Earticle

본고는 중국 대학 내 효과적인 한국어 문장구역 교육을 이루기 위해 플립러닝과 협동학습 을 활용하는 한국어 문장구역 수업 모형을 개발하는 데에 목적이 있다. 문장구역은 통역사가 눈으로 출발어 텍스트를 읽으면서 도착어로 말하는 통역 방식으로서 순차통역과 동시통역에 비해 난이도가 상대적으로 낮다. 또한 문장구역 훈련은 학습자의 한국어 능력과 기본적인 통 역 능력 등을 신장할 수 있다는 점에서 학부의 한국어 전공 학습자에게 적합한 교육 방법으로 활용할 수 있다. 그러므로 본 연구는 학부에서 한국어 문장구역 수업을 개설할 필요성을 확인 하고 중국에서의 한국어 전공 학습자의 요구를 파악하며 문장구역 수업 모형을 설계하였다. 본고에서는 한국어 문장구역 수업을 단계별로 나누어 교사와 학습자의 역할을 설명하였다. 수업 전 단계에 교사는 ‘교육 목표 설정’, ‘문장구역 텍스트 선정’, ‘텍스트 분석’, ‘동영상 촬 영’, ‘소그룹 편성’, 학습자는 ‘동영상 학습’, ‘병렬텍스트 작성’, ‘문제점 정리’를 수행하는 것이 다. 수업 단계에 교사는 ‘질의응답’, ‘조 활동을 만들기’, ‘통역 활동을 모니터링하기’, ‘피드백 하기’, 학습자는 ‘조별로 통역하기’, ‘녹음하기’, ‘동료 피드백하기’, ‘질의응답’을 수행한다. 수 업 후 단계에 교사는 학습 성과를 확인하는 것이고 학습자는 ‘녹음 및 학습 내용 정리’, ‘조별 로 섀도잉 연습’, ‘통역일지 작성’, ‘자기평가서 작성’ 활동을 수행하는 것이다.

This paper aims to develop a classroom model for Sight Translation education in Chinese universities by leveraging flipped learning and cooperative learning methods. Sight Translation, a mode of interpretation where interpreters orally translate source text while reading it, poses relatively lower difficulty compared to consecutive and simultaneous interpretation. Moreover, it can enhance learners’ Korean proficiency and basic interpretation skills, making it a suitable educational approach for Korean language majors in undergraduate programs. Consequently, this study validates the necessity of offering Korean Sight Translation classes at the undergraduate level, identifies the demands of Korean language majors in Chinese universities, and designs a classroom model for Sight Translation education. The paper delineates the roles of teachers and learners in each stage of the Korean Sight Translation classes. Pre-class stages involve teachers setting educational objectives, selecting texts, analyzing texts, recording videos, and organizing subgroups, while learners engage in video-based learning, parallel texts, and summarizing questions. During class stages, teachers facilitate question-and-answer sessions, create team activities, monitor interpretation activities, and provide feedback, while learners participate in group interpretation, recording, peer feedback, and question-and-answer sessions. Post-class stages entail teachers assessing learning outcomes, while learners engage in activities such as summarizing recorded content, group shadowing exercises, writing interpretation journals, and self-assessment reports.

Purpose: This study aimed to identify latent classifications based on trajectories of change in depressive symptoms among multicultural adolescents in middle and high school and to identify factors that influence classification. Methods: This study used six time-point data from the Multicultural Adolescents Panel Study (MAPS) conducted by the National Youth Policy Institute (NYPI). We longitudinally analyzed data from 2014 to 2019, which corresponds to the participants' middle and high school years. Latent Growth Curve Modeling (LGCM) was used to analyze the depressive developmental trajectories of multicultural youth in middle and high school. Latent Class Growth Modeling (LCGM) was used to determine the number and shape of latent classes according to the type of depression among multicultural adolescents. We applied multinomial logistics regression analysis to explore the predictors of each class. Results: A model with three latent classes was identified: (1) low-decreasing class (intercept=13.34, slope=-0.07, 37.9%), (2) moderate-increasing class (intercept=17.76, slope=0.41, 47.6%), (3) high-increasing class (intercept=23.22, slope=0.44, 14.5%). Multinomial logistic regression showed multicultural adolescents who were male, experienced high acculturative stress and social withdrawal, and had low self-esteem, life satisfaction, and family support tended to belong to either the moderate-increasing or high-increasing class. Conclusion: These findings suggest that preliminary assessments of gender, acculturation stress, self-esteem, life satisfaction, social withdrawal, and family support among multicultural adolescents may be valuable for developing tailored mental health programs.

