• 의학교육논단
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• 제13권2호
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• pp.9-23
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• 2011

This study aimed to investigate the effects of tutors' domain and teaching expertise on learning outcomes in a problem based learning (PBL) environment. Four tutors and 25 first-year medical students participated in this study. Tutors' domain expertise was classified by clinical or non-clinical which is basic medicine and teaching expertise by previous tutoring experiences or not. The results showed a statistically significant difference in achievement depending on the tutors' domain expertise. Students grouped with an experienced clinical tutor attained higher achievement scores than those with an experienced non-clinical tutor, while those with an inexperienced non-clinical tutor attained higher scores than those with both inexperienced clinical tutors and experienced non-clinical tutors. Students with clinical medicine tutors also showed higher satisfaction scores than those with non-clinical medicine tutors. In particular, students grouped with an experienced clinical tutor gained higher satisfaction scores than those with inexperienced non-clinical tutors, and among the inexperienced tutors, students tutored by a clinical tutor showed higher scores than those with a non-clinical tutor. Different intervention styles were also found depending on tutors' domain and teaching expertise. Experienced tutors gradually reduced the tutoring intervention, whereas the novice provided more as the semester proceeded. Moreover, experts with a clinical medicine degree preferred direct teaching, whereas, non-clinical tutors preferred facilitating. Also, experienced tutors in the clinical medicine facilitated critical awareness than the other tutors. These results show the importance of developing a program for novice tutors to improve PBL in medical education.

• 한국과학교육학회지
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• 제27권9호
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• pp.907-918
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• 2007

본 연구의 목적은 뛰어난 연구 성과를 이룩한 과학 인재들의 성장과 전문성 개발과정에 영향을 미친 주요 요인을 밝히는 것이다. 이러한 연구 목적을 달성하기 위해서,2007년 3월부터 9월까지 과학 분야에서 권위있는 상을 수상한 국내 과학자 31명을 대상으로 심층 면담을 통한 질적 사례연구를 수행하였다. 면담내용은 전관성 발달 단계별로 Csikszentmihalyi의 개인-영역-환경 상호작용(IDF) 모형의 이론적 틀에 맞추어 분석하였다. 우선 탐색기에서는 자기주도적 학습태도,다양한 관심 및 강점의 발견,학구적이며 자유로운 가정환경,의미 있는 만남이,입문기에서는 독립적인 성격특성,전공분야에 대한 지식습득, 대학에서의 학문적 갈증과 지적탐구가 과학인재의 전문성 발달에 중요한 영향을 미치는 것으로 나타났다. 성장기에서는 과제집착력,몰입의 경험,관심분야 및 평생 연구주제의 발견,형식교육에서의 멘토와의 만남이,주도기에서는 우선 순위정하기,의사소통능력,창조적 연구 성과와 사명감,또 다른 재능과의 만남,평가 및 지원 체계가 영향을 미치는 주요 요인으로 나타났다. 결론에서는 면담 내용을 통해 나타나는 주요 요인의 의미를 해석하고,보다많은 과학 인재의 양성을 위해 필요한 교육적 시사점을 논의하였다.

• 지능정보연구
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• 제26권2호
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• pp.79-104
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• 2020

최근 텍스트와 이미지 딥러닝 기술의 괄목할만한 발전에 힘입어, 두 분야의 접점에 해당하는 이미지 캡셔닝에 대한 관심이 급증하고 있다. 이미지 캡셔닝은 주어진 이미지에 대한 캡션을 자동으로 생성하는 기술로, 이미지 이해와 텍스트 생성을 동시에 다룬다. 다양한 활용 가능성 덕분에 인공지능의 핵심 연구 분야 중 하나로 자리매김하고 있으며, 성능을 다양한 측면에서 향상시키고자 하는 시도가 꾸준히 이루어지고 있다. 하지만 이처럼 이미지 캡셔닝의 성능을 고도화하기 위한 최근의 많은 노력에도 불구하고, 이미지를 일반인이 아닌 분야별 전문가의 시각에서 해석하기 위한 연구는 찾아보기 어렵다. 동일한 이미지에 대해서도 이미지를 접한 사람의 전문 분야에 따라 관심을 갖고 주목하는 부분이 상이할 뿐 아니라, 전문성의 수준에 따라 이를 해석하고 표현하는 방식도 다르다. 이에 본 연구에서는 전문가의 전문성을 활용하여 이미지에 대해 해당 분야에 특화된 캡션을 생성하기 위한 방안을 제안한다. 구체적으로 제안 방법론은 방대한 양의 일반 데이터에 대해 사전 학습을 수행한 후, 소량의 전문 데이터에 대한 전이 학습을 통해 해당 분야의 전문성을 이식한다. 또한 본 연구에서는 이 과정에서 발생하게 되는 관찰간 간섭 문제를 해결하기 위해 '특성 독립 전이 학습' 방안을 제안한다. 제안 방법론의 실현 가능성을 파악하기 위해 MSCOCO의 이미지-캡션 데이터 셋을 활용하여 사전 학습을 수행하고, 미술 치료사의 자문을 토대로 생성한 '이미지-전문 캡션' 데이터를 활용하여 전문성을 이식하는 실험을 수행하였다. 실험 결과 일반 데이터에 대한 학습을 통해 생성된 캡션은 전문적 해석과 무관한 내용을 다수 포함하는 것과 달리, 제안 방법론에 따라 생성된 캡션은 이식된 전문성 관점에서의 캡션을 생성함을 확인하였다. 본 연구는 전문 이미지 해석이라는 새로운 연구 목표를 제안하였고, 이를 위해 전이 학습의 새로운 활용 방안과 특정 도메인에 특화된 캡션을 생성하는 방법을 제시하였다.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 1999년도 추계학술대회-지능형 정보기술과 미래조직 Information Technology and Future Organization
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• pp.121-130
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• 1999

