• Journal of Korean Elementary Science Education
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• v.42 no.1
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• pp.109-126
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• 2023

In this study, I took the evidence-explanation (E-E) continuum perspective to examine the epistemological implications of scientific reasoning cases designed by preservice elementary teachers during their simulation teaching. The participants were four preservice teachers who conducted simulation instruction on the seasons and high/low air pressure and wind. The selected discourse episodes, which included cases of inductive, deductive, or abductive reasoning, were analyzed for their epistemological implications-specifically, the role played by the reasoning cases in the E-E continuum. The two preservice teachers conducting seasons classes used hypothetical-deductive reasoning when they identified evidence by comparing student-group data and tested a hypothesis by comparing the evidence with the hypothetical statement. However, they did not adopt explicit reasoning for creating the hypothesis or constructing a model from the evidence. The two preservice teachers conducting air pressure and wind classes applied inductive reasoning to find evidence by summarizing the student-group data and adopted linear logic-structured deductive reasoning to construct the final explanation. In teaching similar topics, the preservice teachers showed similar epistemic processes in their scientific reasoning cases. However, the epistemological implications of the instruction were not similar in terms of the E-E continuum. In addition, except in one case, the teachers were neither good at abductive reasoning for creating a hypothesis or an explanatory model, nor good at using reasoning to construct a model from the evidence. The E-E continuum helps in examining the epistemological implications of scientific reasoning and can be an alternative way of transmitting scientific reasoning.

• Journal of the Korean earth science society
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• v.42 no.1
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• pp.118-131
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• 2021

The purpose of this study was to investigate the characteristics of evidence-based reasoning practiced by middle school gifted students. Data were collected through an online task in which middle school students in gifted education institutes of a university located in the metropolitan area, Korea, performed inquiry about the shape of a planet's orbit. The students were given data of Mercury's greatest elongations and asked to draw the planet's orbit with the data. Each of the students was also asked to provide his or her hypothesis of Mercury's orbit before the drawing and to reason about the orbit again using his or her own drawing as evidence. The content analysis of the students' reports revealed 5 different types of judgement about the shape of Mercury's orbit, 4 types of reasoning about the hypothesis and evidence, and the characteristics of evidence-based reasoning within the judgement types. Based upon the analysis results, the importance of proper interpretations of evidence in evidence-based reasoning, the core role of the theory-evidence coordination, and the usefulness of working with multiple hypotheses were discussed. In addition, implications for earth science education were suggested.

• Journal of Korea Fair Competition Federation
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• no.113
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• pp.15-31
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• 2005

