• 인지과학
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• 제28권1호
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• pp.43-64
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• 2017

본 연구의 목적은 과제와 무관련한 정서 자극에 의한 점화가 고차인지과정에 미치는 영향을 알아보는 것이다. 보다 구체적으로 본 연구에서는 과제와 직접적으로 관련이 없는 정서 점화 자극이 삼단논법추론 과제의 수행에 영향을 미치는지를 살펴보았다. 이를 위해 실험 1에서는 점화 자극인 IAPS 사진의 정서차원을 통제하고 각성차원을 조작하였으며 실험 2에서는 IAPS 사진의 각성차원을 통제하고 정서차원을 조작하였다. 두 실험 모두에서 과제와 무관련한 정서 점화 자극이 제시된 뒤에 세 개의 문장으로 이루어진 삼단논법추론 과제가 제시되었으며 참가자들의 추론 정확률이 측정되었다. 점화 자극의 정서차원은 결론 문장의 타당성과 신념에 따른 신념편향(belief-bias)에 영향을 미쳤으나 점화 자극의 각성차원은 추론에 영향을 미치지 않았다. 특히 긍정정서는 신념 편향을 감소시켜 논리적, 분석적 처리를 향상 시켰으나 각성차원은 추론 과제 수행에 영향을 미치지 않았다. 이와 같은 결과는 정서차원과 각성차원이 고차인지능력에 독립적으로 영향을 미친다는 것을 보여준다.

• 한국컴퓨터정보학회논문지
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• 제27권7호
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• pp.35-48
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• 2022

본 연구에서는 멀티에이전트 환경에서 지식을 표현하고 추론함에 있어서 증명 이론적 방법을 제안한다. 이 방법은 논리적 결과를 기계적 방법으로 결정하므로 초기 인공지능 연구부터 핵심분야로 발전해 왔다. 하지만 임의의 닫힌 문장들의 집합에서 항상 명제가 증명할 수 있지 않기에 논리적 결과가 결정할 수 있어지려면 절 형식의 문장으로 그 표현 범위를 제한한다. 그리고 절 형식의 문장들에서만 적용 가능한, 단순하면서도 강력한 추론 규칙인 비교흡수 원리(Resolution principle)를 적용한다. 또한 증명이론을 메타술어로 표현할 수 있으므로 증명이론의 메타논리로 확장 가능하다. 메타논리가 모델 이론의 인식 논리(epistemic logic)보다 향상된 표현력을 기반으로 실용적인 면과 효율면에서 우월할 수 있다. 이를 입증하기 위해 인식 논리의 의미론과 증명이론의 메타논리 방식으로 각각 Muddy Children 문제에 적용한다. 그 결과 협력적 멀티에이전트 환경에서 메타논리를 사용하여 지식과 공통지식을 표현하고 추론한 방법이 더 효율적임을 증명한다.

• 한국지능시스템학회논문지
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• 제13권3호
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• pp.366-370
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• 2003

In this research, we suggest a hybrid intelligent Web recommendation systems based on Web data mining and case-based reasoning (CBR). One of the important research topics in the field of Internet business is blending artificial intelligence (AI) techniques with knowledge discovering in database (KDD) or data mining (DM). Data mining is used as an efficient mechanism in reasoning for association knowledge between goods and customers＇ preference. In the field of data mining, the features, called attributes, are often selected primary for mining the association knowledge between related products. Therefore, most of researches, in the arena of Web data mining, used association rules extraction mechanism. However, association rules extraction mechanism has a potential limitation in flexibility of reasoning. If there are some goods, which were not retrieved by association rules-based reasoning, we can＇t present more information to customer. To overcome this limitation case, we combined CBR with Web data mining. CBR is one of the AI techniques and used in problems for which it is difficult to solve with logical (association) rules. A Web-log data gathered in real-world Web shopping mall was given to illustrate the quality of the proposed hybrid recommendation mechanism. This Web shopping mall deals with remote-controlled plastic models such as remote-controlled car, yacht, airplane, and helicopter. The experimental results showed that our hybrid recommendation mechanism could reflect both association knowledge and implicit human knowledge extracted from cases in Web databases.

