Earticle

본 연구는 대학생의 직업기초능력 지도, 평가 및 활용을 위한 실질적인 교육모델을 개발하 기 위하여 액션러닝 교육방식을 적용한 교육모델을 개발한 내용과 개발된 교육모델의 실제 강좌적용 이후 교육효과를 분석해 본 탐색적 사례연구라 할 수 있다. 이상과 같은 연구목적의 달성을 위하여 NCS 직업기초능력과 액션러닝 교육방식에 대한 기존 연구문헌 들을 고찰하고 관련자와의 FGI 분석을 통하여 교육모델 초안 개발을 위한 시사점을 도출 하였으며, 시사점 도출 결과에 따라 해외영업원 직무분야와 연결되는 대학생 직업기초능 력 함양을 위한 액션러닝 교육모델을 개발하여 시범강좌를 실시하고 이후 해당 강좌의 직업기초능력 교육효과를 분석하였다. 본 연구를 통하여 수강생들은 팀 활동, 기업의 해외진출 활동과 관련되는 지식과 이에 따르는 문제해결 및 학습방법에 관하여 다양한 측면으로의 학습을 수행한 것을 알 수 있었으며, 액션러닝 교육방식이 실제 기업직무에 필요한 다양한 직업기초능력 함양을 병합적으로 습득할 수 있는 적절한 학습방법이라는 것을 확인할 수 있었다.

This study was an exploratory case study by analyzing the development of an action learning education model to develop a practical education model for guiding, evaluating and utilizing vocational basic competencies of university students and the effects of education after the actual course application of the developed education model. In order to achieve these research purposes, literature review on NCS vocational basic competencies and action learning education were reviewed, and suggestions for the development of the draft education model were derived through FGI analysis with those involved, and action learning education models were developed to develop the vocational basic competencies of university students connected to the job field of overseas salesmen according to the results of the findings, and the effects of vocational basic competencies education of the courses were analyzed afterwards. Through this study, students were able to learn from various aspects regarding team activities, knowledge related to the enterprise's overseas advancement activities, and the corresponding problem-solving and learning methods, and it was confirmed that the action learning education method was an appropriate way to combine the various vocational basic competencies required for actual corporate jobs.

본 연구는 액션 러닝 적용 수업이 예비보육교사의 과학 교과 교육학지식에 미치는 변화를 분석하여 액션 러닝 적용 수업의 효과를 검증하고자 한다. 연구의 대상은 부산시 소재 4년제 D 대학교 B 학과에서 예비보육교사를 희망하는 학습자 41명이다. 자료수집 기간은 2016년 9월 중순부터 2016년 11월 증순 까지 약 8주간 진행되었으며, 액션 러닝 적용 수업이 예비보육교사의 과학 교과 교육학지식에 미치는 변화를 살펴보기 위하여 단일집단 사전 사후 설계(One-Group Pretest-Post test Design)로 구성되었다. 액션 러닝 실시 전과 후 과학 교과 교육학지식에 대한 설문조사를 수행하고, 평균과 표준편차를 구하고, 전후 차이 검정을 위해 대응표본 t-검정을 하였다. 연구결과, 액션 러닝 적용 수업은 예비보육교사의 과학 교과 교육학지식 중 과학 교수․학습방법과 과학 교과 내용에 대한 지식, 과학교육 학습자에 대한 지식을 향상하는 데 효과가 있다.

The purpose of this study is to verify the effectiveness of the action learning application class on prospective childcare teachers’ knowledge of science subject pedagogy. The subjects of this study were 41 learners who hoped to become trainee teachers in the B department of 4-year university in Busan city. The data collection period lasted for about 8 weeks, from mid-September, 2016 to November, 2016. The action learning classes were divided in accordance with one-group pretest/post-test design. A questionnaire survey was conducted to ascertain the learners’ knowledge of science subject pedagogy before and after action learning. Mean and standard deviations were calculated and a corresponding sample t-test was conducted for the post-learning difference test. The results of the study showed that science education learners improved their knowledge of science teaching and learning methods and science subject content.