교통계획에서 사람들의 수단선택 의사 결정과정을 이해하고 이를 토대로 수요예측의 정확 성을 높이는 것은 매우 중요하다. 이를 위해 여러 계층마다 수단선택 영향요인들이 다르게 나 타나는 이질성(taste heterogeneity)을 반영한 모형들이 개발되어 왔다. 본 연구에서는 목적지의 토지이용 특성에 따라 수단선택에 미치는 요인의 영향력이 다를 것이라는 가설을 세우고 2010 년 서울시 가구통행실태조사 자료를 활용하여 서울시내 출근통행에 대한 잠재계층모형을 분 석하였다. 먼저 목적지의 토지이용 특성을 활용하여 수단선택에 대한 잠재계층을 구분하고, 각 각의 잠재계층에 대한 수단선택 모형을 개발하였다. 잠재계층모형 추정결과, 서울시내 출근통 행 수단선택의 경우 두 개의 잠재계층으로 분석되었다. 첫 번째 계층은 승용차와 대중교통의 수단분담이 비슷하고, 목적지가 상대적으로 도심이 아닌 주거시설이 많은 지역들이고, 두 번째 계층은 주로 대중교통의 분담률이 높고 목적지가 상대적으로 도심에 속하는 업무/상업시설이 많은 지역이다. 또한 이들 계층간의 수단선택 모형의 경우, 인구 및 사회경제지표들의 수단선 택에 미치는 영향이 계층간에 차이가 있는 것으로 분석되었다.

It is crucial to understand how people make decisions on mode choice and to accurately predict their behaviors in transportation planning. One of avenues for advancing modeling is, in particular, taking into account for taste heterogeneity in modeling that can incorporate different decision-making processes across group. In this study, we hypothesize that how people make decisions on mode choice would differ by destination in that land use characteristics are heterogeneous by zone even if zones are all in the same area. To this end, we apply Latent Class Modeling (LCM) to commute trips in Seoul by using 2010 household travel diary survey, investigate types of latent classes with the aid of characteristics of destination, and analyze how those classes differently response to factors. The LCM identifies two classes: in the first one, modal split of auto and public transit (bus and metro) is almost half-and-half and the trip destinations are characterized by relatively more residence facilities and less business/commercial facilities; in the second one, public transit has a notably high share and trip destinations are characterized by relatively more business/commercial facilities. In addition, it turns out that demographic and socio-economic variables affect mode choice differently by class.

Capsule endoscopy is one of the increasingly demanded diagnostic methods among patients in recent years because of its ability to observe small intestine difficulties. It is often conducted for 12 to 14 hours, but significant frames constitute only 10% of whole frames. Thus, it has been designed to automatically acquire significant frames through deep learning. For example, studies to track the position of the capsule (stomach, small intestine, etc.) or to extract lesion-related information (polyps, etc.) have been conducted. However, although grouping or labeling the training images according to similar features can improve the performance of a learning model, various attributes (such as degree of wrinkles, presence of valves, etc.) are not considered in conventional approaches. Therefore, we propose a class-labeling method that can be used to design a learning model by constructing a knowledge model focused on main lesions defined in standard terminologies for capsule endoscopy (minimal standard terminology, capsule endoscopy structured terminology). This method enables the designing of a systematic learning model by labeling detailed classes through differentiation of similar characteristics.