• 한국수학교육학회지시리즈A:수학교육
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• 제51권2호
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• pp.161-171
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• 2012

Generally mathematics is regarded as a subtle subject to grasp their true meaning. And teacher's personal conceptions of mathematics influence greatly on the teaching and learning of mathematics. More over often teachers confess their difficulties in explaining the true nature of mathematics. In this paper, applying the theory of epistemology, we tried to search factors that must be counted important when trying to understand the true nature of mathematics. As results, we identified five characteristics of mathematical knowledge such as logical reasoning, abstractive concept, mathematical representation, systematical structure, and axiomatic validation. Next, we tried to investigate math education major students' conception of mathematics using these items. To proceed this research we asked 51 students from three Universities to answer their opinion on 'What do you think is mathematics?'. Analysing their answers in the light of the above five items, we got the following facts. 1. Only 38% of the students regarded mathematics as one of the five items, which can be considered to reveal students' low concern about the basic nature of mathematics. 2. The status of students' responses to the question were greatly different among the three Universities. This shows that mathematics professors need to lead students to have concern about the true nature of mathematics.

• 대한수학교육학회지:수학교육학연구
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• 제9권1호
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• pp.245-261
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• 1999

Proof is an essential characteristic of mathematics and as such should be a key component in mathematics education. But, teaching proof in school mathematics have been unsuccessful for many students. The traditional approach to proofs stresses formal logic and rigorous proof. Thus, most students have difficulties of the concept of proof and students' experiences with proof do not seem meaningful to them. However, different views of proof were asserted in the reassessment of the foundations of mathematics and the nature of mathematical truth. These different views of justification need to be reflected in demonstrative geometry classes. The purpose of this study is to characterize the types of students' justification in demonstrative geometry classes taught using dynamic software. The types of justification can be organized into three categories : empirical justification, deductive justification, and authoritarian justification. Empirical justification are based on evidence from examples, whereas deductive justification are based logical reasoning. If we assume that a strong understanding of demonstrative geometry is shown when empirical justification and deductive justification coexist and benefit from each other, then students' justification should not only some empirical basis but also use chains of deductive reasoning. Thus, interaction between empirical and deductive justification is important. Dynamic geometry software can be used to design the approach to justification that can be successful in moving students toward meaningful justification of ideas. Interactive geometry software can connect visual and empirical justification to higher levels of geometric justification with logical arguments in formal proof.

• 대한수학교육학회지:수학교육학연구
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• 제17권2호
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• pp.179-199
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• 2007

본 연구는 초등학교 5학년 수학영재와 일반아의 확률판단 능력과 근거를 비교하는 것을 목표로 하였다. 적절한 비교 준거를 개발하기 위해 선행연구에서 제시하는 확률판단 검사문항을 수정하고 보완하였다. 개발된 검사문항을 이용하여 확률교육을 받지 않은 수학영재 170명, 일반아 228명을 대상으로 검사를 실시한 후, 확률판단의 차이와 확률판단에 영향을 미치는 요인에 대하여 분석하였다. 분석 결과 수학영재가 일반아에 비해 정답률이 높았으나 일부 문항에 대해서는 일반아의 정답률이 더 높게 나타났다. 정답에 대한 확신의 정도는 대체로 수학영재가 더 높았다. 확률 판단에 영향을 미치는 요인으로 수학영재는 논리적 추론과 수학적 지식의 활용을 들 수 있으며, 일반아는 직관적 판단 등이 활용되는 것으로 나타났다.

• 한국과학교육학회지
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• 제37권1호
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• pp.39-48
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• 2017