현대 사회는 정보통신 기술의 급속한 발달로 인해 인간의 삶의 질이 향상되었지만, 동시에 그 역기능으로 인해 다양한 사회적 문제들이 심각하게 제기되는 상황이다. 이러한 문제점들은 특히 성인과 달리 가치관 성립 단계에 있는 청소년들의 올바른 성장에 장애를 초래할 수 있다. 그리하 여 이러한 문제들에 주목하여, 청소년들에게 올바른 가치관 함양과 건전한 정보 활용 능력을 키우 기 위한 정보윤리교육의 필요성이 강조되고 있다. 하지만 현재 학교에서 이루어지는 정보윤리교육 은 교육내용과 교육방법 등에서 비체계성과 형식적 교육에 머무르고 있다는 비판을 받고 있는 실 정이다. 이에 본 연구에서는 교육방법과 관련하여 Action Learning(액션러닝)을 활용하여 정보윤리 교육의 교수-학습 방법을 구체화해보고 그 가능성을 타진해보고자 한다. 이미 액션러닝은 현대 지 식 및 정보 사회의 효과적 교수-학습 방법 중 하나로서 적극 활용되고 있는데, 액션러닝은 한 집 단 및 조직이 직면한 실질적인 문제를 해결하는 과정에서 학습이 이루어지도록 하는 것이다. 이때 구성원들은 문제해결 과정에 직접 참여해 봄으로써 효과적인 학습을 이룰 수 있다. 사실 한국의 학교교육에서는 그렇게 적극 활용되진 않으나, 기업교육의 영역에서는 액션러닝이 매우 활발히 활 용되고 있다. 이에 본 연구는 액션러닝 방법을 고등학교 도덕과 수업 특히 ‘정보윤리교육’에 적용 해 봄으로써 그 가능성을 타진코자 하였다. 사실 도덕 교과의 궁극적 목표는 학습자로 하여금 도 덕적 행위를 실천하도록 학습시키는 것이다. 도덕 교과의 이러한 궁극적 목표는 액션러닝 방법이 내재하는 본질적 철학 - 실행 중시 - 과 그 맥을 같이 하고 있다고 볼 수 있다. 따라서 본 연구에 서는 액션러닝에 대한 교실 수업의 모델을 개발하고, 이러한 모델이 학교 수업에 있어 성공적으로 정착되기 위해 필수적으로 선행되어야 할 핵심적 요인들을 중심으로 논의를 전개해 보고자 한다.

It is not easy to find out well organized teaching and learning methodology for Information ethics education in moral subject. Action learning empowers students to apply their knowledge and skills for solve problems and help to learn from their experience. This approach make 'Information ethics education' more effective by planning learning activities which use young people's experience and develop skill and understanding through their active involvement in a project(program). This study describes and analyses how action learning can make 'Information ethics education' more effective in moral subject. This study examine how action learning to encourage students to learn about contents of 'Information ethics education' in moral subject. This study argue that contents of information ethics education can be learned by engaging students in a project and other activities, which encourage them to develop understanding of information society. Meanwhile, this study also attempted to investigate which factors should be applied to implement the action learning method effectively in Information ethics education and to examine what the key factors so that they could be successive learning and operation. The findings from this study were as follows: First, action learning - based teaching materials for information ethics education could serve to stir up the interest of students by letting them face problem situations caused by the disfunction of the information society. Second, application of action learning to information ethics education was effective to develop an individual and team in classroom and to solve the problem of organization. Third, application of action learning to information ethics education could be one of effective approachs to boost not only practice capability of student to promote but also learning ability and teaching interest.

각 대학은 사회적 책무성에 근거하여 핵심역량을 고루 갖춘 인재양성에 주력하고 있다. 특히 세분화된 특정분야의 첨단지식의 지속시간이 짧아지는 시대적 특성을 고려하여 교양교육 과정을 개편 운영하고, 교수학습 방법을 개선하고 있다. 본 연구는 대학생들의 핵심역량 육성을 위해 적용된 Action Learning에서의 경험과정을 탐색하는 것을 목적으로 한다. 이를 위해 근거이론 접근방법을 사용하였다. 따라서 핵심역량 교과 영역 수강자들을 고루 포함할 수 있도록 하면서 다양한 범주, 속성 및 차원에 속하는 참여자를 모집하기 위해 이론적 표본추출을 하였다. 결과 총 15명을 연구 참여자로 선정하였고, 수집된 심층면담자료는 Strauss와 corbin의 근거이론 접근방법에 따라 분석하였다. 분석결과는 첫째, 액션러닝의 운영단계에 따라 러닝코치의 역할이 달라야 하고, 둘째, 효과적인 액션러닝 운영을 위해서 개인성찰의 기회도 충분히 가져야 한다. 셋째, 학습자들이 학습과정에서 도출되는 문제를 직접 해결해보는 것이 중요하고, 넷째, 핵심역량 교과목의 목적에 대한 숙지도 중요 한 것으로 나타났다.