This study explores the effect of a humanities-based convergent class model (HBCCM) on critical thinking (CT) when Kakao-Talk is utilized as a virtual learning space to acquire new knowledge using flipped learning (FL). Its objective is to promote EFL undergraduates’ (n=51) participation in face-to-face discussion activities by getting them to prepare before coming to class. The preliminary learning contents and conceptual knowledge organized into specific argumentative topics based on Thomas Hardy’s Tess of the D’Urbervilles and Foucault’s philosophical perspective of Sexuality, Madness and Power were provided via Kakao-Talk. Students could experience a self-regulatory learning process outside of class and develop their ideas with peers' through in-class discussion. While the collaborative learning through group activities promoted social interaction, interdependence and critical analysis, the students self-evaluated their ideas clearly. Qualitative and quantitative methodologies including Watson-Glaser's (W-G) CT assessment were conducted to evaluate the change of CT skills. The results showed the significant interaction of the CT skills. In particular, the students improved the skills of recognizing assumption, deductive reasoning and evaluating arguments as they experienced CT-efficacy through this learning process. Accordingly, HBCCM may contribute to the higher education for activating CT and the improvement of a teaching and learning method.

The purpose of this study is to verification of relationship model be-tween Korean new elderly class’s recovery resilience and productive aging. As of 2013, this study sampled preliminary elderly people in Gyeonggi-do and other provinces nationwide. Data from a total of ef-fective 484 subjects was analyzed. The collected data was processed using the IBM SPSS 20.0 and AMOS 20.0, and underwent descriptive statistical analysis, confirmatory factor analysis, and structure model verification. The path coefficient associated with model fitness was ex-amined. The standardization path coefficient between recovery resil-ience and productive aging is β=0.975 (t=14.790), revealing a statisti-cally significant positive effect. Thus, it was found that the proposed ba-sic model on the direct path of recovery resilience and productive aging was fit for the model.

This paper presents an innovative method for reconstructing 3D models from 2D stereoscopic images captured from the front, back, left, and right sides of an object at 90 - degree horizontal rotations. The proposed process involves several key steps: plant class segmentation using artificial intelligence (AI), disparity and depth mapping from stereo images, point cloud generation, merging multiple point clouds into a single unified point cloud, and mesh application to ensure surface continuity of the 3D model. Recognizing the critical role of accurate segmentation in 3D reconstruction, this study compares two AI segmentation architectures-YOLOv8 and Detectron2-to determine which performs better in terms of segmentation accuracy, training speed, and memory consumption for the plant class. This research focuses on the 3D reconstruction phase of a parent study titled "Investigating Deep Learning for Predicting and Simulating Plant Growth Structures: A Preparatory Effort Towards the Digital Twin Paradigm in Agriculture," whose dataset comprises 2D stereo images of plants that require 3D visualization. Its long-term vision is to develop a user experience that assists farmers in making informed decisions by leveraging predictive models and 3D visualizations of crop growth.

In order to obtain ultra-high resolution MRI images, research and development of 11 T or higher superconducting magnets have been actively conducted in the world, recently. The high-temperature superconductor (HTS), first discovered in 1986, was very limited in industrial application until mid-2010, despite its high critical current characteristics in the high magnetic field compared to the low-temperature superconductor. This is because HTS magnets were unable to operate stably due to the thermal damage when a quench occurred. With the introduction of no-insulation (NI) HTS magnet winding technology that does not burn electrically, it could be expected that the HTS magnets are dramatically reduced in weight, volume, and cost. In this paper, a 6 T-class NI HTS magnet for basic characteristic analysis was designed, and a distributed equivalent circuit model of the NI coils was configured to analyze the charging current characteristics caused by excitation current, and the charge delay phenomenon and loss were predicted through the development of a simulation model. Additionally, the critical current of the NI HTS magnets was estimated, considering the magnetic field, its angle and temperature with a given current. The loss due to charging delay characteristics was analyzed and the result was shown. It is meaningful to obtain detailed operation technology to secure a stable operation protocol for a 6T NI HTS magnet which is actually manufactured.