이 연구에서는 고등학교 학생들이 이온 결합에 대해 생성한 비유의 특징을 비유 생성 개수와 대응 관계 이해도, 비유의 소재와 유형의 측면에서 분석하고, 이 결과를 학생들의 개념 이해도와 논리적 사고력, 비유 추론 능력에 따라 비교하였다. 서울특별시에 소재한 5개 고등학교에 재학 중인 2학년 학생 395명이 연구에 참여하였다. 연구 결과, 개념 이해도, 논리적 사고력, 비유 추론 능력이 높을수록 학생들은 비유를 더 많이 생성하는 것으로 나타났다. 생성한 비유에 대한 대응 관계 이해도는 논리적 사고력과 비유 추론 능력만 관계가 있었다. 학생들이 비유를 생성하기 위해 활용하는 소재는 조사한 인지적 특성 중 목표 개념에 대한 이해도에 따라서만 다르게 나타났다. 또한, 개념 이해도가 높을수록 다양한 소재를 활용하여 비유를 생성하였다. 학생들이 생성한 비유의 유형은 일부 인지적 특성과 관련이 있었다. 예를 들어, 개념 이해도와 논리적 사고력이 높은 학생들이 글과 그림을 모두 사용한 비유를 더 많이 생성하였다. 작위성과 추상도, 체계성의 측면에서 비유의 유형은 인지적 특성과 관련이 없었다. 이상의 결과를 바탕으로 교육적 함의를 논의하였다.

• 한국경영과학회지
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• 제28권3호
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• pp.135-148
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• 2003

In this paper we introduce the Internet-based purchase support systems using data mining and case-based reasoning (CBR). Internet Business activity that involves the end user is undergoing a significant revolution. The ability to track users browsing behavior has brought the vendor and end customer's closer than ever before. It is now possible for a vendor to personalize his product message for individual customers at massive scale. Most of former researchers, in this research arena, used data mining techniques to pursue the customer's future behavior and to improve the frequency of repurchase. The area of data mining can be defined as efficiently discovering association rules from large collections of data. However, the basic association rule-based data mining technique was not flexible. If there were no inference rules to track the customer's future behavior, association rule-based data mining systems may not present more information. To resolve this problem, we combined association rule-based data mining with CBR mechanism. CBR is used in reasoning for customer's preference searching and training through the cases. Data mining and CBR-based hybrid purchase support mechanism can reflect both association rule-based logical inference and case-based information reuse. A Web-log data gathered in the real-world Internet shopping mall is given to illustrate the quality of the proposed systems.

• 한국과학교육학회지
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• 제16권1호
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• pp.87-96
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• 1996

In this study, students' performances on the reasoning tasks dealing with physical situations were analyzed. Through these analysis, the influences of students' preconceptions and logical abilities in reasoning process were described. For this study, 97 high school students were randomly selected. Among them, the number of the students who changed their misconceptions is 62% for the first task(force acting on the upward moving body), and 25% for the second task(force acting on the body when it is on the top of its motion). The students who show the premise-based response changed their conceptions in both of the tasks are more than those who responded in the idea based responses. The index of the influence of prior knowledge, ${\alpha}$ is 33% for the first task, and 67% for the second task, and ${\beta}$ is 41% for the first task, and 17% for the second task. When students performed the reasoning tasks about force and motion, the misconcepts frequently influenced their performances. But for the first task, the precentage of students who changed their concepts is about 62%. It shows the possibility that if the task is simple and appropriate, students can change their concepts.

• 한국과학교육학회지
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• 제17권1호
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• pp.11-19
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• 1997

Students' protocols obtained from think-aloud interviews were analyzed in the aspects of the success at first two problem-solving stages (understanding and planning), the time to complete a problem, the time at each problem-solving stage, the number of transition, and the transition rate. These were compared in the aspects of the context of problem, the success in solving problem, students' logical reasoning ability, spatial ability, and learning approach. The results were as follows:1. Students tended to spend more time in everyday contexts than in scientific contexts, especially at the stages of understanding and reviewing. The transition rate during solving a problem in everyday contexts was greater than that in scientific contexts. 2. Unsuccessful students spent more time at the stage of understanding, but successful students spent more time at the stage of planning. 3. Students' logical reasoning ability, as measured with the Group Assessment of Logical Thinking, was significantly correlated with the success in solving problem. Concrete-operational students spent more time in completing a problem, especially understanding the problem. 4. Students' spatial ability, as measured with the Purdue Visualization of Rotations Test and the Find A Shape Puzzle, was significantly correlated with their abilities to understand a problem and to plan for its solution. 5. Students' learning approach, as measured with the Questionnaire on Approaches to Learning and Studying, was not significantly correlated with the success in solving problem. However, the students in deep approach had more transitions and greater transition rates than the students in surface approach.