The objective of this paper is to apply Extended AND-OR Graph (EAOG)-related techniques to extract knowledge from a specific problem-domain and perform analysis in complicated decision making area. Expert systems use expertise about a specific domain as their primary source of solving problems belonging to that domain. However, such expertise is complicated as well as uncertain, because most knowledge is expressed in causal relationships between concepts or variables. Therefore, if expert systems can be used effectively to provide more intelligent support for decision making in complicated specific problems, it should be equipped with real-time inference mechanism. We develop two kinds of EAOG-driven inference mechanisms(1) EAOG-based forward chaining and (2) EAOG-based backward chaining. and The EAOG method processes the following three characteristics. 1. Real-time inference : The EAOG inference mechanism is suitable for the real-time inference because its computational mechanism is based on matrix computation. 2. Matrix operation : All the subjective knowledge is delineated in a matrix form, so that inference process can proceed based on the matrix operation which is computationally efficient. 3. Bi-directional inference : Traditional inference method of expert systems is based on either forward chaining or backward chaining which is mutually exclusive in terms of logical process and computational efficiency. However, the proposed EAOG inference mechanism is generically bi-directional without loss of both speed and efficiency.

• 한국BIM학회 논문집
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• 제13권3호
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• pp.21-29
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• 2023

ChatGPT, a chatbot based on GPT large language models, has gained immense popularity among the general public as well as domain professionals. To assess its proficiency in specialized fields, ChatGPT was tested on mainstream exams like the bar exam and medical licensing tests. This study evaluated ChatGPT's ability to answer questions related to Building Information Modeling (BIM) by testing it on Korea's BIM expertise exam, focusing primarily on multiple-choice problems. Both GPT-3.5 and GPT-4 were tested by prompting them to provide the correct answers to three years' worth of exams, totaling 150 questions. The results showed that both versions passed the test with average scores of 68 and 85, respectively. GPT-4 performed particularly well in categories related to 'BIM software' and 'Smart Construction technology'. However, it did not fare well in 'BIM applications'. Both versions were more proficient with short-answer choices than with sentence-length answers. Additionally, GPT-4 struggled with questions related to BIM policies and regulations specific to the Korean industry. Such limitations might be addressed by using tools like LangChain, which allow for feeding domain-specific documents to customize ChatGPT's responses. These advancements are anticipated to enhance ChatGPT's utility as a virtual assistant for BIM education and modeling automation.

• 공학교육연구
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• 제19권3호
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• pp.3-12
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• 2016

The purpose of this study was to examine the current states of role model and effects on the expertise development in engineers (i.e., undergraduate students and experts in the field of engineering). Based on the previous studies, role model was categorized into two domain, general role model and value sharing role model. A total of 257 participants (162 undergraduate students, 95 experts) answered survey questions about their role model (the number of their role model, the frequency of meeting with them, and the number of sharing value with them), major confidence, knowledge acquisition, and research performance. The results showed that engineers had 1 or 2 general role models and that the contents of role model were different between the two groups. The value-sharing role model significantly predicted major confidence and research performance in undergraduate students whereas the number of general role model was closely associated with major satisfaction in experts. These results suggest that it is important for engineering major students to have general role model and value-sharing role model in order to enhance expertise development. Establishing infrastructure for having and meeting with role models can facilitate the development of personal expertise in engineers.