최근 연구데이터가 국가자산이라는 인식의 확산으로 원시데이터 관리 및 재사용의 필요성이 이슈이다. 본 연구에서는 데이터의 체계적인 관리를 위해, 스키마 클래스를 상속하는 방식의 메타데이터 설계 모델과 상속을 통해 생성된 스키마 객체들을 대상으로 메타데이터 통합 검색 모델을 제안하였다. 스키마 클래스를 상속한 스키마 객체가 데이터 컬렉션에 1대1의 관계를 갖도록 데이터 아키텍처를 설계하였으며, 제안된 모델의 검증을 위해서 가상 스키마 클래스 및 객체가 시스템적으로 구현 가능함을 증명하였다. 본 연구에서 제안하는 스키마 클래스 상속 및 통합검색 모델은 일반적으로 사용되는 '하향식 계층 모델'의 단점을 극복하는 모델로서, 정부 기관에서 생산되는 데이터를 독립적으로 관리하는데 활용될 수 있다고 사료된다.

The necessity of the raw data management and reuse is issued by diffusion of the recognition that research data is a national asset. In this paper, a metadata design model by schema class inheritance and a metadata integrated search model by schema objects are suggested for a structural management of the data. A data architecture in which an schema object has an 1 : 1 relation to the data collection was designed. A suggested model was testified by creation of a virtual schema class and objects which inherit the schema class. It showed the possibility of implement systematically. A suggested model can be used to manage the data which are produced by government agencies because schema inheritance and integrated search model present way to overcome the weak points of the 'Top-dow Hierarchy model' which is being used to design the metadata schema.

본 연구에서는 아동발달의 변화성과 다양성을 고려하여 시간의 경과에 따라 학령기 아동의 게임 사용시간의 변화궤적을 유형화하고, 각 유형에 영향을 미치는 예측요인을 다차원적으로 검증하였다. 이를 위해 한국아동·청소년패널조사의 초1패널의 2차년도에서 6차년도까지의 자료를 활용하였으며, 본 연구의 최종 분석대상자는 총 1959명이다. 분석방법으로는 학령기 아동의 게임 사용시간 변화궤적 유형화를 위해서 잠재계층성장분석을 실시하였으며, 이후 다중로지스틱 회귀분석을 통해 유의미한 예측요인을 검증하였다. 분석결과, 학령기 아동의 게임 사용시간 변화궤적은 ‘게임 저사용 증가집단’, ‘게임 초기 고사용-변동 집단’, ‘게임 고사용 증가집단’으로 분류되었으며, 성별, 공격성, 주의집중, 방과후 보호자 부재, 주양육자의 교육수준, 형제자매, 방임, 가구소득, 연간 가족여행 횟수, 학교성적, 또래관계가 각 유형의 분류에 유의미한 영향을 미치는 예측변인으로 나타났다. 이러한 연구결과들을 바탕으로 학령기 초기 아동의 게임 과다사용에 대한 예방적 개입의 필요성을 강조하고 유용한 실천적 제언을 하였다.

This study aimed to explore the trajectories of computer game use of school age children and to identify the related predictors. The data for this study used Korean Children and Youth Panel data covering from the second year to the sixth year of elementary school. A total of 1,959 participants were analyzed. Latent class growth model was employed to explore the trajectories of computer game use and multinomial logistic regression was conducted to identify the significant predictors. Main results indicated that three types of trajectories were identified: low game using group, high initial using-fluctuating group, and high increasing game using group. Each group was found to be associated deferentially with sex, aggression, attention deficit, main caregiver’s education, siblings, parent absence after-school, neglecting, family income, family trip, school grades, and peer relationship. Based on these findings, this study emphasized the importance of predictive intervention for the game user among early school age children and suggested useful practical strategies.

