Automatic Generation of Setup for CNC Spring Coiler Based on Case-based Reasoning

Institute of Scientific and Technical Information of China (English)

KU Xiangchen; WANG Runxiao; LI Jishun; WANG Dongbo

2006-01-01

When producing special-shape spring in CNC spring coiler, the setup of the coiler is often a manual work using a trial-and-error method. As a result, the setup of coiler consumes so much time and becomes the bottleneck of the spring production process. In order to cope with this situation, this paper proposes an automatic generation system of setup for CNC spring coiler using case-based reasoning (CBR). The core of the study contains: (1) integrated reasoning model of CBR system;(2) spatial shape describe of special-shape spring based on feature;(3) coiling case representation using shape feature matrix; and (4) case similarity measure algorithm. The automatic generation system has implemented with C++ Builder 6.0 and is helpful in improving the automaticity and efficiency of spring coiler.

Emerging medical informatics with case-based reasoning for aiding clinical decision in multi-agent system.

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Shen, Ying; Colloc, Joël; Jacquet-Andrieu, Armelle; Lei, Kai

2015-08-01

This research aims to depict the methodological steps and tools about the combined operation of case-based reasoning (CBR) and multi-agent system (MAS) to expose the ontological application in the field of clinical decision support. The multi-agent architecture works for the consideration of the whole cycle of clinical decision-making adaptable to many medical aspects such as the diagnosis, prognosis, treatment, therapeutic monitoring of gastric cancer. In the multi-agent architecture, the ontological agent type employs the domain knowledge to ease the extraction of similar clinical cases and provide treatment suggestions to patients and physicians. Ontological agent is used for the extension of domain hierarchy and the interpretation of input requests. Case-based reasoning memorizes and restores experience data for solving similar problems, with the help of matching approach and defined interfaces of ontologies. A typical case is developed to illustrate the implementation of the knowledge acquisition and restitution of medical experts. Copyright © 2015 Elsevier Inc. All rights reserved.

ROENTGEN: case-based reasoning and radiation therapy planning.

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Berger, J.

1992-01-01

ROENTGEN is a design assistant for radiation therapy planning which uses case-based reasoning, an artificial intelligence technique. It learns both from specific problem-solving experiences and from direct instruction from the user. The first sort of learning is the normal case-based method of storing problem solutions so that they can be reused. The second sort is necessary because ROENTGEN does not, initially, have an internal model of the physics of its problem domain. This dependence on explicit user instruction brings to the forefront representational questions regarding indexing, failure definition, failure explanation and repair. This paper presents the techniques used by ROENTGEN in its knowledge acquisition and design activities. PMID:1482869

Case-based reasoning combined with statistics for diagnostics and prognosis

International Nuclear Information System (INIS)

Olsson, T; Funk, P

2012-01-01

Many approaches used for diagnostics today are based on a precise model. This excludes diagnostics of many complex types of machinery that cannot be modelled and simulated easily or without great effort. Our aim is to show that by including human experience it is possible to diagnose complex machinery when there is no or limited models or simulations available. This also enables diagnostics in a dynamic application where conditions change and new cases are often added. In fact every new solved case increases the diagnostic power of the system. We present a number of successful projects where we have used feature extraction together with case-based reasoning to diagnose faults in industrial robots, welding, cutting machinery and we also present our latest project for diagnosing transmissions by combining Case-Based Reasoning (CBR) with statistics. We view the fault diagnosis process as three consecutive steps. In the first step, sensor fault signals from machines and/or input from human operators are collected. Then, the second step consists of extracting relevant fault features. In the final diagnosis/prognosis step, status and faults are identified and classified. We view prognosis as a special case of diagnosis where the prognosis module predicts a stream of future features.

A conversational case-based reasoning approach to assisting experts in solving professional problems

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Negar Armaghan

2018-03-01

Full Text Available Nowadays, organizations attempt to retrieve, collect, preserve and manage knowledge and experience of experts in order to reuse them later and to promote innovation. In this sense, Experience Management is one of the important organizational issues. This article is discussed the main ideas of a future Conversational Case-Based Reasoning (CCBR intended to assist the experts of after-sales service in a French industrial company. The aim of this research is to formalize the experience of experts in after-sales service in order to better reuse them for similar problems in future. The research opts for an action research method which consists of two main parts: description of failure and proposition of decision protocol. The data were complemented by questionnaires, documentary analysis (including technical reports and other technical documents, observation and many interviews with experts. The findings include several aspects: the formalization of Problem-solving Cards, proposing the structure of case base, as well as the framework of proposed system. These formalizations permit after-sales service experts to provide effective diagnosis and problem-solving.

A prototype case-based reasoning human assistant for space crew assessment and mission management

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Owen, Robert B.; Holland, Albert W.; Wood, Joanna

1993-01-01

We present a prototype human assistant system for space crew assessment and mission management. Our system is based on case episodes from American and Russian space missions and analog environments such as polar stations and undersea habitats. The general domain of small groups in isolated and confined environments represents a near ideal application area for case-based reasoning (CBR) - there are few reliable rules to follow, and most domain knowledge is in the form of cases. We define the problem domain and outline a unique knowledge representation system driven by conflict and communication triggers. The prototype system is able to represent, index, and retrieve case studies of human performance. We index by social, behavioral, and environmental factors. We present the problem domain, our current implementation, our research approach for an operational system, and prototype performance and results.

Safety early warning research for highway construction based on case-based reasoning and variable fuzzy sets.

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Liu, Yan; Yi, Ting-Hua; Xu, Zhen-Jun

2013-01-01

As a high-risk subindustry involved in construction projects, highway construction safety has experienced major developments in the past 20 years, mainly due to the lack of safe early warnings in Chinese construction projects. By combining the current state of early warning technology with the requirements of the State Administration of Work Safety and using case-based reasoning (CBR), this paper expounds on the concept and flow of highway construction safety early warnings based on CBR. The present study provides solutions to three key issues, index selection, accident cause association analysis, and warning degree forecasting implementation, through the use of association rule mining, support vector machine classifiers, and variable fuzzy qualitative and quantitative change criterion modes, which fully cover the needs of safe early warning systems. Using a detailed description of the principles and advantages of each method and by proving the methods' effectiveness and ability to act together in safe early warning applications, effective means and intelligent technology for a safe highway construction early warning system are established.

Safety Early Warning Research for Highway Construction Based on Case-Based Reasoning and Variable Fuzzy Sets

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Yan Liu

2013-01-01

Full Text Available As a high-risk subindustry involved in construction projects, highway construction safety has experienced major developments in the past 20 years, mainly due to the lack of safe early warnings in Chinese construction projects. By combining the current state of early warning technology with the requirements of the State Administration of Work Safety and using case-based reasoning (CBR, this paper expounds on the concept and flow of highway construction safety early warnings based on CBR. The present study provides solutions to three key issues, index selection, accident cause association analysis, and warning degree forecasting implementation, through the use of association rule mining, support vector machine classifiers, and variable fuzzy qualitative and quantitative change criterion modes, which fully cover the needs of safe early warning systems. Using a detailed description of the principles and advantages of each method and by proving the methods’ effectiveness and ability to act together in safe early warning applications, effective means and intelligent technology for a safe highway construction early warning system are established.

Benchmarking of industrial control systems via case-based reasoning

International Nuclear Information System (INIS)

Hadjiiski, M.; Boshnakov, K.; Georgiev, Z.

2013-01-01

Full text: The recent development of information and communication technologies enables the establishment of virtual consultation centers related to the control of specific processes that are widely presented worldwide as the location of the installations does not have influence on the results. The centers can provide consultations regarding the quality of the process control and overall enterprise management as correction factors such as weather conditions, product or service and associated technology, production level, quality of feedstock used and others can be also taken into account. The benchmarking technique is chosen as a tool for analyzing and comparing the quality of the assessed control systems in individual plants. It is a process of gathering, analyzing and comparing data on the characteristics of comparable units to assess and compare these characteristics and improve the performance of the particular process, enterprise or organization. By comparing the different processes and the adoption of the best practices energy efficiency could be improved and hence the competitiveness of the participating organizations will increase. In the presented work algorithm for benchmarking and parametric optimization of a given control system is developed by applying the approaches of Case-Based Reasoning (CBR) and Data Envelopment Analysis (DEA). Expert knowledge and approaches for optimal tuning of control systems are combined. Two of the most common systems for automatic control of different variables in the case of biological wastewater treatment are presented and discussed. Based on analysis of the processes, different cases are defined. By using DEA analysis the relative efficiencies of 10 systems for automatic control of dissolved oxygen are estimated. The designed and implemented in the current work CBR and DEA are applicable for the purposed of virtual consultation centers. Key words: benchmarking technique, energy efficiency, Case-Based Reasoning (CBR

A case-based reasoning tool for breast cancer knowledge management with data mining concepts and techniques

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Demigha, Souâd.

