육을 실행한다고 응답하였고 같은 수의 교사(6.4%)는 창의성과 인성 교육 어느 것도 실행하지 않는다고 응답하였다. 가정과 교사의 창의 인성 교육 요소의 실행 정도를 조사한 결과, 창의 인성 교육 요소의 실행은 평균은 5점 만점에서 3.76이었고 창의성 요소의 평균은 3.59, 인성 요소의 평균은 3.94로 보통보다 높았다. 창의성 교육 요소의 실행 정도에 대해서, 개방성/민감성(3.97)을 가장 많이 실행하였고 다음으로 문제해결능력(3.79), 호기심/흥미(3.73), 비판적 사고(3.68), 논리/분석적 사고(3.63), 문제발견능력(3.61), 독창성(3.57), 유추성(3.47), 유창성/융통성(3.46), 정교성(3.46), 상상력(3.37), 몰입/공감(3.37)의 순으로 실행하였다. 인성 교육 요소는 실천력(4.07)을 가장 많이 실행하였고, 다음으로 협동/배려/공정(4.06), 자기관리능력(4.04), 시민의식(4.04), 진로개발능력(4.03), 환경친화능력(3.95), 책임(감)/소유(3.94), 의사결정능력(3.89), 신뢰/정직/약속(3.88), 자율성(3.86), 글로벌역량(3.55)의 순으로 실행한 것으로 나타났다. 창의 인성 교육을 실행할 때 어려운 점으로, 많은 가정과 교사(64.71%)는 창의 인성 교육을 실행할 수업 자료가 부족한 데 있다고 하였으며, 40.11%의 교사는 창의 인성 교육의 연수 기회가 적은데 있다고 응답하였다. 한편 38.50%의 가정과 교사는 창의 인성 교육에 대한 평가 기준을 설정하거나 평가 도구를 개발하는 것이 어렵다고 응답하였고, 25.67%의 교사는 창의 인성 교육 방법을 모른다고 응답하였다. 창의 인성 교육 실행을 위해서 필요한 지원에 대해서, '창의 인성 교육과 관련된 학생들의 체험활동의 확대'(4.34), '창의성과 인성을 중시하는 가정과 수업 문화 조성'(4.29), '학생 발달 단계에 적합한 창의 인성 교육 내용'(4.27), '창의 인성 교육을 담당할 교수 인력 확보'(4.21), '창의 인성 교육의 개념과 가치 확립'(4.09), '지역 사회 기업 등과 연계한 창의 인성 교육 추진'(3.94)의 순으로 응답하였다.
To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.