• 한국초등과학교육학회지:초등과학교육
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• 제38권3호
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• pp.375-386
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• 2019

This study explores how elementary school students construct food pyramid prediction models using scientific reasoning. Thirty small groups of sixth-grade students in the Kyoungki province (n=138) participated in this study; each small group constructed a food pyramid prediction model based on scientific reasoning, utilizing prior knowledge on topics such as biotic and abiotic factors, food chains, food webs, and food pyramid concepts. To understand the scientific reasoning applied by the students during the modeling process, three forms of qualitative data were collected and analyzed: each small group's discourse, their representation, and the researcher's field notes. Based on this data, the researcher categorized the students' model patterns into three categories and identified how the students used scientific reasoning in their model patterns. The study found that the model patterns consisted of the population number variation model, the biological and abiotic factors change model, and the equilibrium model. In the population number variation model, students used phenomenon-based reasoning and relation-based reasoning to predict variations in the number of producers and consumers. In the biotic and abiotic factors change model, students used relation-based reasoning to predict the effects on producers and consumers as well as on decomposers and abiotic factors. In the equilibrium model, students predicted that "the food pyramid would reach equilibrium," using relation-based reasoning and model-based reasoning. This study demonstrates that elementary school students can systematically elaborate on complicated ecology concepts using scientific reasoning and modeling processes.

• 한국초등과학교육학회지:초등과학교육
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• 제31권1호
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• pp.71-83
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• 2012

The purpose of this study was to explore ecological concepts, epistemological reasoning and reasoning processes through constructing 'food web and food pyramid' in ecology. We conducted classes which involved a 'food web and food pyramid' for $6^{th}$ grade students. Each class is constructed of small groups to do modeling and epistemological reasoning through communication. The researcher had videotaped and recorded each class and have made transcription about classes. We analysed patterns of 'food web and food pyramid models' and reasoning processes according to scientific epistemology using transcription data and student outputs. As a result, students represented phenomenon-based reasoning, relation-based reasoning and model-based reasoning in scientific epistemology from their modeling. Students usually did relation-based reasoning and model-based reasoning in food web which explains ecological phenonenon, while they usually did model-based reasoning in food pyramid which expects ecological phenomenon. Student's reasoning can be limited when they have misconception of scientific knowledge and are limited by fragmentary knowledge. This represents that students has to do relation-based reasoning and model-based reasoning is beneficial in their ecological model. It also suggests that students need to define correct-conception related to ecological modeling(food web, food pyramid).

• 한국지능시스템학회논문지
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• 제21권2호
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• pp.165-170
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• 2011

규칙베이스 추론과 사례베이스 추론의 협조에 의해 보다 유연한 추론을 위한 효율적인 방법의 실현이 기대된다. 본 논문에서는 MVL 오토마타 모델을 적용하여 규칙베이스와 사례 베이스의 통합 추론모델과 이에 따른 불확실성 처리 방법을 제안한다.

• Journal of Information Technology Applications and Management
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• 제12권4호
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• pp.1-12
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• 2005

In general, other conventional researches propose the fuzzy Petri net-based fuzzy reasoning algorithms based on the exhaustive search algorithms. If it can allow the certainty factors representing in the fuzzy production rules to use as the heuristic information, then it can allow the reasoning of rule-based systems to perform fuzzy reasoning in more effective manner. This paper presents a fuzzy Petri net(FPN) model to represent the fuzzy production rules of a rule-based system. Based on the fuzzy Petri net model, a weighted fuzzy reasoning algorithm is proposed to Perform the fuzzy reasoning automatically, This algorithm is more effective and more intelligent reasoning than other reasoning methods because it can perform fuzzy reasoning using the certainty factors which are provided by domain experts as heuristic information

• 한국과학교육학회지
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• 제28권8호
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• pp.796-813
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• 2008

과학 개념에 대한 높은 이해와 과학 분야에 무한한 가능성과 잠재력을 가지고 있는 과학영재들이 물리 개념 이해 과정 중에 나타내는 사고 모형을 분석하기 위해서 역학 개념 검사인 FCI, MBT와 전자기학 개념검사인 CSEM을 사용하였다. 세 가지의 설문지 필답검사를 실시한 후에는 그룹 토의의 교실 상황 관찰과 개인 면담을 실시하고 그 결과를 종합 분석하였다. 분석 결과에 따르면 과학영재의 물리 개념 이해 과정에서 나타나는 사고 모형은 물리 개념에 대한 정확한 이해와 적용으로 개념의 형성이 안정성과 일관성을 보이는 일관성 사고 모형을 가진 학생과 문제에 적용할 때마다 유동성과 상황 의존성을 보이는 다양성 사고 모형을 가진 학생으로 분류되었고 또한 과학영재이지만 뉴턴의 운동 법칙에 대하여 힘과 운동의 관계를 잘못 이해한 아리스토텔레스 정신모형을 가진 학생과 옳은 과학 개념인 뉴턴 모형을 가진 학생 그리고 문제 상황에 따라 달라지는 두 정신모형이 혼합된 학생으로 분류되어 개인차가 있음을 알 수 있었다.