2016-03-01

The paper presents a Case-Based Reasoning Tool for Breast Cancer Knowledge Management to improve breast cancer screening. To develop this tool, we combine both concepts and techniques of Case-Based Reasoning (CBR) and Data Mining (DM). Physicians and radiologists ground their diagnosis on their expertise (past experience) based on clinical cases. Case-Based Reasoning is the process of solving new problems based on the solutions of similar past problems and structured as cases. CBR is suitable for medical use. On the other hand, existing traditional hospital information systems (HIS), Radiological Information Systems (RIS) and Picture Archiving Information Systems (PACS) don't allow managing efficiently medical information because of its complexity and heterogeneity. Data Mining is the process of mining information from a data set and transform it into an understandable structure for further use. Combining CBR to Data Mining techniques will facilitate diagnosis and decision-making of medical experts.

Case-based Reasoning for Automotive Engine Performance Tune-up

International Nuclear Information System (INIS)

Vong, C. M.; Huang, H.; Wong, P. K.

2010-01-01

The automotive engine performance tune-up is greatly affected by the calibration of its electronic control unit (ECU). The ECU calibration is traditionally done by trial-and-error method. This traditional method consumes a large amount of time and money because of a large number of dynamometer tests. To resolve this problem, case based reasoning (CBR) is employed, so that an existing and effective ECU setup can be adapted to fit another similar class of engines. The adaptation procedure is done through a more sophisticated step called case-based adaptation (CBA)[1, 2]. CBA is an effective knowledge management tool, which can interactively learn the expert adaptation knowledge. The paper briefly reviews the methodologies of CBR and CBA. Then the application to ECU calibration is described via a case study. With CBR and CBA, the efficiency of calibrating an ECU can be enhanced. A prototype system has also been developed to verify the usefulness of CBR in ECU calibration.

Learning material recommendation based on case-based reasoning similarity scores

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Masood, Mona; Mokmin, Nur Azlina Mohamed

2017-10-01

A personalized learning material recommendation is important in any Intelligent Tutoring System (ITS). Case-based Reasoning (CBR) is an Artificial Intelligent Algorithm that has been widely used in the development of ITS applications. This study has developed an ITS application that applied the CBR algorithm in the development process. The application has the ability to recommend the most suitable learning material to the specific student based on information in the student profile. In order to test the ability of the application in recommending learning material, two versions of the application were created. The first version displayed the most suitable learning material and the second version displayed the least preferable learning material. The results show the application has successfully assigned the students to the most suitable learning material.

A self-adaptive case-based reasoning system for dose planning in prostate cancer radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Mishra, Nishikant; Petrovic, Sanja; Sundar, Santhanam [Automated Scheduling, Optimisation and Planning Research Group, School of Computer Science, University of Nottingham, Nottingham NG8 1BB (United Kingdom); Department of Oncology, Nottingham University Hospitals NHS Trust, Nottingham NG5 1PB (United Kingdom)

2011-12-15

Purpose: Prostate cancer is the most common cancer in the male population. Radiotherapy is often used in the treatment for prostate cancer. In radiotherapy treatment, the oncologist makes a trade-off between the risk and benefit of the radiation, i.e., the task is to deliver a high dose to the prostate cancer cells and minimize side effects of the treatment. The aim of our research is to develop a software system that will assist the oncologist in planning new treatments. Methods: A nonlinear case-based reasoning system is developed to capture the expertise and experience of oncologists in treating previous patients. Importance (weights) of different clinical parameters in the dose planning is determined by the oncologist based on their past experience, and is highly subjective. The weights are usually fixed in the system. In this research, the weights are updated automatically each time after generating a treatment plan for a new patient using a group based simulated annealing approach. Results: The developed approach is analyzed on the real data set collected from the Nottingham University Hospitals NHS Trust, City Hospital Campus, UK. Extensive experiments show that the dose plan suggested by the proposed method is coherent with the dose plan prescribed by an experienced oncologist or even better. Conclusions: The developed case-based reasoning system enables the use of knowledge and experience gained by the oncologist in treating new patients. This system may play a vital role to assist the oncologist in making a better decision in less computational time; it utilizes the success rate of the previously treated patients and it can also be used in teaching and training processes.

A self-adaptive case-based reasoning system for dose planning in prostate cancer radiotherapy

International Nuclear Information System (INIS)

Mishra, Nishikant; Petrovic, Sanja; Sundar, Santhanam

2011-01-01

Purpose: Prostate cancer is the most common cancer in the male population. Radiotherapy is often used in the treatment for prostate cancer. In radiotherapy treatment, the oncologist makes a trade-off between the risk and benefit of the radiation, i.e., the task is to deliver a high dose to the prostate cancer cells and minimize side effects of the treatment. The aim of our research is to develop a software system that will assist the oncologist in planning new treatments. Methods: A nonlinear case-based reasoning system is developed to capture the expertise and experience of oncologists in treating previous patients. Importance (weights) of different clinical parameters in the dose planning is determined by the oncologist based on their past experience, and is highly subjective. The weights are usually fixed in the system. In this research, the weights are updated automatically each time after generating a treatment plan for a new patient using a group based simulated annealing approach. Results: The developed approach is analyzed on the real data set collected from the Nottingham University Hospitals NHS Trust, City Hospital Campus, UK. Extensive experiments show that the dose plan suggested by the proposed method is coherent with the dose plan prescribed by an experienced oncologist or even better. Conclusions: The developed case-based reasoning system enables the use of knowledge and experience gained by the oncologist in treating new patients. This system may play a vital role to assist the oncologist in making a better decision in less computational time; it utilizes the success rate of the previously treated patients and it can also be used in teaching and training processes.

Irrelevance Reasoning in Knowledge Based Systems

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Levy, A. Y.

1993-01-01

This dissertation considers the problem of reasoning about irrelevance of knowledge in a principled and efficient manner. Specifically, it is concerned with two key problems: (1) developing algorithms for automatically deciding what parts of a knowledge base are irrelevant to a query and (2) the utility of relevance reasoning. The dissertation describes a novel tool, the query-tree, for reasoning about irrelevance. Based on the query-tree, we develop several algorithms for deciding what formulas are irrelevant to a query. Our general framework sheds new light on the problem of detecting independence of queries from updates. We present new results that significantly extend previous work in this area. The framework also provides a setting in which to investigate the connection between the notion of irrelevance and the creation of abstractions. We propose a new approach to research on reasoning with abstractions, in which we investigate the properties of an abstraction by considering the irrelevance claims on which it is based. We demonstrate the potential of the approach for the cases of abstraction of predicates and projection of predicate arguments. Finally, we describe an application of relevance reasoning to the domain of modeling physical devices.

Case-based medical informatics

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Arocha José F

2004-11-01

Full Text Available Abstract Background The "applied" nature distinguishes applied sciences from theoretical sciences. To emphasize this distinction, we begin with a general, meta-level overview of the scientific endeavor. We introduce the knowledge spectrum and four interconnected modalities of knowledge. In addition to the traditional differentiation between implicit and explicit knowledge we outline the concepts of general and individual knowledge. We connect general knowledge with the "frame problem," a fundamental issue of artificial intelligence, and individual knowledge with another important paradigm of artificial intelligence, case-based reasoning, a method of individual knowledge processing that aims at solving new problems based on the solutions to similar past problems. We outline the fundamental differences between Medical Informatics and theoretical sciences and propose that Medical Informatics research should advance individual knowledge processing (case-based reasoning and that natural language processing research is an important step towards this goal that may have ethical implications for patient-centered health medicine. Discussion We focus on fundamental aspects of decision-making, which connect human expertise with individual knowledge processing. We continue with a knowledge spectrum perspective on biomedical knowledge and conclude that case-based reasoning is the paradigm that can advance towards personalized healthcare and that can enable the education of patients and providers. We center the discussion on formal methods of knowledge representation around the frame problem. We propose a context-dependent view on the notion of "meaning" and advocate the need for case-based reasoning research and natural language processing. In the context of memory based knowledge processing, pattern recognition, comparison and analogy-making, we conclude that while humans seem to naturally support the case-based reasoning paradigm (memory of past experiences

Signal Analysis of Automotive Engine Spark Ignition System using Case-Based Reasoning (CBR) and Case-based Maintenance (CBM)

International Nuclear Information System (INIS)

Huang, H.; Vong, C. M.; Wong, P. K.