본 연구는 지체장애인의 경제적 노후준비의 다양성과 변화성을 고려하여 시간의 경과에 따라 나타나는 경제적 노후준비의 변화궤적을 유형화하고, 그에 영향을 미치는 결정요인들의 영향력을 Andersen의 모형에 따라 검증하였다. 이를 위해 장애인고용패널 2차년도(2009)부터 8차년도(2015)까지 총 7개년의 자료를 활용하였으며, 분석에 사용된 대상자는 총 1847명이다. 장애인의 경제적 노후준비에 관한 종단적 변화유형을 파악하기 위해서는 잠재계층성장분석(LCGA)을 실시하였으며, 이후 분류된 유형에 대한 결정요인들의 영향력을 살펴보기 위해서는 다항로지스틱회귀분석을 실시하였다. 분석결과, 지체장애인의 경제적 노후준비 종단적 변화유형은 노후준비감소집단, 비노후준비지속집단, 노후준비증가집단, 노후준비유지집단으로 구분되었으며, 결정요인으로는 교육수준, 소득, 사회경제적 지위, 취업, 주택소유, 국민기초생활보장제도 수급여부, 일상생활능력정도가 각 유형의 분류에 유의미한 영향을 미치는 것으로 나타났다. 이러한 결과에 따라 지체장애인의 경제적 노후준비를 촉진할 수 있는 구체적이고 차별화된 대응방안과 실질적인 정책적 제언을 제시하였다.

This study aimed to explore the trajectories of economic preparations for the aging among people with physical disabilities and to identify the determinants according to the Andersen model. For this study, data were drawn from Panel Survey of Employment for the Disabled (PSED). A total of 1,847 samples were used from the second to the eighth wave. Latent class growth model was conducted to explore the longitudinal change classes for the disabled, and the multinominal logistic regression analysis was conducted to examine the influence of the determinants. As a result, four classes were identified: preparation decrease group, continuous non-preparation group, preparation increase group, and continuous preparation group. Each group was found to be associated deferentially with education level, family income, socioeconomic status, employment, home ownership, national basic livelihood security recipient status, and ADL. These findings proposed the practical and political implications for the strategies concerned with facilitating the economic preparations for the aging among the disabled.

딥러닝 분류 모델에 대한 공격 중 하나인 적대적 공격은 입력 데이터에 인간이 구별할 수 없는 섭동을 추가하여 딥러닝 분류 모델이 잘못 분류하도록 만드는 공격이며, 다양한 적대적 공격 알고리즘이 존재한다. 이에 따라 적대적 데이터를 탐지하는 연구는 많이 진행되었으나 적대적 데이터가 어떤 적대적 공격 알고리즘에 의해 생성되었는지 분류하는 연구는 매우 적게 진행되었다. 적대적 공격을 분류할 수 있다면, 공격 간의 차이를 분석하여 더욱 견고한 딥러닝 분류 모델을 구축할 수 있을 것이다. 본 논문에서는 공격 대상 딥러닝 모델이 예측하는 클래스를 기반으로 은닉층의 출력값에서 특징을 추출하고 추출된 특징을 입력으로 하는 랜덤 포레스트 분류 모델을 구축하여 적대적 공격을 탐지 및 분류하는 모델을 제안한다. 실험 결과 제안한 모델은 최신의 적대적 공격 탐지 및 분류 모델보다 정상 데이터의 경우 3.02%, 적대적 데이터의 경우 0.80% 높은 정확도를 보였으며, 기존 연구에서 분류하지 않았던 새로운 공격을 분류한다.

Adversarial attack, one of the attacks on deep learning classification model, is attack that add indistinguishable perturbations to input data and cause deep learning classification model to misclassify the input data. There are various adversarial attack algorithms. Accordingly, many studies have been conducted to detect adversarial attack but few studies have been conducted to classify what adversarial attack algorithms to generate adversarial input. if adversarial attacks can be classified, more robust deep learning classification model can be established by analyzing differences between attacks. In this paper, we proposed a model that detects and classifies adversarial attacks by constructing a random forest classification model with input features extracted from a target deep learning model. In feature extraction, feature is extracted from a output value of hidden layer based on class predicted by the target deep learning model. Through Experiments the model proposed has shown 3.02% accuracy on clean data, 0.80% accuracy on adversarial data higher than the result of pre-existing studies and classify new adversarial attack that was not classified in pre-existing studies.

