• Journal of Korean Elementary Science Education
• /
• v.30 no.3
• /
• pp.379-393
• /
• 2011

The purpose of this study was to analyze the complexity of scientific reasoning during open inquiry activities of pre-service elementary school teachers. In this study, 6 pre-service elementary teachers who participated in open-inquiry activities were selected. The data of scientific reasoning during their inquiry process was collected from the video recording of reporting about inquiry process and results, their reports and researcher's notetaking. CSRI Matrix (Dolan & Grady, 2010) was used to analyze the complexity of participants' scientific reasoning. The result showed that the degree of the complexity of their scientific reasoning varied in participants. Particularly the low degree of the complexity of scientific reasoning presented in posing preliminary hypotheses, providing suggestions for future research, communicating and defending finding. Also, The more pre-service teachers' epistemology of inquiry are similar to that of scientists, the more complex scientific reasoning represents. This results suggest that teachers should impress on students the importance of doing the precedent study and providing suggestions for future research, and provide a place for communicating and defending findings.

• Journal of English Language & Literature
• /
• v.57 no.6
• /
• pp.911-938
• /
• 2011

The present study examined the effect of two variables of task complexity, reasoning demand and time pressure, each from the resourcedirecting and resource-dispersing dimension in Robinson's (2001) framework of task classification. Reasoning demand was operationalized as the two types of texts to read and summarize, expository and argumentative. Time pressure was operationalized as the two modes of performance, oral and written. Six university students summarized the two types of text orally and twenty four students from the same school summarized them in the written form. Results from t test and ANCOVA showed that in the oral mode, reasoning demand tends to heighten the complexity of the language used in the summary in competition with accuracy but such an effect disappeared in the written mode. It was interpreted that the degree of time pressure is not the only difference between the oral and written modes but that the two modes may be fundamentally different cognitive tasks, and that Robinson's (2001) and Skehan's (1998) models were differentially supported by the oral mode of tasks but not by the written mode of the tasks.

• Journal of Science Education
• /
• v.37 no.2
• /
• pp.323-337
• /
• 2013

The purpose of this study was to analyze the scientific reasoning ability during open-inquiry activities of science-gifted 2nd middle school students. Open-inquiry activity is similar to process of scientists' science knowledge generation. Identifying and analyzing the scientific reasoning process and the scientific reasoning ability during open-inquiry activities of science-gifted students, will be able to provide implications for future research. CSRI Matrix(Dolan & Grady, 2010) was used to analyze the complexity of the scientific reasoning ability. The higher degree of complexity of the scientific reasoning is similar to process of scientists' science knowledge generation. The results showed that each process of the open-inquiry activities were distributed by various steps of complexity of the scientific reasoning. Particularly, 'The generating questions' and 'Connecting data to the research question' were 'most complex' step in all teams. On the other side, 'Posing preliminary hypotheses', 'Selecting dependent and independent variables', 'Considering the limitations or flaws of their experiments' were low steps in most teams. And 'Communicating and defending findings' was distributed by most various steps of complexity of the scientific reasoning.

• IEIE Transactions on Smart Processing and Computing
• /
• v.3 no.5
• /
• pp.338-344
• /
• 2014

As the role of information collection becomes increasingly important in the enormous data environment, there is growing demand for more intelligent information technologies for managing complex data. On the other hand, it is difficult to find a solution because of the data complexity and big scaled amount. Accordingly, there is a need for a special intelligent knowledge base frame that can be operated by itself flexibly. In this paper, by adopting switching function for signal transmission in the synapse of the human brain, I/E selective activation based knowledge reconfiguring mechanism is proposed for building more intelligent information management system. In particular, knowledge network design, a special knowledge node structure, Type definition, I/E gauge definition and I/E matching scheme are provided. Using these concepts, the proposed system makes the functions of activation by I/E Gauge, selection and reconfiguration. In a more efficient manner, the routing and reasoning process was performed based on the knowledge reconfiguration network. In the experiments, the process of selection by I/E matching, knowledge reconfiguration and routing & reasoning results are described.

• Journal of the Korean earth science society
• /
• v.31 no.2
• /
• pp.185-204
• /
• 2010

Inquiring earth science phenomena is characterized by the followings: a big scale of time and space, inaccessibility, uncontrollability, and complexity. Thus, it is very difficult or, in some cases, impossible to investigate them through the actual manipulation in laboratories. Therefore, it is necessary to provide chance for students to experience scientific inquiry without actual manipulation in earth science classes. This study is to explore the role of reasoning based on a thought experiment as a representative model without actual manipulation, and to investigate features of various inquiry models using reasoning in classes. We can make implications when applying for applying each inquiry model to earth science classes, proposing a reasoning-based inquiry model embedded in earth scientific phenomena.