In order to live up to public expectations, universities dedicate their best efforts to cultivating all Essential Competencies for outstanding individuals, especially reorganizing and improving their general education curricula and methods of teaching and learning, in light of the fact that a cutting-edge technology in a specific field does not bear a long span in the modern society. Through a Grounded Theory approach, the aim of this research is to study undergraduates' Experience Process of Action Learning designed to foster their Essential Competencies. With broadly selected 15 students from the courses for Essential Competencies, the method of theoretical sampling was employed so as to secure the diversity of the subjects' characteristics and backgrounds. After in-depth interviews, the data from the subjects were analyzed on the basis of Grounded theory approach of Strauss and Corbin. The conclusions of this analysis are as follows; Firstly, a learning coach should play a different role depending on the levels of Action Learning. Secondly, some time for introspection should be taken for the effective operation of Action Learning. Thirdly, learners ought to solve the problems faced during the learning process on their own. Fourthly, the aims of courses for Essential Competencies are also needed to be focused.

In this study, I examined the concept of action learning, its characteristics, operation method, and action learning cases in domestic and foreign countries. Also, I studied the possibility of using action learning in teaching healthy family specialist education. I researched the wellbeing action learning held from June 10 to June 20, 2007, with 20 participants. I conducted interviews and wrote a paper about how much action learning subjects were helped in their improving task-handling ability, its merits and drawbacks, and suggestions the subjects had about their participation in. The results were as shown below. First, the Catholic Welfare Department of Baekseok Uuniversity developed and operated action learning subjects to improve task-handling abilities in NURY business. Second, the action team valuated its subjects that everyone had fear and burden about action learning, but as time goes by, their confidence and adaptation ability have been improved. Also, organization staff and coaches answered that it was helpful to their self-development and improve capacity.

Recently, extensive studies have been conducted to apply deep learning to reinforcement learning to solve the state-space problem. If the state-space problem was solved, reinforcement learning would become applicable in various fields. For example, users can utilize dance-tutorial systems to learn how to dance by watching and imitating a virtual instructor. The instructor can perform the optimal dance to the music, to which reinforcement learning is applied. In this study, we propose a method of reinforcement learning in which the action space is dynamically adjusted. Because actions that are not performed or are unlikely to be optimal are not learned, and the state space is not allocated, the learning time can be shortened, and the state space can be reduced. In an experiment, the proposed method shows results similar to those of traditional Q-learning even when the state space of the proposed method is reduced to approximately 0.33% of that of Q-learning. Consequently, the proposed method reduces the cost and time required for learning. Traditional Q-learning requires 6 million state spaces for learning 100,000 times. In contrast, the proposed method requires only 20,000 state spaces. A higher winning rate can be achieved in a shorter period of time by retrieving 20,000 state spaces instead of 6 million.

Purpose: This study examined the influence of visuomotor congruency on learning a relative phase relationship between a single joint movement and an external signal. Methods: Participants (N=5) were required to rhythmically coordinate elbow flexion-extension movements with a continuous sinusoidal wave (0.375 Hz) at a $90^{\circ}$ relative phase relationship. The congruent group was provided online feedback in which the elbow angle decreased (corresponding to elbow flexion) as the angle trajectory was movingup, and vice versa. The incongruent group was provided online feedback in which the elbow angle decreased as the angle trajectory was moving down, and vice versa. There were two practice sessions (day 1 and 2) and each session consisted of 6 trials per block (5 blocks per session). Retention tests were performed 24 hours after session 2, and only the external sinusoidal wave was provided. Repeated ANOVAs were used for statistical analysis. Results: During practice, the congruent group was significantly less variable than the incongruent group. Phase variability in the incongruent group did not significantly change across blocks, while variability decreased significantly in the congruent group. In retention, the congruent group produced the required $90^{\circ}$ relative phase pattern with significantly less phase variability than the incongruent group. Conclusions: Congruent visual feedback facilitates learning. Moreover, the deprivation of online feedback does not affect the congruent group but does affect the incongruent group in retention.

Recent advances in deep learning have facilitated widespread deployment of posture recognition system. However, the scarcity of accessible human posture datasets presents a significant challenge to achieving high model precision and robustness. To address this challenge, we introduce a federated learning (FL) framework that enables training of posture recognition models across diverse and privacy-sensitive datasets. Our approach integrates FL strategies with fundamental deep learning architectures for human pose estimation and action recognition. To identify the optimal base model, we evaluate five widely adopted architectures. Using a posture recognition dataset, our systematically compare conventional single-machine training models with FL-enhanced models across key metrics: precision, recall, F1-score, and accuracy. Results demonstrate that our FeLM achieves superior generalization while preserving data privacy, highlighting the efficacy of FL in posture recognition tasks. This underscores the benefit of FL in improving the generalization of a model without compromising data privacy.