2010-01-01

With the development of modern technology, modern vehicles adopt electronic control system for injection and ignition. In traditional way, whenever there is any malfunctioning in an automotive engine, an automotive mechanic usually performs a diagnosis in the ignition system of the engine to check any exceptional symptoms. In this paper, we present a case-based reasoning (CBR) approach to help solve human diagnosis problem. Nevertheless, one drawback of CBR system is that the case library will be expanded gradually after repeatedly running the system, which may cause inaccuracy and longer time for the CBR retrieval. To tackle this problem, case-based maintenance (CBM) framework is employed so that the case library of the CBR system will be compressed by clustering to produce a set of representative cases. As a result, the performance (in retrieval accuracy and time) of the whole CBR system can be improved.

Assessing model-based reasoning using evidence-centered design a suite of research-based design patterns

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Mislevy, Robert J; Riconscente, Michelle; Wise Rutstein, Daisy; Ziker, Cindy

2017-01-01

This Springer Brief provides theory, practical guidance, and support tools to help designers create complex, valid assessment tasks for hard-to-measure, yet crucial, science education standards. Understanding, exploring, and interacting with the world through models characterizes science in all its branches and at all levels of education. Model-based reasoning is central to science education and thus science assessment. Current interest in developing and using models has increased with the release of the Next Generation Science Standards, which identified this as one of the eight practices of science and engineering. However, the interactive, complex, and often technology-based tasks that are needed to assess model-based reasoning in its fullest forms are difficult to develop. Building on research in assessment, science education, and learning science, this Brief describes a suite of design patterns that can help assessment designers, researchers, and teachers create tasks for assessing aspects of model-based...

A case-based assistant for clinical psychiatry expertise.

Science.gov (United States)

Bichindaritz, I

1994-01-01

Case-based reasoning is an artificial intelligence methodology for the processing of empirical knowledge. Recent case-based reasoning systems also use theoretic knowledge about the domain to constrain the case-based reasoning. The organization of the memory is the key issue in case-based reasoning. The case-based assistant presented here has two structures in memory: cases and concepts. These memory structures permit it to be as skilled in problem-solving tasks, such as diagnosis and treatment planning, as in interpretive tasks, such as clinical research. A prototype applied to clinical work about eating disorders in psychiatry, reasoning from the alimentary questionnaires of these patients, is presented as an example of the system abilities.

Toward translational incremental similarity-based reasoning in breast cancer grading

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Tutac, Adina E.; Racoceanu, Daniel; Leow, Wee-Keng; Müller, Henning; Putti, Thomas; Cretu, Vladimir

2009-02-01

One of the fundamental issues in bridging the gap between the proliferation of Content-Based Image Retrieval (CBIR) systems in the scientific literature and the deficiency of their usage in medical community is based on the characteristic of CBIR to access information by images or/and text only. Yet, the way physicians are reasoning about patients leads intuitively to a case representation. Hence, a proper solution to overcome this gap is to consider a CBIR approach inspired by Case-Based Reasoning (CBR), which naturally introduces medical knowledge structured by cases. Moreover, in a CBR system, the knowledge is incrementally added and learned. The purpose of this study is to initiate a translational solution from CBIR algorithms to clinical practice, using a CBIR/CBR hybrid approach. Therefore, we advance the idea of a translational incremental similarity-based reasoning (TISBR), using combined CBIR and CBR characteristics: incremental learning of medical knowledge, medical case-based structure of the knowledge (CBR), image usage to retrieve similar cases (CBIR), similarity concept (central for both paradigms). For this purpose, three major axes are explored: the indexing, the cases retrieval and the search refinement, applied to Breast Cancer Grading (BCG), a powerful breast cancer prognosis exam. The effectiveness of this strategy is currently evaluated over cases provided by the Pathology Department of Singapore National University Hospital, for the indexing. With its current accuracy, TISBR launches interesting perspectives for complex reasoning in future medical research, opening the way to a better knowledge traceability and a better acceptance rate of computer-aided diagnosis assistance among practitioners.

Research on SDG-Based Qualitative Reasoning in Conceptual Design

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Kai Li

2013-01-01

Full Text Available Conceptual design is the initial stage throughout the product life cycle, whose main purposes include function creation, function decomposition, and function and subfunction designs. At this stage, the information about product function and structure has the characteristics of imprecision, incompleteness, being qualitative, and so forth, which will affect the validity of conceptual design. In this paper, the signed directed graph is used to reveal the inherent causal relationship and interactions among the variables and find qualitative interactions between design variables and design purpose with the help of causal sequence analysis and constraint propagation. In the case of incomplete information, qualitative reasoning, which has the function of qualitative behavior prediction, can improve conceptual design level aided by the computer. To some extent, qualitative reasoning plays a supplementary role in evaluating scheme and predicting function. At last, with the problem of planar four-bar mechanism design, a qualitative reasoning flowchart based on the Signed Directed Graph is introduced, and an analysis is made of how to adjust design parameters to make the trajectory of a moving point reach to the predetermined position so as to meet the design requirements and achieve the effect that aided designers expect in conceptual design.

Construction Tender Subcontract Selection using Case-based Reasoning

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Due Luu

2012-11-01

Full Text Available Obtaining competitive quotations from suitably qualified subcontractors at tender tim n significantly increase the chance of w1nmng a construction project. Amidst an increasingly growing trend to subcontracting in Australia, selecting appropriate subcontractors for a construction project can be a daunting task requiring the analysis of complex and dynamic criteria such as past performance, suitable experience, track record of competitive pricing, financial stability and so on. Subcontractor selection is plagued with uncertainty and vagueness and these conditions are difficul_t o represent in generalised sets of rules. DeciSIOns pertaining to the selection of subcontr:act?s tender time are usually based on the mtu1t1onand past experience of construction estimators. Case-based reasoning (CBR may be an appropriate method of addressing the chal_lenges of selecting subcontractors because CBR 1s able to harness the experiential knowledge of practitioners. This paper reviews the practicality and suitability of a CBR approach for subcontractor tender selection through the development of a prototype CBR procurement advisory system. In this system, subcontractor selection cases are represented by a set of attributes elicited from experienced construction estimators. The results indicate that CBR can enhance the appropriateness of the selection of subcontractors for construction projects.

Supportive decision making at the point of care: refinement of a case-based reasoning application for use in nursing practice.

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DI Pietro, Tammie L; Doran, Diane M; McArthur, Gregory

2010-01-01

Variations in nursing care have been observed, affecting patient outcomes and quality of care. Case-based reasoners that benchmark for patient indicators can reduce variation through decision support. This study evaluated and validated a case-based reasoning application to establish benchmarks for nursing-sensitive patient outcomes of pain, fatigue, and toilet use, using patient characteristic variables for generating similar cases. Three graduate nursing students participated. Each ranked 25 patient cases using demographics of age, sex, diagnosis, and comorbidities against 10 patients from a database. Participant judgments of case similarity were compared with the case-based reasoning system. Feature weights for each indicator were adjusted to make the case-based reasoning system's similarity ranking correspond more closely to participant judgment. Small differences were noted between initial weights and weights generated from participants. For example, initial weight for comorbidities was 0.35, whereas weights generated by participants for pain, fatigue, and toilet use were 0.49, 0.42, and 0.48, respectively. For the same outcomes, the initial weight for sex was 0.15, but weights generated by the participants were 0.025, 0.002, and 0.000, respectively. Refinement of the case-based reasoning tool established valid benchmarks for patient outcomes in relation to participants and assisted in point-of-care decision making.

A prognostic model for temporal courses that combines temporal abstraction and case-based reasoning.

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Schmidt, Rainer; Gierl, Lothar

2005-03-01

Since clinical management of patients and clinical research are essentially time-oriented endeavours, reasoning about time has become a hot topic in medical informatics. Here we present a method for prognosis of temporal courses, which combines temporal abstractions with case-based reasoning. It is useful for application domains where neither well-known standards, nor known periodicity, nor a complete domain theory exist. We have used our method in two prognostic applications. The first one deals with prognosis of the kidney function for intensive care patients. The idea is to elicit impairments on time, especially to warn against threatening kidney failures. Our second application deals with a completely different domain, namely geographical medicine. Its intention is to compute early warnings against approaching infectious diseases, which are characterised by irregular cyclic occurrences. So far, we have applied our program on influenza and bronchitis. In this paper, we focus on influenza forecast and show first experimental results.

Effects of a Case-Based Reasoning System on Student Performance in a Java Programming Course

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Schmidt, Cecil

2007-01-01

The purpose of this study was to determine if a case-based reasoning tool would improve a student's understanding of the complex concepts in a Java programming course. Subjects for the study were randomly assigned from two sections of an introductory Java programming course. Posttests were used to measure the effects of the case-based reasoning…

Cost-sensitive case-based reasoning using a genetic algorithm: application to medical diagnosis.