• 한국과학교육학회지
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• 제38권5호
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• pp.599-610
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• 2018

이 연구의 목적은 파브르의 탐구 과정에서 나타난 메커니즘 추론을 분석하고, 분석 결과에 기반하여 메커니즘 추론 모델을 개발하는 것이다. 이를 위해 Russ et al.(2008)의 분석틀을 수정 보완한 메커니즘 추론 분석틀로 "파브르 곤충기 1~10" 가운데 추론요소가 등장하는 30개의 챕터를 분석하였다. 분석결과 첫째, 파브르의 탐구 과정에서 나타난 메커니즘 추론의 하위 과정 요소는 선지식확인, 대상속성확인, 시작조건확인, 활동확인 등의 과정이 반복적으로 일어났다. 뿐만 아니라 이 메커니즘 추론의 과정 요소들의 순서는 탐구 주제, 의문 유형, 선지식이나 주어진 상황 등에 따라 다르게 나타났으며, 비선형적이고 반복적인 형태로 나타났다. 둘째, 메커니즘 추론의 과정 요소가 나타난 순서에 기반하여 메커니즘 추론 모델을 개발하였다. 파브르의 탐구 과정 분석을 통해 제안되는 메커니즘 추론 모델은 실체확인형 메커니즘 추론 모델(MIE), 활동확인형 메커니즘 추론 모델(MIA), 실체 속성확인형 메커니즘 추론 모델(MIP) 3가지였다. 이러한 결과는 인과 메커니즘을 밝히고자 하는 탐구를 수행하는 학생들에게 교사가 Why 뿐만 아니라 How, If, What과 같은 다양한 발문을 통해 탐구를 진행하도록 유도할 수 있음을 시사해준다. 또한 교사는 자연 현상의 기저에 존재하는 여러 실체들을 인식하는 메커니즘적 이해가 요구되며 학생들에게 다양한 가설을 생성하도록 하는 기회를 제공해야함을 시사해 준다.

• 한국수학교육학회지시리즈D:수학교육연구
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• 제25권2호
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• pp.135-158
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• 2022

This study aimed to building models to understand the relationships between reasoning resources and content knowledge. We applied Support Vector Machine and linear models to the data including fifth graders' scores in the Cornel Critical Thinking Test and the Iowa Assessments, demographic information, and learning science approach (a student-centered approach to learning called the Science Writing Heuristic [SWH] or traditional). The SWH model showing the relationships between critical thinking domains and academic achievement at grade 5 was developed, and its validity was tested across different learning environments. We also evaluated the stability of the model by applying the SWH models to the data of the grade levels. The findings can help mathematics educators understand how critical thinking and achievement relate to each other. Furthermore, the findings suggested that reasoning in mathematics classrooms can promote performance on standardized tests.

• 전자통신동향분석
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• 제38권6호
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• pp.1-11
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• 2023

Large language models seem promising for handling reasoning problems, but their underlying solving mechanisms remain unclear. Large language models will establish a new paradigm in artificial intelligence and the society as a whole. However, a major challenge of large language models is the massive resources required for training and operation. To address this issue, researchers are actively exploring compact large language models that retain the capabilities of large language models while notably reducing the model size. These research efforts are mainly focused on improving pretraining, instruction tuning, and alignment. On the other hand, chain-of-thought prompting is a technique aimed at enhancing the reasoning ability of large language models. It provides an answer through a series of intermediate reasoning steps when given a problem. By guiding the model through a multistep problem-solving process, chain-of-thought prompting may improve the model reasoning skills. Mathematical reasoning, which is a fundamental aspect of human intelligence, has played a crucial role in advancing large language models toward human-level performance. As a result, mathematical reasoning is being widely explored in the context of large language models. This type of research extends to various domains such as geometry problem solving, tabular mathematical reasoning, visual question answering, and other areas.

• 한국안전학회지
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• 제14권1호
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• pp.167-176
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• 1999

Construction accidents occur reiteratively in similar fashions. There have been several attempts to develop a safety program for preventing construction accidents on sites. It will be very effective to use previous accident cases for establishing proper safety plan and managing safety process. This research develops a case-based construction safety management system which enables construction managers or safety managers to prevent potential accidents during the construction process. The case-oriented approach is performed through the representation of previous accident cases in accordant with the similarity to the conditions of current site. It uses a case-based reasoning which is one of the reasoning methods of an expert system. A prototype system for the reasoning model was implemented using one of the case based system development tools. The system was applied to a real construction site to verify its capability and validity. It was founded that the causes of accidents were successfully removed, so the proposed model proved to be reasonable. Additional research is needed to resolve the technical problem how to adapt the countermeasures for accident prevention provided by the reasoning model.

• 디지털산업정보학회논문지
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• 제7권3호
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• pp.25-35
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• 2011

In the Semantic Web, storage models are required to efficiently store and retrieve metadata and ontology represented using OWL that can provide expressive power and reasoning support. In this paper, we propose an OWL storage model that can store and retrieve many restrictions and semantic relations defined on ontology with metadata. In addition, we propose some methods and rules to improve query processing efficiency of the proposed storage model. The proposed storage model can store and process large amounts of ontology and metadata because it consists of tables based on the relational database. And the proposed model can quickly provide more accurate results to users because of performing two different types of ontology reasoning and using the prime number labeling scheme to easily identify hierarchy relationships between classes or properties. The comparative evaluation results show that our storage model provides better performance than the existing storage model.