How can action learning program promote organizational learning performance and especially project based team performance in Web-based small and medium-sized enterprises (SMEs)? This article discusses the association between project based team in action learning program and the performance of Web-based SME to be learning organization. In the case of ALPACO, action learning program that promote employee communication behavior, knowledge sharing, and organizational learning are found to be positively associated with the project based team performance and organizational learning. The results indicate that action learning program in SMEs indeed associated with greater knowledge sharing, learning communication skills and changing organizational culture. Learning organization can be, in turn, positively developed by project based team through action learning program for creating competitive advantage. Also, this study offers further support for the practical perspective on learning organization performance. The evidence from this case study suggests that the project team in action learning program play a significant role in team performance and the development of learning organization of the firm. Therefore, in the future, Web-based SMEs should consider making investments in action learning program that encourage project team’s effective management in decision making, knowledge sharing, and organizational learning.

본 연구는 스페인어 학습자를 위한 액션러닝을 활용한 소통강화 교수학습 모형을 제안하고 스페인어 수업 사례 연구를 통하여 그 효과를 검증하는 데 있다. 본 연구는 2019년 9월1일부터 12월20일까지 교양 스페인어 수강생 91명 을 실험반과 통제반으로 나누어 동일한 조건 하에 진행하였지만 실험반의 경우에는 액션러닝을 활용한 소통강화 교수 학습모형을 적용하였다. 즉, 교사주도하의 개인적 쓰기활동으로 이루어진 통제반과는 다르게 실험반은 팀별 자유로운 토의와 협력활동을 통해 쓰기활동을 하도록 하였다. 실험 결과, 두 반 모두 쓰기 능력에 있어서는 어느 정도 향상되었 지만, 액션러닝을 적용한 실험반의 학습자들이 글의 내용, 표현, 유창성 측면에서 더 유의마한 결과를 나타냈고 정의적 영역 검사에서도 유의미한 차이를 가져왔다. 학습자 중심 융합 활동에 필요한 이러한 수업모형의 개발은 비단 스페인어 의사소통의 향상뿐만 아니라 다른 외국어 수업활동에 활용할 수 있기 때문에 학문적의의가 있을 것으로 본다.

This study is to propose a communication strengthening teaching model using action learning for Spanish learners, and to verify its effectiveness through a case study of Spanish lessons. This study was conducted under the same conditions by dividing 91 students from September 1 to December 20, 2019 into experiment and control classes. As a result of the experiment, both classes improved their writing ability to some extent, but the learners in the experimental class applying action learning showed more meaningful results in terms of the content, expressions, fluency of the text, and the affective domain test also showed a significant difference. The development of this teaching model, which is necessary for learner-centered convergence activities, is expected to be of academic significance as it can be used for other foreign language class activities as well as improving Spanish communication.

본 연구의 목적은 교양영어 학습자들을 대상으로 실천학습(Action learning) 기법을 활용한 영어 수업 사례 연구를 통하여 그 효과를 알아보고자 했다. 본 연구는 학습자 중심 수업을 기본으로 하여 학습자 간의 상호수정 활동을 통해 영어 기술을 익힐 수 있다는 것에 연구의 가치를 두고 실천학습(Action learning)을 수업에 활용함으로써 그 효과 를 알아보고자 했다. 2018년 3월 1일부터 2018년 6월15일까지 교양 영어 두개 반(실험반, 통제반) 학생을 대상으로 하였으며 실험 집단은 실천학습(Action learning) 협력기법을 활용한 협력쓰기 수업을 진행하고, 통제 반은 교수자가 기존에 하던 방식의 쓰기 수업을 진행하여 비교하였다. 본 연구의 연구문제는 실천학습(Action learning) 기법을 적용한 협력 쓰기 활동이 학생들의 쓰기 유창성에 어떠한 영향을 미치는가를 알아보고자했다. 연구결과, 실험집단의 경우 단어 의 수, 문장의 수와 문장 길이 등의 쓰기의 유창성 부분에서 통계적으로 유의미한 결과를 가져왔다. 학습자들은 학습 관계에서 더 깊이 있게 다른 사람들이 지닌 지식이나 생각을 공유하고 보다 규칙적인 근거를 가지고 근접발달영역 들어 갈 수 있었다.