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Park, Yoon-Joo; Chun, Se-Hak; Kim, Byung-Chun

2011-02-01

The paper studies the new learning technique called cost-sensitive case-based reasoning (CSCBR) incorporating unequal misclassification cost into CBR model. Conventional CBR is now considered as a suitable technique for diagnosis, prognosis and prescription in medicine. However it lacks the ability to reflect asymmetric misclassification and often assumes that the cost of a positive diagnosis (an illness) as a negative one (no illness) is the same with that of the opposite situation. Thus, the objective of this research is to overcome the limitation of conventional CBR and encourage applying CBR to many real world medical cases associated with costs of asymmetric misclassification errors. The main idea involves adjusting the optimal cut-off classification point for classifying the absence or presence of diseases and the cut-off distance point for selecting optimal neighbors within search spaces based on similarity distribution. These steps are dynamically adapted to new target cases using a genetic algorithm. We apply this proposed method to five real medical datasets and compare the results with two other cost-sensitive learning methods-C5.0 and CART. Our finding shows that the total misclassification cost of CSCBR is lower than other cost-sensitive methods in many cases. Even though the genetic algorithm has limitations in terms of unstable results and over-fitting training data, CSCBR results with GA are better overall than those of other methods. Also the paired t-test results indicate that the total misclassification cost of CSCBR is significantly less than C5.0 and CART for several datasets. We have proposed a new CBR method called cost-sensitive case-based reasoning (CSCBR) that can incorporate unequal misclassification costs into CBR and optimize the number of neighbors dynamically using a genetic algorithm. It is meaningful not only for introducing the concept of cost-sensitive learning to CBR, but also for encouraging the use of CBR in the medical area

How Case-Based Reasoning on e-Community Knowledge Can Be Improved Thanks to Knowledge Reliability

OpenAIRE

Gaillard , Emmanuelle; Lieber , Jean; Nauer , Emmanuel; Cordier , Amélie

2014-01-01

International audience; This paper shows that performing case-based reasoning (CBR) on knowledge coming from an e-community is improved by taking into account knowledge reliability. MKM (meta-knowledge model) is a model for managing reliability of the knowledge units that are used in the reasoning process. For this, MKM uses meta-knowledge such as belief, trust and reputation, about knowledge units and users. MKM is used both to select relevant knowledge to conduct the reasoning process, and ...

A Cold Start Context-Aware Recommender System for Tour Planning Using Artificial Neural Network and Case Based Reasoning

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Zahra Bahramian

2017-01-01

Full Text Available Nowadays, large amounts of tourism information and services are available over the Web. This makes it difficult for the user to search for some specific information such as selecting a tour in a given city as an ordered set of points of interest. Moreover, the user rarely knows all his needs upfront and his preferences may change during a recommendation process. The user may also have a limited number of initial ratings and most often the recommender system is likely to face the well-known cold start problem. The objective of the research presented in this paper is to introduce a hybrid interactive context-aware tourism recommender system that takes into account user’s feedbacks and additional contextual information. It offers personalized tours to the user based on his preferences thanks to the combination of a case based reasoning framework and an artificial neural network. The proposed method has been tried in the city of Tehran in Iran. The results show that the proposed method outperforms current artificial neural network methods and combinations of case based reasoning with k-nearest neighbor methods in terms of user effort, accuracy, and user satisfaction.

Knowledge-light adaptation approaches in case-based reasoning for radiotherapy treatment planning.

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Petrovic, Sanja; Khussainova, Gulmira; Jagannathan, Rupa

2016-03-01

Radiotherapy treatment planning aims at delivering a sufficient radiation dose to cancerous tumour cells while sparing healthy organs in the tumour-surrounding area. It is a time-consuming trial-and-error process that requires the expertise of a group of medical experts including oncologists and medical physicists and can take from 2 to 3h to a few days. Our objective is to improve the performance of our previously built case-based reasoning (CBR) system for brain tumour radiotherapy treatment planning. In this system, a treatment plan for a new patient is retrieved from a case base containing patient cases treated in the past and their treatment plans. However, this system does not perform any adaptation, which is needed to account for any difference between the new and retrieved cases. Generally, the adaptation phase is considered to be intrinsically knowledge-intensive and domain-dependent. Therefore, an adaptation often requires a large amount of domain-specific knowledge, which can be difficult to acquire and often is not readily available. In this study, we investigate approaches to adaptation that do not require much domain knowledge, referred to as knowledge-light adaptation. We developed two adaptation approaches: adaptation based on machine-learning tools and adaptation-guided retrieval. They were used to adapt the beam number and beam angles suggested in the retrieved case. Two machine-learning tools, neural networks and naive Bayes classifier, were used in the adaptation to learn how the difference in attribute values between the retrieved and new cases affects the output of these two cases. The adaptation-guided retrieval takes into consideration not only the similarity between the new and retrieved cases, but also how to adapt the retrieved case. The research was carried out in collaboration with medical physicists at the Nottingham University Hospitals NHS Trust, City Hospital Campus, UK. All experiments were performed using real-world brain cancer

Problem-Oriented Corporate Knowledge Base Models on the Case-Based Reasoning Approach Basis

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Gluhih, I. N.; Akhmadulin, R. K.

2017-07-01

One of the urgent directions of efficiency enhancement of production processes and enterprises activities management is creation and use of corporate knowledge bases. The article suggests a concept of problem-oriented corporate knowledge bases (PO CKB), in which knowledge is arranged around possible problem situations and represents a tool for making and implementing decisions in such situations. For knowledge representation in PO CKB a case-based reasoning approach is encouraged to use. Under this approach, the content of a case as a knowledge base component has been defined; based on the situation tree a PO CKB knowledge model has been developed, in which the knowledge about typical situations as well as specific examples of situations and solutions have been represented. A generalized problem-oriented corporate knowledge base structural chart and possible modes of its operation have been suggested. The obtained models allow creating and using corporate knowledge bases for support of decision making and implementing, training, staff skill upgrading and analysis of the decisions taken. The universal interpretation of terms “situation” and “solution” adopted in the work allows using the suggested models to develop problem-oriented corporate knowledge bases in different subject domains. It has been suggested to use the developed models for making corporate knowledge bases of the enterprises that operate engineer systems and networks at large production facilities.

An effective framework for finding similar cases of dengue from audio and text data using domain thesaurus and case base reasoning

Science.gov (United States)

Sandhu, Rajinder; Kaur, Jaspreet; Thapar, Vivek

2018-02-01

Dengue, also known as break-bone fever, is a tropical disease transmitted by mosquitoes. If the similarity between dengue infected users can be identified, it can help government's health agencies to manage the outbreak more effectively. To find similarity between cases affected by Dengue, user's personal and health information are the two fundamental requirements. Identification of similar symptoms, causes, effects, predictions and treatment procedures, is important. In this paper, an effective framework is proposed which finds similar patients suffering from dengue using keyword aware domain thesaurus and case base reasoning method. This paper focuses on the use of ontology dependent domain thesaurus technique to extract relevant keywords and then build cases with the help of case base reasoning method. Similar cases can be shared with users, nearby hospitals and health organizations to manage the problem more adequately. Two million case bases were generated to test the proposed similarity method. Experimental evaluations of proposed framework resulted in high accuracy and low error rate for finding similar cases of dengue as compared to UPCC and IPCC algorithms. The framework developed in this paper is for dengue but can easily be extended to other domains also.

Case-based clinical reasoning in feline medicine: 2: Managing cognitive error.

Science.gov (United States)

Canfield, Paul J; Whitehead, Martin L; Johnson, Robert; O'Brien, Carolyn R; Malik, Richard

2016-03-01

This is Article 2 of a three-part series on clinical reasoning that encourages practitioners to explore and understand how they think and make case-based decisions. It is hoped that, in the process, they will learn to trust their intuition but, at the same time, put in place safeguards to diminish the impact of bias and misguided logic on their diagnostic decision-making. Article 1, published in the January 2016 issue of JFMS, discussed the relative merits and shortcomings of System 1 thinking (immediate and unconscious) and System 2 thinking (effortful and analytical). This second article examines ways of managing cognitive error, particularly the negative impact of bias, when making a diagnosis. Article 3, to appear in the May 2016 issue, explores the use of heuristics (mental short cuts) and illness scripts in diagnostic reasoning. © The Author(s) 2016.

