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RISS 인기검색어
- 검색키워드
- 저자 : Gyumin Lee (검색결과 3 건)
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이규민 Graduate School, Yonsei University 2020 국내석사
난제로 분류되는 현대사회의 공공문제가 점차 복잡해짐에 따라 많은 이해관계자들이 공공부문에 참여하고 있다. 전통적인 관료제적 접근법은 이러한 사회적 현상을 해결하기 어렵기 때문에 많은 학자들과 실무자들이 네트워크 구조에 관심을 기울이고 있다. 네트워크 구조는 많은 학자들에 의해 연구된 바 있으나, 네트워크를 유발하는 관리자/행위자의 개인적 행위인 네트워킹에 대해서는 많이 논의된 바 없다. 따라서 본 논문은 서울시공무원 자료를 이용해 관리자/행위자의 특성이 네트워킹에 어떤 영향을 미치는지 측정해보고자 한다. 관리자 혹은 행위자 간의 다른 성격을 파악하기 위해 본 연구는 골드버그의 Big 5 성격 이론(성격을 외향성, 우호성, 성실성, 신경증, 개방성의 다섯 가지 차원으로 분류)을 이용하였고, 다양한 차원의 분석을 통해 외향성과 성실성이 네트워킹에 있어 가장 우호적인 성격으로 밝혀졌다. Public problems in modern society have become wicked compared to those of the past. Also, more and more stakeholders are involving in public sectors. These all together make harder for a previous bureaucratic approach to solving these problems (Head & Alford, 2015). To solve these wicked problems, not only scholars but also practitioners have to give attention to the network. However, how the managers and actors affect to network, which is known as networking, is not well known. This thesis started with the assumption that an individual's personality affects networking. To figure out the different personality between actors, this thesis uses the framework of Goldberg's Big five personality (i.e., divide personality into five dimensions as extraversion, agreeableness, conscientiousness, neuroticism, and openness). The analyzed sample come from the seoul metropolitan government data. Extraversion and conscientiousness turned out to have most significant influence.
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The purpose of this study is to develop learners’ task selection-supporting strategies in self-directed e-learning environment and examine their effects and optimality. To achieve the purpose, this study established the following two research questions: (1) developing learners’ task selection-supporting strategies and (2) verifying the effects and optimality of learners’ task selection-supporting strategies for self-directed learning. Further, the second research question comprised three subordinate research objectives: (1) investigating the effects of self-directed learning on learners’ task-selection accuracy, self-directed learning abilities, and learning achievements; (2) verifying the effect of learners’ task selection-supporting strategies on learners’ task selection decision making; and (3) investigating the optimality of learners’ task selection-supporting strategies in self-directed learning. In Research 1, this study drew relevant strategies based on literature review to develop strategies to support learners’ task selection in self-directed learning and then validate the strategies through experts’ primary and secondary reviews. Then, this study developed an e-learning program with the final strategies reflected and subsequently validated the program through prototype evaluation on the storyboards and through usability evaluation. In Research 2.1, this study selected 236 sixth-grade elementary school students and applied the e-learning program with the final strategies reflected to investigate the effects of learners’ task selection-supporting strategies on learners’ task selection accuracy, self-directed learning abilities, and learning achievements for self-directed e-learning. Path analysis revealed that task selection-supporting strategies had a significant effect on learners’ task selection accuracy in self-directed e-learning, while learners’ task selection accuracy had a significant effect on their learning achievements. In Research 2.2, this study collected data from 27 sixth-grade elementary school students to examine the effect of learners’ task selection-supporting strategies on learners’ task selection decision making in self-directed e-learning. One-way ANOVA revealed that task selection-supporting strategies did not have a significant effect on learners’ task selection decision making in self-directed e-learning. In Research 2.3, this study collected qualitative data from 27 sixth-grade elementary school students and confirmed the optimality of task selection-supporting strategies in self-directed e-learning, Overall, this study has great significance in that it developed strategies to support learners’ task selection in self-directed learning and confirmed their positive effects on learners’ task selection accuracy and learning achievements and even confirmatively analyzed the future direction of learners’ task selection strategies by comprehending the optimality of the strategies.
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