• The KIPS Transactions:PartB
• /
• v.17B no.2
• /
• pp.163-168
• /
• 2010

A linguistic case-based fuzzy reasoning (LCBFR) based on standardized parametric membership functions (SPMF) is proposed. It provides an efficient mechanism for a fuzzy reasoning within linear time complexity. Thus, it can be used to improve the speed of fuzzy reasoning. In the process of LCBFR, linguistic case indexing and retrieval based on SPMF is suggested. It can be processed relatively fast compared to the previous linguistic approximation methods. From the engineering viewpoint, it may be a valuable advantage.

• Journal of Korean Institute of Industrial Engineers
• /
• v.18 no.1
• /
• pp.81-89
• /
• 1992

After much research on qualitative reasoning, the problem of ambiguities still hampers the practicality of this important AI tool. In this paper, the sources of ambiguities are examined in depth with a systems engineering point of view and possible directions to disambiguation are suggested. This includes some modeling strategies and an architecture of temporal inference for building unambiguous qualitative models of practical complexity. It is argued that knowledge of multiple levels in abstraction hierarchy must be reflected in the modeling to resolve ambiguities by introducing the designer's decisions. The inference engine must be able to integrate two different types of temporal knowledge representation to determine the partial ordering of future events. As an independent quantity management system that supports the suggested modeling approach, LIQUIDS(Linear Quantity-Information Deriving System) is described. The inference scheme can be conjoined with ordinary rule-based reasoning systems and hence generalized into many different domains.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.7 no.2
• /
• pp.25-33
• /
• 1997

A DEDS is a system whose states change in response to the occurence of events from a predefined event set. In this paper, we consider the optimal control and reasoning problem for Discrete Event Systems(DES) in the Temporal Logic Framework(TEL) which have been recnetly defined. The TLE is enhanced with objective functions(event cost indices) and a measurement space is alos deined. A sequence of event which drive the system form a give initial state to a given final state is generated by minimizing a cost functioin index. Our research goal is the reasoning of optimal trajectory and the design of the optimal controller for DESs. This procedure could be guided by the heuristic search methods. For the heuristic search, we suggested the Stochastic Ruler algorithm, instead of the A algorithm with difficulties as following ; the uniqueness of solutions, the computational complexity and how to select a heuristic function. This SR algorithm is used for solving the optimal problem. An example is shown to illustrate our results.

• Journal of Ocean Engineering and Technology
• /
• v.11 no.1
• /
• pp.36-43
• /
• 1997

Weld bead shape is an important measure for evaluation of weld quality. Many welding parameters have influence on the weld bead shape. The quantitative relationship between welding parameters and bead shape, however, is not determined yet because of their high complexity and many unknown factors. Fuzzy expert system is an advanced expert system which uses fuzzy rules and approximate reasoning. It is a vert useful tool for welding technology because is can process rationally the uncertain and inexact information such as the welding information. In this paper, the empirical and the qualitative relationship between welding parameters and bead shape are analyzed and represented by fuzzy rules. They are converted to the quantitative relationship by use of approximate reasoning of fuzzy expert system. Weld bead shape is estimated from the welding parameters using fuzzy expert system. The result of comparison between measured values of weld bead by welding experiments and the estimates values by fuzzy expert system shows a good consistancy.

• Nuclear Engineering and Technology
• /
• v.46 no.6
• /
• pp.753-772
• /
• 2014

The paper presents functional modelling and its application for diagnosis in nuclear power plants. Functional modelling is defined and its relevance for coping with the complexity of diagnosis in large scale systems like nuclear plants is explained. The diagnosis task is analyzed and it is demonstrated that the levels of abstraction in models for diagnosis must reflect plant knowledge about goals and functions which is represented in functional modelling. Multilevel flow modelling (MFM), which is a method for functional modelling, is introduced briefly and illustrated with a cooling system example. The use of MFM for reasoning about causes and consequences is explained in detail and demonstrated using the reasoning tool, the MFMSuite. MFM applications in nuclear power systems are described by two examples: a PWR; and an FBR reactor. The PWR example show how MFM can be used to model and reason about operating modes. The FBR example illustrates how the modelling development effort can be managed by proper strategies including decomposition and reuse.