Novel Agent Based-approach for Industrial Diagnosis: A Combined use Between Case-based Reasoning and Similarity Measure

Directory of Open Access Journals (Sweden)

Fatima Zohra Benkaddour

2016-12-01

Full Text Available In spunlace nonwovens industry, the maintenance task is very complex, it requires experts and operators collaboration. In this paper, we propose a new approach integrating an agent- based modelling with case-based reasoning that utilizes similarity measures and preferences module. The main purpose of our study is to compare and evaluate the most suitable similarity measure for our case. Furthermore, operators that are usually geographically dispersed, have to collaborate and negotiate to achieve mutual agreements, especially when their proposals (diagnosis lead to a conflicting situation. The experimentation shows that the suggested agent-based approach is very interesting and efficient for operators and experts who collaborate in INOTIS enterprise.

PDA: A coupling of knowledge and memory for case-based reasoning

Science.gov (United States)

Bharwani, S.; Walls, J.; Blevins, E.

1988-01-01

Problem solving in most domains requires reference to past knowledge and experience whether such knowledge is represented as rules, decision trees, networks or any variant of attributed graphs. Regardless of the representational form employed, designers of expert systems rarely make a distinction between the static and dynamic aspects of the system's knowledge base. The current paper clearly distinguishes between knowledge-based and memory-based reasoning where the former in its most pure sense is characterized by a static knowledge based resulting in a relatively brittle expert system while the latter is dynamic and analogous to the functions of human memory which learns from experience. The paper discusses the design of an advisory system which combines a knowledge base consisting of domain vocabulary and default dependencies between concepts with a dynamic conceptual memory which stores experimental knowledge in the form of cases. The case memory organizes past experience in the form of MOPs (memory organization packets) and sub-MOPs. Each MOP consists of a context frame and a set of indices. The context frame contains information about the features (norms) common to all the events and sub-MOPs indexed under it.

INTEGRATING CASE-BASED REASONING, KNOWLEDGE-BASED APPROACH AND TSP ALGORITHM FOR MINIMUM TOUR FINDING

Directory of Open Access Journals (Sweden)

Hossein Erfani

2009-07-01

Full Text Available Imagine you have traveled to an unfamiliar city. Before you start your daily tour around the city, you need to know a good route. In Network Theory (NT, this is the traveling salesman problem (TSP. A dynamic programming algorithm is often used for solving this problem. However, when the road network of the city is very complicated and dense, which is usually the case, it will take too long for the algorithm to find the shortest path. Furthermore, in reality, things are not as simple as those stated in AT. For instance, the cost of travel for the same part of the city at different times may not be the same. In this project, we have integrated TSP algorithm with AI knowledge-based approach and case-based reasoning in solving the problem. With this integration, knowledge about the geographical information and past cases are used to help TSP algorithm in finding a solution. This approach dramatically reduces the computation time required for minimum tour finding.

Case-based clinical reasoning in feline medicine: 1: Intuitive and analytical systems.

Science.gov (United States)

Canfield, Paul J; Whitehead, Martin L; Johnson, Robert; O'Brien, Carolyn R; Malik, Richard

2016-01-01

This is Article 1 of a three-part series on clinical reasoning that encourages practitioners to explore and understand how they think and make case-based decisions. It is hoped that, in the process, they will learn to trust their intuition but, at the same time, put in place safeguards to diminish the impact of bias and misguided logic on their diagnostic decision-making. This first article discusses the relative merits and shortcomings of System 1 thinking (immediate and unconscious) and System 2 thinking (effortful and analytical). Articles 2 and 3, to appear in the March and May 2016 issues of JFMS, respectively, will examine managing cognitive error, and use of heuristics (mental short cuts) and illness scripts in diagnostic reasoning. © The Author(s) 2016.

Clinical reasoning and case-based decision making: the fundamental challenge to veterinary educators.

Science.gov (United States)

May, Stephen A

2013-01-01

Confusion about the nature of human reasoning and its appropriate application to patients has hampered veterinary students' development of these skills. Expertise is associated with greater ability to deploy pattern recognition (type 1 reasoning), which is aided by progressive development of data-driven, forward reasoning (in contrast to scientific, backward reasoning), analytical approaches that lead to schema acquisition. The associative nature of type 1 reasoning makes it prone to bias, particularly in the face of "cognitive miserliness," when clues that indicate the need for triangulation with an analytical approach are ignored. However, combined reasoning approaches, from the earliest stages, are more successful than one approach alone, so it is important that those involved in curricular design and delivery promote student understanding of reasoning generally, and the situations in which reasoning goes awry, and develop students' ability to reason safely and accurately whether presented with a familiar case or with a case that they have never seen before.

A case-based reasoning approach for estimating the costs of pump station projects

Directory of Open Access Journals (Sweden)

Mohamed M. Marzouk

2011-10-01

Full Text Available The effective estimation of costs is crucial to the success of construction projects. Cost estimates are used to evaluate, approve and/or fund projects. Organizations use some form of classification system to identify the various types of estimates that may be prepared during the lifecycle of a project. This research presents a parametric-cost model for pump station projects. Fourteen factors have been identified as important to the influence of the cost of pump station projects. A data set that consists of forty-four pump station projects (fifteen water and twenty-nine waste water are collected to build a Case-Based Reasoning (CBR library and to test its performance. The results obtained from the CBR tool are processed and adopted to improve the accuracy of the results. A numerical example is presented to demonstrate the development of the effectiveness of the tool.

Logistics case study based research: Towards higher quality

DEFF Research Database (Denmark)

Pedrosa, Alex; Näslund, Dag; Jasmand, Claudia

2012-01-01

analysis of 134 case study based articles published in six leading logistics and supply chain management (SCM) journals between 1998 and 2010 is used to assess and evaluate the quality of the case study based research approach as documented in these publications. Findings – This research provides...... to address to ensure high quality of the case study based research approach in published articles. Research limitations/implications – This study is limited to the analysis of published articles in six logistics and SCM journals. Further research should investigate different journals in logistics and other...

What physicians reason about during admission case review.

Science.gov (United States)

Juma, Salina; Goldszmidt, Mark

2017-08-01

Research suggests that physicians perform multiple reasoning tasks beyond diagnosis during patient review. However, these remain largely theoretical. The purpose of this study was to explore reasoning tasks in clinical practice during patient admission review. The authors used a constant comparative approach-an iterative and inductive process of coding and recoding-to analyze transcripts from 38 audio-recorded case reviews between junior trainees and their senior residents or attendings. Using a previous list of reasoning tasks, analysis focused on what tasks were performed, when they occurred, and how they related to the other tasks. All 24 tasks were observed in at least one review with a mean of 17.9 (Min = 15, Max = 22) distinct tasks per review. Two new tasks-assess illness severity and patient decision-making capacity-were identified, thus 26 tasks were examined. Three overarching tasks were identified-assess priorities, determine and refine the most likely diagnosis and establish and refine management plans-that occurred throughout all stages of the case review starting from patient identification and continuing through to assessment and plan. A fourth possible overarching task-reflection-was also identified but only observed in four instances across three cases. The other 22 tasks appeared to be context dependent serving to support, expand, and refine one or more overarching tasks. Tasks were non-sequential and the same supporting task could serve more than one overarching task. The authors conclude that these findings provide insight into the 'what' and 'when' of physician reasoning during case review that can be used to support professional development, clinical training and patient care. In particular, they draw attention to the iterative way in which each task is addressed during a case review and how this finding may challenge conventional ways of teaching and assessing clinical communication and reasoning. They also suggest that further research

Knowledge discovery in hyper-heuristic using case-based reasoning on course timetabling

OpenAIRE

Burke, Edmund; MacCarthy, Bart L.; Petrovic, Sanja; Qu, Rong

2002-01-01

This paper presents a new hyper-heuristic method using Case-Based Reasoning (CBR) for solving course timetabling problems. The term Hyper-heuristics has recently been employed to refer to 'heuristics that choose heuristics' rather than heuristics that operate directly on given problems. One of the overriding motivations of hyper-heuristic methods is the attempt to develop techniques that can operate with greater generality than is currently possible. The basic idea behind this is that we main...

Design of a Golf Swing Injury Detection and Evaluation open service platform with Ontology-oriented clustering case-based reasoning mechanism.

Science.gov (United States)

Ku, Hao-Hsiang

2015-01-01

Nowadays, people can easily use a smartphone to get wanted information and requested services. Hence, this study designs and proposes a Golf Swing Injury Detection and Evaluation open service platform with Ontology-oritened clustering case-based reasoning mechanism, which is called GoSIDE, based on Arduino and Open Service Gateway initative (OSGi). GoSIDE is a three-tier architecture, which is composed of Mobile Users, Application Servers and a Cloud-based Digital Convergence Server. A mobile user is with a smartphone and Kinect sensors to detect the user's Golf swing actions and to interact with iDTV. An application server is with Intelligent Golf Swing Posture Analysis Model (iGoSPAM) to check a user's Golf swing actions and to alter this user when he is with error actions. Cloud-based Digital Convergence Server is with Ontology-oriented Clustering Case-based Reasoning (CBR) for Quality of Experiences (OCC4QoE), which is designed to provide QoE services by QoE-based Ontology strategies, rules and events for this user. Furthermore, GoSIDE will automatically trigger OCC4QoE and deliver popular rules for a new user. Experiment results illustrate that GoSIDE can provide appropriate detections for Golfers. Finally, GoSIDE can be a reference model for researchers and engineers.