최근 미국의 법원은 담합을 입증하려는 시도를 주로 경제적 증거에 입각하여 분석하는 추세를 보여 왔다. 하지만 담합의 존재를 입증하는데 있어서 경제분석의 역할에도 많은 이견이 날카롭게 표출되었다. 담합의 존재에 관한 경제적 증거를 분석하는 데에 있어 유일한 합리적 근거는 최신과점이론(Modern oligopoly theory)이다. 그런데 증인으로 나선 많은 경제학자들과 법원이 최신과점이론에 자신들의 분석을 뚜렷이 기초하지 않았기 때문에, 판례법의 현 상태가 불만족스럽다고 주장하는 것이 본 논문의 핵심적 내용이다. 셔먼법 제1조는 ''계약, 결합, 공모(contract, combination, or conspiracy)에 의해 초래되는 거래(즉 경쟁)의 불합리한 제한을 규제''하는데, 이러한 계약 결합, 공모의''용어들은 합의라는 하나의 개념으로 통합하여 이해''할 수 있다. 제 1조는 다수의 당사자가 ''단일한 목적, 공통된 의도와 의견의 일치, 혹은 의사의 합치(Meeting of minds)'', 즉 ''공통된 계획에 대한 의식적 참가(consious commitment to a common scheme)''를 합의한 모든 협약을 규제한다. 셔먼법 제 1조 위반을 입증하기 위해서는 일치된 행동이 합의 하에서 일어났음을 입증해야 한다. 미국 법원은 합의를 추론할 수 있는 증거력 있는 정황증거(admissible circumstantial evidence)의 원칙을 확립하였다. 독점가격에 가까운 수준의 과점가격 설정은 ''조정되었다(coordinated)''라고 칭해지는데, 이는 ''구두 합의''와 ''암묵적 합의''의 두 가지 형태로 나뉜다. 한편, 일회게임 과점 모형과 반복게임 모형은 과점이론의 핵심을 이룬다. 과점에 대한 Chamberlin의 견해는 본래 게임과 Stigler의 모형은 그와 같은 생각의 오류를 가르쳤다. 그러나 판례법은, Petroleum products antitrust litigation사건과 reserve supply사건에서 볼 수 있듯이 종종 그러한 교훈을 망각했다. 최신과정이론과 판례를 종합해 보면, 합의의 존재에 관해 경제학자가 이끌어내는 추론과 법원이 이끌어내는 추론을 포괄하는 다음의 네 가지 일반적 원칙이 도출된다. 1. 합의가 추론되기 위해서는 상호의존성을 넘는 무언가가 먼저 제시되어야 한다. 2. 합의의 존재는 일회게임 과점 모형에서의 비협조적 내쉬균형과 일치하는 행동으로부터는 추론될 수 없다. 3. 합의의 존재는, 비록 무한반복 과점게임에서의 비협조적 내쉬균형(혹은 Chamberlin-Fellner식의 과점)과 일치하더라도, 일회게임 과점 모형에서의 비협조적 내쉬균형과 일치하지 않는 행동으로부터 추론될 수 있다. 4. 증거는 구두합의의 존재를 뒷받침해야만 한다. 이러한 원칙에서 얻을 수 있는 가장 중요한 교훈은, 합의가 존재하지 않을 경우 과점상황으로부터는 독점가격이 예상될 수 없다는 사실을 법원이 인식하는 것만으로도 합의의 추론에서 범하기 쉬운 가장 큰 오류를 회피할 수 있다는 것이다.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.634-636
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• 2005

지능형 로봇 기술이 발전하면서 영상에서 장면을 이해하는 연구가 많은 관심을 받고 있으며, 최근에는 불확실한 환경에서도 좋은 성능을 발휘할 수 있는 확률적 접근 방법이 많이 연구되고 있다. 본 논문에서는 확률적 모델링이 가능한 베이지안 네트워크(BN)를 이용해서 장면 인식 추론 모듈을 설계하고, 실제 환경에서 얻어진 증거 및 베이지안 추론 결과를 결합하여 분류 성능을 향상시키기 위한 방법을 제안한다. 영상 정보는 시간에 대해 연속성을 가지고 있기 때문에, 증거 정보와 베이지안 추론 결과들을 적절히 결합하면 더 좋은 결과를 예상할 수 있으며, 본 논문에서는 확신 요소(Certainty Factor: CF) 분석에 의한 결합 방법을 사용하였다. 성능 평가 실험을 위해서 SET (Scale Invariant Feature Transform) 기법을 이용하여 물체 인식 처리를 수행하고, 여기서 얻어진 데이터를 베이지안 추론의 증거로 사용하였으며, 전문가의 CF 값 정의에 의한 베이지안 네트워크 설계 방법을 이용하였다.

• Journal of Science Education
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• v.41 no.3
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• pp.426-446
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• 2017

The purpose of this study was to analyze undergraduate students' reasoning for solving a problem about a rock and investigate the roles and importance of critical evidence (CE) and critical resource models (CRMs) in abductive reasoning. Participants were 20 senior undergraduate students enrolled in a science major course in a university of education. They were asked to abductively infer geologic processes of sedimentary rocks having a lot of holes and represent them with models. Their reasoning were analyzed according to a scheme for modeling-based abductive reasoning. As a result, successful student reasoning was characterized by using a diversity of grains and lots of holes as CE, activating the sedimentary rock formation and weathering as CRMs, and combining the CRMs into a scientifically sound explanatory model (SSEM). By contrast, in the reasoning unsuccessful in proposing a SSEM, students activated the igneous rock (basalt) formation and deposition as resource models (RMs) based on the evidence of the holes in the rocks and diverse grains, respectively, and used the RMs to construct their own explanatory models (EMs). It was suggested that to construct SSEMs to solve earth scientific problems about rocks, students need to know what could be CE in a particular problem situation, take an integrative or systemic approach to a rock problem, use multiple RMs, and evaluate RMs or EMs in light of evidence.

