본 연구는 대학생들의 계획된 우연대처기술과 진로결정 자기효능감의 관계와 사회적 지 지의 매개효과를 검증한 연구이다. 수집된 자료는 기술통계, Pearson 상관분석과 다중회 귀분석 및 매개효과 분석을 실시했다. 연구 결과는 다음과 같다. 첫째, 대학생들의 계획된 우연대처기술은 정보적 지지, 물질적 지지에 유의미한 영향을 미치는 것으로 나타났다. 둘째, 대학생들의 계획된 우연대처기술은 진로결정 자기효능감에 영향을 미치는 것으로 나타났다. 셋째, 대학생들의 사회적 지지의 하위요인에 해당하는 정보적 지지, 정서적 지 지, 물질적 지지는 진로결정 자기효능감에 영향을 미치는 것으로 나타났다. 넷째, 대학생 들의 계획된 우연대처기술은 정보적 지지, 정서적 지지, 물질적 지지를 매개로 진로결정 자기효능감에 영향을 미치는 것으로 나타났다. 연구 결과에 근거하여 대학교 학생상담센 터 또는 진로취업지원센터의 상담 전문가들이 우연대처기술과 사회적 지지를 강화하고 대 학생들의 진로결정 자기효능감을 높일 수 있는 제언을 했다.

본 연구는 대학생의 코칭역량과 사회적 지지가 진로결정 자기효능감에 미치 는 영향을 규명하고 정서지능이 매개역할을 하는지 실증적으로 규명하여 대학 생 진로와 관련한 교육적 기초자료를 제공하는 데 그 목적이 있다. 본 연구를 위하여 대학생을 대상으로 설문을 실시하였고, 그 중 535부를 SPSS와 AMOS 28.0을 사용하여 분석한 결과는 다음과 같다. 첫째, 모든 연구변인 간에 통계적으로 유의미한 정적 상관이 있는 것으로 나 타났다. 둘째, 코칭역량과 사회적 지지는 정서지능에, 정서지능은 진로결정 자기 효능감에 유의미한 정적 영향을 미쳤고, 진로결정 자기효능감에 코칭역량은 직 접적으로 유의미한 영향을 미쳤으나 사회적 지지가 직접적으로 미치는 영향은 미미하였다. 셋째, 정서지능의 매개효과를 살펴본 결과 코칭역량과 진로결정 자 기효능감 간의 관계에서 부분 매개하였고, 사회적 지지와 진로결정 자기효능감 간의 관계에서 완전 매개하고 있음을 알 수 있었다. 이 연구를 통해 코칭역량과 사회적 지지가 정서지능을 매개하여 진로결정 자 기효능감에 직ㆍ간접적으로 영향을 미치는 변인임을 확인하고, 각 변인이 진로 관련 교육과정에 활용되기를 제안한다.

Agrophotovoltaic (APV) system is an integrated system producing crops as well as solar energy. Because crop production underneath Photovoltaic (PV) modules requires delicate management of crops, smart farming equipment such as real-time remote monitoring sensors (e.g., soil moisture sensors) and micro-climate monitoring sensors (e.g., thermometers and irradiance sensors) is installed in the APV system. This study aims at introducing a decision support system (DSS) for smart farming in an APV system. The proposed DSS is devised to provide a mobile application service, satellite image processing, real-time data monitoring, and performance estimation. Particularly, the real-time monitoring data is used as an input of the DSS system for performance estimation of an APV system in terms of production yields of crops and monetary benefit so that a data-driven function is implemented in the proposed system. The proposed DSS is validated with field data collected from an actual APV system at the Jeollanamdo Agricultural Research and Extension Services in South Korea. As a result, farmers and engineers enable to efficiently produce solar energy without causing harmful impact on regular crop production underneath PV modules. In addition, the proposed system will contribute to enhancement of the smart farming technology in the field of agriculture.

Agrophotovoltaic (APV) system is an integrated system producing crops as well as solar energy. Because crop production underneath Photovoltaic (PV) modules requires delicate management of crops, smart farming equipment such as real-time remote monitoring sensors (e.g., thermometers, irradiance sensors, and soil moisture sensors) is installed in the APV system. This study aims at introducing a simulation-based decision support system (DSS) for smart farming in an APV system. The proposed DSS is devised to provide a mobile application service, satellite image processing, real-time data monitoring, and simulation-based performance estimation. Particularly, an agent-based simulation (ABS) is used to mimic functions of an APV system so that a data-driven function and digital twin environment are implemented in the proposed system. The ABS model is validated with field data collected from an actual APV system at the Jeollanamdo Agricultural Research and Extension Services in South Korea. As a result, farmers and engineers enable to efficiently produce solar energy without causing harmful impact on regular crop production underneath PV modules. In addition, the proposed system will contribute to enhancement of the digital twin technology in the field of agriculture.

This study evaluated methods of improving sustained learning participation by examining the structural relationship of school support consisting of professor support, friend-senior support and educational environment support, career decisionmaking self-efficacy, school satisfaction, and learning persistence depending on the characteristics of college students majoring in culinary art and food service. The study findings were as follows. First, the general characteristics of college students majoring in culinary art and food service were perceived significantly more by female students than by male students. Second, school support directly influenced the career decision-making self-efficacy and school satisfaction, but did not directly influence the learning persistence. Instead, school support influenced school satisfaction and learning persistence indirectly by the medium of career decision-making self-efficacy. Third, career decision-making self-efficacy directly influenced school satisfaction and learning persistence and indirectly influenced learning persistence by the medium of school satisfaction. Lastly, school satisfaction directly influenced the learning persistence, implying that school satisfaction is an important factor for the learning persistence of college students majoring in culinary art and food service. These results show that, because school members and environmental support cannot exclusively make learning persistence, diverse systems and programs must be developed and applied to improve the career decision-making self-efficacy and school satisfaction of college students majoring in culinary art and food service.

Due to changes in the agricultural market environment and both overseas and domestic farming conditions, uncertainties in agricultural production and management are becoming greater. Hence, there is a stronger need for farmers to choose crops in the optimal condition. This research aims to introduce the result and process of developing a decision support system for selecting crops, aimed to assist farmers in selecting the optimal crops most suitable in the given situation. There are basically three main factors to consider in the decision-making process for farmers when selecting a crop to introduce to their lands. First of all, one must consider how much profit crop A will produce when it is cultivated. Secondly, one must consider which crop to cultivate in order to earn a certain amount of profit. Thirdly, one must consider what is the best way to maximize Farm A’s business profit. For instance, a farm may have land as its resource, and one must research which location, type of crop, level of technology, and so forth, to maximize profit.This research creates a database of the profitability of a total of 180 crop types by analyzing Rural Development Administration’s survey of agricultural products income of 115 crop types, small land profitability index survey of 53 crop types, and Statistics Korea’s survey of production costs of 12 crop types. Furthermore, this research presents the result and developmental process of a web-based crop introduction decision support system that provides overseas cases of new crop introduction support programs, as well as databases of outstanding business success cases of each crop type researched by agricultural institutions.