A Framework to Support Research on Informal Inferential Reasoning

Science.gov (United States)

Zieffler, Andrew; Garfield, Joan; delMas, Robert; Reading, Chris

2008-01-01

Informal inferential reasoning is a relatively recent concept in the research literature. Several research studies have defined this type of cognitive process in slightly different ways. In this paper, a working definition of informal inferential reasoning based on an analysis of the key aspects of statistical inference, and on research from…

A fuzzy-ontology-oriented case-based reasoning framework for semantic diabetes diagnosis.

Science.gov (United States)

El-Sappagh, Shaker; Elmogy, Mohammed; Riad, A M

2015-11-01

Case-based reasoning (CBR) is a problem-solving paradigm that uses past knowledge to interpret or solve new problems. It is suitable for experience-based and theory-less problems. Building a semantically intelligent CBR that mimic the expert thinking can solve many problems especially medical ones. Knowledge-intensive CBR using formal ontologies is an evolvement of this paradigm. Ontologies can be used for case representation and storage, and it can be used as a background knowledge. Using standard medical ontologies, such as SNOMED CT, enhances the interoperability and integration with the health care systems. Moreover, utilizing vague or imprecise knowledge further improves the CBR semantic effectiveness. This paper proposes a fuzzy ontology-based CBR framework. It proposes a fuzzy case-base OWL2 ontology, and a fuzzy semantic retrieval algorithm that handles many feature types. This framework is implemented and tested on the diabetes diagnosis problem. The fuzzy ontology is populated with 60 real diabetic cases. The effectiveness of the proposed approach is illustrated with a set of experiments and case studies. The resulting system can answer complex medical queries related to semantic understanding of medical concepts and handling of vague terms. The resulting fuzzy case-base ontology has 63 concepts, 54 (fuzzy) object properties, 138 (fuzzy) datatype properties, 105 fuzzy datatypes, and 2640 instances. The system achieves an accuracy of 97.67%. We compare our framework with existing CBR systems and a set of five machine-learning classifiers; our system outperforms all of these systems. Building an integrated CBR system can improve its performance. Representing CBR knowledge using the fuzzy ontology and building a case retrieval algorithm that treats different features differently improves the accuracy of the resulting systems. Copyright © 2015 Elsevier B.V. All rights reserved.

High School Students' Reasons for Their Science Dispositions: Community-Based Innovative Technology-Embedded Environmental Research Projects

Science.gov (United States)

Ebenezer, Jazlin; Kaya, Osman Nafiz; Kasab, Dimma

2018-05-01

The purpose of this investigation was to qualitatively describe high school students' reasons for their science dispositions (attitude, perception, and self-confidence) based on their long-term experience with innovative technology-embedded environmental research projects. Students in small groups conducted research projects in and out of school with the help of their teachers and community experts (scientists and engineers). During the 3-year period of this nationally funded project, a total of 135 students from five schools in a mid-west State participated in research activities. Of the 135 students, 53 students were individually interviewed to explore reasons for their science dispositions. Students' reasons for each disposition were grouped into categories, and corresponding frequency was converted to a percentage. The categories of reasons were not only attributed to the use of innovative technologies in environmental research but also the contexts and events that surrounded it. The reasons that influenced students' science dispositions positively were because engaging in environmental research projects with technology contributed to easing fear and difficulty, building a research team, disseminating findings, communicating with the community, researching with scientists, training by teachers, and acknowledging teachers' knowledge. These results advanced how and why students develop science dispositions in the positive direction, which are as follows: building science teacher capacity, developing a community of inquirers, and committing to improve pedagogical practices.

Context based support for Clinical Reasoning

DEFF Research Database (Denmark)

Vilstrup Pedersen, Klaus

2004-01-01

In many areas of the medical domain, the decision process i.e. reasoning, involving health care professionals is distributed, cooperative and complex. Computer based decision support systems has usually been focusing on the outcome of the decision making and treated it as a single task....... In this paper a framework for a Clinical Reasoning Knowledge Warehouse (CRKW) is presented, intended to support the reasoning process, by providing the decision participants with an analysis platform that captures and enhances information and knowledge. The CRKW mixes theories and models from Artificial...... Intelligence, Knowledge Management Systems and Business Intelligence to make context sensitive, patient case specific analysis and knowledge management. The knowledge base consists of patient health records, reasoning process information and clinical guidelines. Patient specific information and knowledge...

Research of Litchi Diseases Diagnosis Expertsystem Based on Rbr and Cbr

Science.gov (United States)

Xu, Bing; Liu, Liqun

To conquer the bottleneck problems existing in the traditional rule-based reasoning diseases diagnosis system, such as low reasoning efficiency and lack of flexibility, etc.. It researched the integrated case-based reasoning (CBR) and rule-based reasoning (RBR) technology, and put forward a litchi diseases diagnosis expert system (LDDES) with integrated reasoning method. The method use data mining and knowledge obtaining technology to establish knowledge base and case library. It adopt rules to instruct the retrieval and matching for CBR, and use association rule and decision trees algorithm to calculate case similarity.The experiment shows that the method can increase the system's flexibility and reasoning ability, and improve the accuracy of litchi diseases diagnosis.

Thermodynamic heuristics with case-based reasoning: combined insights for RNA pseudoknot secondary structure.

Science.gov (United States)

Al-Khatib, Ra'ed M; Rashid, Nur'Aini Abdul; Abdullah, Rosni

2011-08-01

The secondary structure of RNA pseudoknots has been extensively inferred and scrutinized by computational approaches. Experimental methods for determining RNA structure are time consuming and tedious; therefore, predictive computational approaches are required. Predicting the most accurate and energy-stable pseudoknot RNA secondary structure has been proven to be an NP-hard problem. In this paper, a new RNA folding approach, termed MSeeker, is presented; it includes KnotSeeker (a heuristic method) and Mfold (a thermodynamic algorithm). The global optimization of this thermodynamic heuristic approach was further enhanced by using a case-based reasoning technique as a local optimization method. MSeeker is a proposed algorithm for predicting RNA pseudoknot structure from individual sequences, especially long ones. This research demonstrates that MSeeker improves the sensitivity and specificity of existing RNA pseudoknot structure predictions. The performance and structural results from this proposed method were evaluated against seven other state-of-the-art pseudoknot prediction methods. The MSeeker method had better sensitivity than the DotKnot, FlexStem, HotKnots, pknotsRG, ILM, NUPACK and pknotsRE methods, with 79% of the predicted pseudoknot base-pairs being correct.

Evidence in clinical reasoning: a computational linguistics analysis of 789,712 medical case summaries 1983-2012.

Science.gov (United States)

Seidel, Bastian M; Campbell, Steven; Bell, Erica

2015-03-21

Better understanding of clinical reasoning could reduce diagnostic error linked to 8% of adverse medical events and 30% of malpractice cases. To a greater extent than the evidence-based movement, the clinical reasoning literature asserts the importance of practitioner intuition—unconscious elements of diagnostic reasoning. The study aimed to analyse the content of case report summaries in ways that explored the importance of an evidence concept, not only in relation to research literature but also intuition. The study sample comprised all 789,712 abstracts in English for case reports contained in the database PUBMED for the period 1 January 1983 to 31 December 2012. It was hypothesised that, if evidence and intuition concepts were viewed by these clinical authors as essential to understanding their case reports, they would be more likely to be found in the abstracts. Computational linguistics software was used in 1) concept mapping of 21,631,481 instances of 201 concepts, and 2) specific concept analyses examining 200 paired co-occurrences for 'evidence' and research 'literature' concepts. 'Evidence' is a fundamentally patient-centred, intuitive concept linked to less common concepts about underlying processes, suspected disease mechanisms and diagnostic hunches. In contrast, the use of research literature in clinical reasoning is linked to more common reasoning concepts about specific knowledge and descriptions or presenting features of cases. 'Literature' is by far the most dominant concept, increasing in relevance since 2003, with an overall relevance of 13% versus 5% for 'evidence' which has remained static. The fact that the least present types of reasoning concepts relate to diagnostic hunches to do with underlying processes, such as what is suspected, raises questions about whether intuitive practitioner evidence-making, found in a constellation of dynamic, process concepts, has become less important. The study adds support to the existing corpus of

Retrieval with Clustering in a Case-Based Reasoning System for Radiotherapy Treatment Planning

Science.gov (United States)

Khussainova, Gulmira; Petrovic, Sanja; Jagannathan, Rupa

2015-05-01

Radiotherapy treatment planning aims to deliver a sufficient radiation dose to cancerous tumour cells while sparing healthy organs in the tumour surrounding area. This is a trial and error process highly dependent on the medical staff's experience and knowledge. Case-Based Reasoning (CBR) is an artificial intelligence tool that uses past experiences to solve new problems. A CBR system has been developed to facilitate radiotherapy treatment planning for brain cancer. Given a new patient case the existing CBR system retrieves a similar case from an archive of successfully treated patient cases with the suggested treatment plan. The next step requires adaptation of the retrieved treatment plan to meet the specific demands of the new case. The CBR system was tested by medical physicists for the new patient cases. It was discovered that some of the retrieved cases were not suitable and could not be adapted for the new cases. This motivated us to revise the retrieval mechanism of the existing CBR system by adding a clustering stage that clusters cases based on their tumour positions. A number of well-known clustering methods were investigated and employed in the retrieval mechanism. Results using real world brain cancer patient cases have shown that the success rate of the new CBR retrieval is higher than that of the original system.