• Journal of KIISE:Software and Applications
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• v.37 no.10
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• pp.736-744
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• 2010

Log data collected from mobile devices contain diverse and meaningful personal information. However, it is not easy to implement a context-aware mobile agent using this personal information due to the inherent limitation in mobile platform such as memory capacity, computation power and its difficulty of analysis of the data. We propose a method of selective inference for modular Bayesian Network for context-aware mobile agent with effectiveness and reliability. Each BN module performs inference only when it can change the result by comparing to the history module which contains evidences and posterior probability, and gets results effectively using a method of influence score of the modules. We adopt memory decay theory and virtual linking method for the evaluation of the reliability and conservation of casual relationship between BN modules, respectively. Finally, we confirm the usefulness of the proposed method by several experiments on mobile phones.

• The Korean Journal of Applied Statistics
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• v.23 no.1
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• pp.113-121
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• 2010

Mixture is that DNA profiles of samples contain material from more than one contributor, especially common in rape cases. In this situation, first, the method based on enumerating a complete set of possible genotype that may have generated the mixed DNA profile have been studied for interpreting DNA mixtures. More recently, the methods utilizing peak area information to calculate likelihood ratios have been suggested. This study is concerned with the analysis and interpretation of mixed forensic stains using quantitative peak area information and the method of forensic inference for extension of material from more than or equal to three contributors. Finally, the numerical example will be outlined.

• Journal of KIISE:Software and Applications
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• v.34 no.6
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• pp.549-561
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• 2007

Vision-based scene understanding is to infer and interpret the context of a scene based on the evidences by analyzing the images. A probabilistic approach using Bayesian networks is actively researched, which is favorable for modeling and inferencing cause-and-effects. However, it is difficult to gather meaningful evidences sufficiently and design the model by human because the real situations are dynamic and uncertain. In this paper, we propose a learning method of Bayesian network that reduces the computational complexity and enhances the accuracy by searching an efficient BN structure in spite of insufficient evidences and training data. This method represents the domain knowledge as ontology and builds an efficient hierarchical BN structure under constraint rules that come from the ontology. To evaluate the proposed method, we have collected 90 images in nine types of circumstances. The result of experiments indicates that the proposed method shows good performance in the uncertain environment in spite of few evidences and it takes less time to learn.

• Journal of The Korean Association For Science Education
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• v.37 no.4
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• pp.553-564
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• 2017

This study investigated the change of pre-service elementary teachers' professional visions through video-based reflection on science teaching with focus on their attention and pedagogical reasoning about student learning. Specifically, we compared two reflection cycles before and after pre-service elementary teachers went through the collaborative video-based reflection process in a professional learning community. The primary data were collected from eight pre-service elementary teachers and included their science lesson plans, videotaped lessons, video-reflection papers, and transcripts from the interviews. Pre-service elementary teachers' attention was categorized in five aspects: classroom management & control, teacher's instruction, students' thinking & learning, subject knowledge, and assessment. The level of their pedagogical reasoning about student thinking and learning was determined with six levels based on the number of evidence, evidence area, and evidence type. The findings revealed that 1) individual reflection is not enough - collaborative reflection is essential to change their attention toward students learning and thinking 2) pedagogical reasoning levels increase gradually throughout the individual and collaborative video-based reflection processes. The participants not only attributed student learning solely to the characteristics of students but also connected it with their own instruction or science content knowledge and used different types of evidences as they went through two reflection cycles. Implications for using video in the teacher education program were discussed.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.4
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• pp.581-587
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• 2011

A wireless sensor network needs to consist of multi-sensors in order to infer a high level of information on circumstances. Data fusion, in turn, is required to utilize the data collected from multi-sensors for the inference of information on circumstances. The current paper, based on Dempster-Shafter's evidence theory, proposes data fusion in a wireless sensor network with different weights assigned to different sensors. The frequency of events per sensor is the crucial element in calculating different weights of the data of circumstances that each sensor collects. Data fusion utilizing these different weights turns out to show remarkable difference in reliability, which makes it much easier to infer information on circumstances.