The purpose of this study is to investigate the effect of action learning methods and practices, which have a research focus on learner-centered teaching after training students to use collaborative learning practices from the viewpoint that the learners acquire English skills through peer correction activities based on sociocultural learning theory[1]. From March 1, 2018 to June 15, 2018, one control class and one experimental group were selected from the general freshman English courses. The experimental group attended classes centered on collaborative writing activities using action learning and cooperation techniques, and the control group attended classes lecture style and rote learning methods to teach writing. The result of study has shown that, for the experimental group, there have been statistically significant results in the production of writing, such as the number of words, the number of sentences, and sentence length. Learners could share the knowledge or ideas of others in their learning relationships with more regular basis.

Past 20 years have witnessed the shift of focus in language teaching from teacher-oriented to learner-centered approach. Although there have been several research studies on cooperative learning, they were limited to the defining of its constructs and pedagogical values, and the surveying of teachers’ beliefs and their practices at school. This paper looks into the experiences that a teacher had in the attempt to change her teaching practice with cooperative learning techniques applied in an EFL reading class. It was also an effort to improve from her previous teaching method which had been grammar-translation mixed with a task-based approach. The process of a teacher’s implementation of a newly adopted class approach including decision-making, operating, interpreting/reflecting is shared through the first-person action research. Various data sources were presented to assess the legitimacy of accepting cooperative learning via group work as a valuable, viable instructional method in the real language classroom. A detailed description of a teacher’s experiences in the self-transforming process is provided along with guidelines to make classrooms successful cooperative language learning places.

본 연구는 신입 간호대학생들이 해부학 학습에서 겪는 인지적 부담과 제한된 개념 통합 시간을 보완하기 위해 생성형 AI와 멘토–멘티 기반 동료학습을 결합한 학습공동체를 개발·운영하고, 그 학습경험을 탐색하는 데 목적이 있다. 8주간 프로그램에는 1학년 4명과 2학년 멘토 2명이 참여하였으며, 수집된 자료는 귀납적 내용분석 으로 분석되었다. 분석 결과, 동료 지지는 학습 동기를 강화하였고, 생성형 AI는 용어 정리, 문제 생성, 즉각적 피드백을 통해 개념 이해를 촉진하였으며, 지속적 참여는 학습습관과 학업 자신감을 향상시키는 것으로 나타났다. 본 프로그램은 인지적 부담을 줄이고 기초 해부학 학습을 강화하는 데 효과적이었다. 향후 연구에서는 이 AI 지원 학습공동체 모형을 생리학·병리학·약리학 등 다른 기초간호학 교과목으로 확장하여 적용성을 검증하고, 학습 성과 의 장기적 지속 여부를 확인하는 종단 연구가 필요하다.

This study developed an AI-supported mentor–mentee learning community to reduce cognitive burden and improve anatomy learning among first-year nursing students. Four first-year students and two second-year mentors participated in an eight-week program, and data were analyzed using inductive content analysis. Peer support increased motivation, AI enhanced conceptual understanding, and consistent participation improved study habits and confidence. The model effectively strengthened foundational learning. Future research should apply this model to other basic nursing courses and evaluate its long-term effects.

Local governments need to continuously enhance their staff’s disaster response capabilities by incorporating the latest knowledge and experience. Recently, after-action reports have been frequently published by local governments to review their disaster responses. Although learning from these reports is effective for improving disaster response capacity, it is not easy for local government officers to spend sufficient time learning from them. In this study, a method to efficiently extract lessons learned from after-action reports on local government disaster response was developed. First, cases of critical situations during emergency responses were collected from after-action reports published after recent disasters. Next, a deep learning model based on a language model (BERT) was developed using the collected cases as training data. The model enables the extraction of new cases similar to the collected ones from after-action reports. As the developed model was able to extract new cases with high accuracy, it may contribute to the efficient learning and analysis of lessons learned from after-action reports. On the other hand, the findings suggested the need to explore the optimal amount of training data required to achieve high accuracy and stable learning performance. After these efforts were started with after-action reports of flood disasters, the reports of earthquake and tsunami disasters were also added as the targets. Finally, a support system was developed to extract lessons from after-action reports using the proposed model and to present accumulated lessons efficiently. This system enables users to explore the latest lessons from recently published after-action reports and enhance their capabilities based on these lessons.