Retrieval with Clustering in a Case-Based Reasoning System for Radiotherapy Treatment Planning

International Nuclear Information System (INIS)

Khussainova, Gulmira; Petrovic, Sanja; Jagannathan, Rupa

2015-01-01

Radiotherapy treatment planning aims to deliver a sufficient radiation dose to cancerous tumour cells while sparing healthy organs in the tumour surrounding area. This is a trial and error process highly dependent on the medical staff's experience and knowledge. Case-Based Reasoning (CBR) is an artificial intelligence tool that uses past experiences to solve new problems. A CBR system has been developed to facilitate radiotherapy treatment planning for brain cancer. Given a new patient case the existing CBR system retrieves a similar case from an archive of successfully treated patient cases with the suggested treatment plan. The next step requires adaptation of the retrieved treatment plan to meet the specific demands of the new case. The CBR system was tested by medical physicists for the new patient cases. It was discovered that some of the retrieved cases were not suitable and could not be adapted for the new cases. This motivated us to revise the retrieval mechanism of the existing CBR system by adding a clustering stage that clusters cases based on their tumour positions. A number of well-known clustering methods were investigated and employed in the retrieval mechanism. Results using real world brain cancer patient cases have shown that the success rate of the new CBR retrieval is higher than that of the original system. (paper)

Spatial and Temporal Wind Power Forecasting by Case-Based Reasoning Using Big-Data

Directory of Open Access Journals (Sweden)

Fabrizio De Caro

2017-02-01

Full Text Available The massive penetration of wind generators in electrical power systems asks for effective wind power forecasting tools, which should be high reliable, in order to mitigate the effects of the uncertain generation profiles, and fast enough to enhance power system operation. To address these two conflicting objectives, this paper advocates the role of knowledge discovery from big-data, by proposing the integration of adaptive Case Based Reasoning models, and cardinality reduction techniques based on Partial Least Squares Regression, and Principal Component Analysis. The main idea is to learn from a large database of historical climatic observations, how to solve the windforecasting problem, avoiding complex and time-consuming computations. To assess the benefits derived by the application of the proposed methodology in complex application scenarios, the experimental results obtained in a real case study will be presented and discussed.

Properties of inductive reasoning.

Science.gov (United States)

Heit, E

2000-12-01

This paper reviews the main psychological phenomena of inductive reasoning, covering 25 years of experimental and model-based research, in particular addressing four questions. First, what makes a case or event generalizable to other cases? Second, what makes a set of cases generalizable? Third, what makes a property or predicate projectable? Fourth, how do psychological models of induction address these results? The key results in inductive reasoning are outlined, and several recent models, including a new Bayesian account, are evaluated with respect to these results. In addition, future directions for experimental and model-based work are proposed.

Case-based reasoning diagnostic technique based on multi-attribute similarity

Energy Technology Data Exchange (ETDEWEB)

Makoto, Takahashi [Tohoku University, Miyagi (Japan); Akio, Gofuku [Okayama University, Okayamaa (Japan)

2014-08-15

Case-based diagnostic technique has been developed based on the multi-attribute similarity. Specific feature of the developed system is to use multiple attributes of process signals for similarity evaluation to retrieve a similar case stored in a case base. The present technique has been applied to the measurement data from Monju with some simulated anomalies. The results of numerical experiments showed that the present technique can be utilizes as one of the methods for a hybrid-type diagnosis system.

Fuzzy Case-Based Reasoning in Product Style Acquisition Incorporating Valence-Arousal-Based Emotional Cellular Model

Directory of Open Access Journals (Sweden)

Fuqian Shi

2012-01-01

Full Text Available Emotional cellular (EC, proposed in our previous works, is a kind of semantic cell that contains kernel and shell and the kernel is formalized by a triple- L = , where P denotes a typical set of positive examples relative to word-L, d is a pseudodistance measure on emotional two-dimensional space: valence-arousal, and δ is a probability density function on positive real number field. The basic idea of EC model is to assume that the neighborhood radius of each semantic concept is uncertain, and this uncertainty will be measured by one-dimensional density function δ. In this paper, product form features were evaluated by using ECs and to establish the product style database, fuzzy case based reasoning (FCBR model under a defined similarity measurement based on fuzzy nearest neighbors (FNN incorporating EC was applied to extract product styles. A mathematical formalized inference system for product style was also proposed, and it also includes uncertainty measurement tool emotional cellular. A case study of style acquisition of mobile phones illustrated the effectiveness of the proposed methodology.

Using case-based reasoning for the reconstitution and manipulation of voxelized phantoms

International Nuclear Information System (INIS)

Henriet, J.; Fontaine, E.; Bopp, M.; Makovicka, L.; Farah, J.; Broggio, D.; Franck, D.; Chebel-Morello, B.

2010-01-01

The authors reports the development of the EquiVox platform, the aim of which is to allow a radioprotection expert (physician, biologist or other) to work with a phantom which will be the closest possible to the examined person in order to make an as precise as possible dosimetric assessment. The objective is to help to select the best phantom among those the expert knows depending on the assessment type he wants to make. First, they present the general principles of the case-based reasoning, and then the EquiVox platform which proposes all the steps: formalization, elaboration, comparison, and so on. Based on typical numerical values associated with different morphological characteristics, they present and discuss graphical results obtained by the platform. They also discuss their validity and reliability

A case study on the investigation of reasoning skills in geometry ...

African Journals Online (AJOL)

The aim of this study is to evaluate the reasoning skills in geometry-related subjects of six 8th Grade students. The study data were obtained at the end of the 2011-2012 spring period in a public elementary school. The study uses a case study with qualitative research techniques to investigate how students use reasoning ...

Optimization of the Case Based Reasoning Systems

International Nuclear Information System (INIS)

Mohamed, A.H.

2014-01-01

Intrusion Detection System (IDS) have a great importance in saving the authority of the information widely spread all over the world through the networks. Many Case Based Systems concerned on the different methods of the unauthorized users/hackers that face the developers of the IDS. The proposed system introduces a new hybrid system that uses the genetic algorithm to optimize an IDS - case based system. It can detect the new anomalies appeared through the network and use the cases in the case library to determine the suitable solution for their behavior. The suggested system can solve the problem either by using an old identical solution or adapt the optimum one till have the targeted solution. The proposed system has been applied to block unauthorized users / hackers from attach the medical images for radiotherapy of the cancer diseases during their transmission through web. The proposed system can prove its accepted performance in this manner

Model-based reasoning technology for the power industry

International Nuclear Information System (INIS)

Touchton, R.A.; Subramanyan, N.S.; Naser, J.A.

1991-01-01

This paper reports on model-based reasoning which refers to an expert system implementation methodology that uses a model of the system which is being reasoned about. Model-based representation and reasoning techniques offer many advantages and are highly suitable for domains where the individual components, their interconnection, and their behavior is well-known. Technology Applications, Inc. (TAI), under contract to the Electric Power Research Institute (EPRI), investigated the use of model-based reasoning in the power industry including the nuclear power industry. During this project, a model-based monitoring and diagnostic tool, called ProSys, was developed. Also, an alarm prioritization system was developed as a demonstration prototype

Clinical reasoning and its application to nursing: concepts and research studies.