• 정보관리학회지
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• 제38권3호
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• pp.1-22
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• 2021

본 논문은 주제분야 전문지식이 적합성 판단에 미치는 영향을 온라인 실험을 통해 살펴보고 주제분야 전문지식이 적합성개념의 기반이 될 수 있는 지를 검증해 보려고 하였다. 문헌정보학 전문가 6명, 문헌정보학 석사과정 학생 9명, 비전문가 12명이 실험에 참여해 문헌정보학 분야에 대한 14개 논문초록과 문헌정보학 영역 이외 14개 논문초록의 적합성을 판정을 실시하였다. 적합성 판단의 일관성은 공동 확률 일치성(Joint-Probability Agreement, PA)과 IBM SPSS의 클래스간 상관관계 계수(Interclass Correlation Coefficient, ICC)를 통해 산출되었다. PA를 사용한 경우, 비전문가는 과제나 그룹 구분에 상관없이 높은 일관성이 보였다. ICC 계산에 따르면, 문헌정보학 전문가들과 비교하였을 때, 문헌정보학 석사과정학생들은 비전문가들보다 높은 수준의 일관성을 가지고 있다는 것으로 나타났다. 2개 그룹(석사 및 박사를 통합으로 하는 전문가그룹과 비전문가)으로 구분하였을 때는 문헌정보학분야 과제에서 예상대로 전문가들이 더 높은 수준의 일관성을 보이는 경향을 볼 수 있었다.

• 대한건축학회논문집:계획계
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• 제36권3호
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• pp.31-38
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• 2020

The purpose of this study is to compare between professionalism in medical field(doctor) and architectural design field(architect) in Korea through synchronic and diachronic analysis, with basic requirement of expertise and systemicity, attitude requirement of the publicness, and structural requirement of exclusiveness and autonomy. The medical professionalism adapted by Korean government in the early period of modernization evolved from Western's professional expertise is highly divided as economy grew and society changed. In comparison, architecture was divided into architecture, urbanism, landscape, and interior architecture. Additionally, architectural field was subdivided with architectural design, engineering, construction, structure, and facilities, but architectural design focused on generalized education and practice system. From the systematical point of view, architectural design field has changed profoundly from architectural engineering as 5 year undergraduate educational system was introduced with Korean architectural accreditation. The publicness is approved through health service in medical field and safety and the public domain in architectural design field, but in reality the professionals are viewed as economic interest groups. Hence, the professionalism in both fields is required to reinforce ideology and ethics, and to practice concrete measures for publicness. Compared with the unified organization of medical field, architectural design professionalism faces various difficulties in unifying the organization, such as internal competition caused by tightened architect's requirements, along with external problems from architectural design permission demands of construction companies. In medical and architectural design professionalism, with the appearance of consumerism and stricter governmental regulations, the autonomy is weakened. From the result of comparative analysis, Korean medical field became extremely subdivided and specialized in each department, therefore integration of each disease and establishment of centers are proposed as solutions. By contrast, the reinforcement of expertise in architectural design professionalism might be necessary to strengthen autonomy caused by governmental restriction, and to form architectural culture and secure public architecture.

• 지식경영연구
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• 제14권5호
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• pp.55-79
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• 2013

This study primarily focused on the opportunity realization process of a korean venture firm based on university. This research examined the relationship between entrepreneurial intent and organizational learning produced in a sustainable opportunity realization process with technology/market domain shifts. Therefore, this research explores the determinants of sustainable growth of a venture firm at the organizational level and suggests optimal solutions for promoting entrepreneurial intent and opportunity realization for many entrepreneurs. The results showed that CEO's entrepreneurial intent is a key driving factor that can positive impacts on opportunity recognition and organizational learning based on university's expertise. Furthermore, the orientation of a entrepreneur can affect venture's technology/market domain shift through the advanced technological knowledge of university. In conclusion, this research sheds light on the growth of a venture firm based on university suggesting more customized solutions for many entrepreneurs. Implications for the results and the future directions are discussed.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -2
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• pp.1165-1168
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• 2002

Knowledge acquisition is the process that extracts the required knowledge from available sources, such as experts, textbooks and databases, for incorporation into a knowledge-based system. Knowledge acquisition is described as the first step in building expert systems and a major bottleneck in the efficient development and application of effective knowledge based expert systems. One cause of the problem is that the process of human reasoning we need to understand for knowledge-based system development is not available for direct observation. Moreover, the expertise of interest is typically not reportable due to the compilation of knowledge which results from extensive practice in a domain of problem solving activity. This is also a problem of modeling knowledge, which has been described as not a problem of accessing and translating what is known, but the familiar scientific and engineering problem of formalizing models for the first time. And this formalization process is especially difficult for knowledge engineers who are often faced with the difficult task of creating a knowledge model of a domain unfamiliar to them. In this paper, we propose an automated knowledge acquisition tool which is based on an implementation of the Inferential Modeling Technique. The Inferential Modeling Technique is derived from the Inferential Model which is a domain-independent categorization of knowledge types and inferences ［Chan 1992］. The model can serve as a template of the types of knowledge in a knowledge model of any domain.