Background: Project-based learning is a teaching method that employs the problem-solving process while carrying out a project. This study aims to find out the learning experiences in the problem solving process by applying project-based learning classes to the physical therapy students of Wonkwang Health University. Design: Qualitative case study. Methods: The project-based learning process comprised the pre-preparation stage (Preparation class), the preparation stage (Pre-class), the execution stage (In-class), and the finishing stage (Post-class). In the pre-preparation stage, background knowledge about life and environment was acquired. In the preparation stage, team-building, topic selection, problem specification, and planning were addressed. In the execution phase, field survey, data arrangement, data analysis, and interim checklist were conducted. In the final stage, group discussion, group presentation, feedback-correction and supplementation, and final results were submitted. Results: This study operated a class for 15 weeks, and analyzed the results obtained from self-questionnaires and narrative responses. Students divided their roles in to groups and actively participated in problem-solving, and experienced self-directed learning. Conclusion: The project-based learning is an innovative teaching method that can lead to improvement in the problem-solving ability, creativity, and social skills of the physical therapy students.

최근 인터넷의 급격한 확장에 따른 정보의 양이 기하급수적으로 증가하고 있다. 그러나 실제 사용자에게 필요한 정보는 극히 일부분으로 사용자가 원하는 정보를 찾는데 까지는 부가적인 시간과 노력이 요구된다. 따라서 검색어로 검색된 문서에 대한 유사도 평가를 통한 계층적 유사 정보와 검색 우선순위에 대한 정보를 제공할 필요성이 있다. 이를 위해서 검색어를 구성하고 있는 키워드의 동시 발생 빈도를 고려한 검색 문서에 대한 유사도를 기반으로 문서 클러스터를 구성하고 SVM을 적용한 빅 데이터 기반 계층적 유형 분류 모델을 제안한다. 계층적 분류방법과 SVM 분류기의 결합은 문서의 계층이 기하급수적으로 늘어나는 웹 문서의 경우에 높은 성능을 얻을 수 있다. 제안된 모델은 정확하고 신속한 검색을 제공하는 정보검색시스템의 응용 모델로 활용될 수 있다.

Recently data growth rates are growing exponentially according to the rapid expansion of internet. Since users need some of all the information, they carry a heavy workload for examination and discovery of the necessary contents. Therefore information retrieval must provide hierarchical class information and the priority of examination through the evaluation of similarity on query and documents. In this paper we propose an Multi-class support vector machines model based clustering for hierarchical document categorization that make semantic search possible considering the word co-occurrence measures. A combination of hierarchical document categorization and SVM classifier gives high performance for analytical classification of web documents that increase exponentially according to extension of document hierarchy. More information retrieval systems are expected to use our proposed model in their developments and can perform a accurate and rapid information retrieval service.

본 연구는 지금까지 연구가 많이 이루어지지 않았던 사범계열이면서 인문사회분야인 영어교육에서의 (1)캡스톤디자인 수업 설계와 실제 운영의 예시를 제시하고 (2)캡스톤디자인 수업의 성과와 만족도를 포함한 학생들의 인식을 알아보는 것을 목적으로 하였다. 대상은 영어교육과에 재학 중인 4학년 학생들이었고 영어교육과 전공수업인 '영미문화' 교과목의 과목명을 '영미문화교육 캡스톤디자인'으로 변경 후 수업 모델을 개발, 적용, 성과를 확인하였다. 본 연구에서는 수업의 설계와 수행 절차, 도출된 주제, 수행 결과물의 예시 등을 제시하였고 영미문화 이해도 평가, 과제 수행 및 최종 결과물 평가, 학생들의 서술형 만족도 조사와 강의평가, 교사의 자기 성찰 평가도 수행하였다. 과제수행의 평가 결과 2017년과 2018년의 모든 팀이 비교적 높은 성취도를 보였다는 것을 알 수 있었고 영미문화 이해도의 경우, 캡스톤디자인을 적용하지 않고 강의와 학생들의 발표로 이루어진 수업과 캡스톤디자인을 적용한 수업에서 유의미한 차이가 없었다. 강의평가 점수의 경우는 캡스톤디자인을 영미문화 수업에 적용한 수업의 강의평가 점수가 높았다.

The purpose of this study is (1) to present a model for Capstone design class in English education, and (2) to recognize students' performance and perceptions about Capstone design class in English education. The participants were senior students majoring in English education. The Capstone design class model was developed, applied, and evaluated after changing 'English-American Culture' subject to 'Capstone Design for English-American Culture Education.' In this study, the class design, performance procedures, derived topics, and examples of performance outcomes were presented. The classes were also evaluated through an understanding evaluation of English-American culture, task performance and final outcome evaluation, a descriptive satisfaction assessment of students, a lecture evaluation, and a teacher's self-reflection assessment. As the result, the average score of a class that applies Capstone design was higher than that of a class that does not apply the Capstone design. There were many positive opinions regarding the Capstone design class. In addition, the teacher's self-reflection indicated that students should be exposed to such design from the beginning.

본 연구의 목적은 자유학기제에 활용 가능한 학교상담자용 학급단위 집단상담 모형을 개발하고 타당화 하는 것이었다. 이를 위해, 본 연구에서는 먼저 선행연구를 고찰하고, 설문조사, 포커스 면접 조사, 전문가 협의회를 실시하여 내용 영역, 조직적인 틀 영역, 소요자원 영역으로 구성된 잠정 모형을 구안하였다. 구안된 잠정 모형은 40명의 학교상담 현장 전문가인 전문상담교사 패널들의 1차, 2차에 걸친 델파이 조사를 통해 내용타당도를 확보하여 최종 모형으로 확정되었다. 본 연구의 연구결과는 다음과 같다. 최종 구안된 자유학기제에 활용 가능한 학교상담자용 학급단위 집단상담 모형은 총 3영역(내용 영역, 조직인인 틀 영역, 소요자원 영역)으로 구성되었다. 첫 번째, 내용 영역으로 3개 영역(자신에 대한 이해와 수용, 의사결정하기, 타인을 이해하고 사이좋게 지내기)으로 구성되었다. 두 번째, 조직적인 틀 영역으로 4개 영역(가용시간, 운영 회기 수, 자유학기제 중 적합한 모형, 프로그램 운영)으로 구성되었다. 세 번째 소요자원 영역은 5개 영역(프로그램 운영자, 필요 역량, 역량개발 방법, 재정적 지원, 행정적 지원)으로 구성되었다. 이러한 본 연구는 중학교에서 학교상담자의 역할 정립과 학급단위 집단상담을 운영할 수 있는 역량강화 방안을 마련하는 데 도움이 되는 모델을 제공했다는 점에서 의의가 있다.

The purpose of this study was to develop and validate a class unit group counseling model for school counselors to use the free-semester program. In order to accomplish the purpose, first of all this study reviewed the previous research studies, and conducted a survey, a focus group interview, and an expert meeting to develop a proposed model, which consists of the content area, the organizational frame area, and the required resource area. The proposed tentative model was confirmed as the final model by securing content validity through the first and second Delphi surveys of panels of professional counselors who are 40 school counseling field experts. The research results of this study are as follows. The class unit group counseling model for school counselors that can be used in the final proposed free semester system consisted of a total of three areas (content area, organizational frame area, and required resource area). The content area includes three sub-areas(understanding and accepting oneself, making a decision, understanding others and getting along well). The organizational framework includes four sub-areas(available time, number of operational sessions, a most suitable model among the free-semester models, and program operation). The required resource area includes five sub-areas (program operator, required capacity, capacity development method, financial support, and administrative support). This study is significant in that it provides a model for looking for a solution to establish the role of school counselors and to enhance their competency to manage class unit group counseling with middle school students.