Science.gov (United States)

Banning, Maggi

2008-05-01

Clinical reasoning may be defined as "the process of applying knowledge and expertise to a clinical situation to develop a solution" [Carr, S., 2004. A framework for understanding clinical reasoning in community nursing. J. Clin. Nursing 13 (7), 850-857]. Several forms of reasoning exist each has its own merits and uses. Reasoning involves the processes of cognition or thinking and metacognition. In nursing, clinical reasoning skills are an expected component of expert and competent practise. Nurse research studies have identified concepts, processes and thinking strategies that might underpin the clinical reasoning used by pre-registration nurses and experienced nurses. Much of the available research on reasoning is based on the use of the think aloud approach. Although this is a useful method, it is dependent on ability to describe and verbalise the reasoning process. More nursing research is needed to explore the clinical reasoning process. Investment in teaching and learning methods is needed to enhance clinical reasoning skills in nurses.

Employing Model-Based Reasoning in Interdisciplinary Research Teams: Evidence-Based Practices for Integrating Knowledge Across Systems

Science.gov (United States)

Pennington, D. D.; Vincent, S.

2017-12-01

The NSF-funded project "Employing Model-Based Reasoning in Socio-Environmental Synthesis (EMBeRS)" has developed a generic model for exchanging knowledge across disciplines that is based on findings from the cognitive, learning, social, and organizational sciences addressing teamwork in complex problem solving situations. Two ten-day summer workshops for PhD students from large, NSF-funded interdisciplinary projects working on a variety of water issues were conducted in 2016 and 2017, testing the model by collecting a variety of data, including surveys, interviews, audio/video recordings, material artifacts and documents, and photographs. This presentation will introduce the EMBeRS model, the design of workshop activities based on the model, and results from surveys and interviews with the participating students. Findings suggest that this approach is very effective for developing a shared, integrated research vision across disciplines, compared with activities typically provided by most large research projects, and that students believe the skills developed in the EMBeRS workshops are unique and highly desireable.

Case-based clinical reasoning in feline medicine: 3: Use of heuristics and illness scripts.

Science.gov (United States)

Whitehead, Martin L; Canfield, Paul J; Johnson, Robert; O'Brien, Carolyn R; Malik, Richard

2016-05-01

This is Article 3 of a three-part series on clinical reasoning that encourages practitioners to explore and understand how they think and make case-based decisions. It is hoped that, in the process, they will learn to trust their intuition but, at the same time, put in place safeguards to diminish the impact of bias and misguided logic on their diagnostic decision-making. Article 1, published in the January 2016 issue of JFMS, discussed the relative merits and shortcomings of System 1 thinking (immediate and unconscious) and System 2 thinking (effortful and analytical). In Article 2, published in the March 2016 issue, ways of managing cognitive error, particularly the negative impact of bias, in making a diagnosis were examined. This final article explores the use of heuristics (mental short cuts) and illness scripts in diagnostic reasoning. © The Author(s) 2016.

Reasoning based in cases applied to diagnosis of electric generators; Razonamiento basado en casos aplicado al diagnostico de generadores electricos

Energy Technology Data Exchange (ETDEWEB)

De la Torre Vega, H. Octavio; Garcia Tevillo, Arturo; Campuzano Martinez, Roberto [Instituto de Investigaciones Electricas, Temixco, Morelos (Mexico); Lopez Azamar, Ernesto [Comision Federal de Electricidad (Mexico)

2000-07-01

The development of a system for the diagnosis of electrical generators that apply techniques of artificial intelligence, is presented, as it is the reasoning based on cases, to support the work of the diagnosis engineer. This system is part of a system called CADIS, dedicated to the diagnosis of electrical generators out of line and reason of previous articles. In this occasion the characteristics of the reasoning module based on experiences (SirBE) are emphasized, indicating how to make a diagnosis using similar cases and how to edit the system base of experience, using the interactive editor of cases. It is included, in addition, a summarized example which represents a case for SirBE and how the system helps to make a diagnosis. [Spanish] Se presenta el desarrollo de un sistema de diagnostico de generadores electricos que aplica tecnicas de inteligencia artificial, como es el razonamiento basado en casos, para apoyar la labor del ingeniero de diagnostico. Este sistema es parte de un sistema denominado CADIS, dedicado al diagnostico de generadores electricos fuera de linea y motivo de articulos anteriores. En esta ocasion se resaltan las caracteristicas del modulo de razonamiento basado en experiencias (SirBE), indicando como realizar un diagnostico utilizando casos similares y como editar la base de experiencia del sistema utilizando el editor interactivo de casos. Se incluye, ademas, un ejemplo resumido de lo que representa un caso para SiRBE y como el sistema ayuda a realizar un diagnostico.

A case-based assistant for clinical psychiatry expertise.

OpenAIRE

Bichindaritz, I.

1994-01-01

Case-based reasoning is an artificial intelligence methodology for the processing of empirical knowledge. Recent case-based reasoning systems also use theoretic knowledge about the domain to constrain the case-based reasoning. The organization of the memory is the key issue in case-based reasoning. The case-based assistant presented here has two structures in memory: cases and concepts. These memory structures permit it to be as skilled in problem-solving tasks, such as diagnosis and treatmen...

Design principles for simulation games for learning clinical reasoning: A design-based research approach.

Science.gov (United States)

Koivisto, J-M; Haavisto, E; Niemi, H; Haho, P; Nylund, S; Multisilta, J

2018-01-01

Nurses sometimes lack the competence needed for recognising deterioration in patient conditions and this is often due to poor clinical reasoning. There is a need to develop new possibilities for learning this crucial competence area. In addition, educators need to be future oriented; they need to be able to design and adopt new pedagogical innovations. The purpose of the study is to describe the development process and to generate principles for the design of nursing simulation games. A design-based research methodology is applied in this study. Iterative cycles of analysis, design, development, testing and refinement were conducted via collaboration among researchers, educators, students, and game designers. The study facilitated the generation of reusable design principles for simulation games to guide future designers when designing and developing simulation games for learning clinical reasoning. This study makes a major contribution to research on simulation game development in the field of nursing education. The results of this study provide important insights into the significance of involving nurse educators in the design and development process of educational simulation games for the purpose of nursing education. Copyright © 2017 Elsevier Ltd. All rights reserved.

Reasoning by cases in Default Logic

NARCIS (Netherlands)

Roos, N.; Roos, Nico

1998-01-01

Reiter's Default Logic is one of the most popular formalisms for describing default reasoning. One important defect of Default Logic is, however, the inability to reason by cases. Over the years, several solutions for this problem have been proposed. All these proposals deal with deriving new

Secondary School Students' Understanding of Science and Their Socioscientific Reasoning

Science.gov (United States)

Karahan, Engin; Roehrig, Gillian

2017-08-01

Research in socioscientific issue (SSI)-based interventions is relatively new (Sadler in Journal of Research in Science Teaching 41:513-536, 2004; Zeidler et al. in Journal of Research in Science Teaching 46:74-101, 2009), and there is a need for understanding more about the effects of SSI-based learning environments (Sadler in Journal of Research in Science Teaching 41:513-536, 2004). Lee and Witz (International Journal of Science Education 31:931-960, 2009) highlighted the need for detailed case studies that would focus on how students respond to teachers' practices of teaching SSI. This study presents case studies that investigated the development of secondary school students' science understanding and their socioscientific reasoning within SSI-based learning environments. A multiple case study with embedded units of analysis was implemented for this research because of the contextual differences for each case. The findings of the study revealed that students' understanding of science, including scientific method, social and cultural influences on science, and scientific bias, was strongly influenced by their experiences in SSI-based learning environments. Furthermore, multidimensional SSI-based science classes resulted in students having multiple reasoning modes, such as ethical and economic reasoning, compared to data-driven SSI-based science classes. In addition to portraying how participants presented complexity, perspectives, inquiry, and skepticism as aspects of socioscientific reasoning (Sadler et al. in Research in Science Education 37:371-391, 2007), this study proposes the inclusion of three additional aspects for the socioscientific reasoning theoretical construct: (1) identification of social domains affecting the SSI, (2) using cost and benefit analysis for evaluation of claims, and (3) understanding that SSIs and scientific studies around them are context-bound.

A combined data mining approach using rough set theory and case-based reasoning in medical datasets

Directory of Open Access Journals (Sweden)

Mohammad Taghi Rezvan

2014-06-01

Full Text Available Case-based reasoning (CBR is the process of solving new cases by retrieving the most relevant ones from an existing knowledge-base. Since, irrelevant or redundant features not only remarkably increase memory requirements but also the time complexity of the case retrieval, reducing the number of dimensions is an issue worth considering. This paper uses rough set theory (RST in order to reduce the number of dimensions in a CBR classifier with the aim of increasing accuracy and efficiency. CBR exploits a distance based co-occurrence of categorical data to measure similarity of cases. This distance is based on the proportional distribution of different categorical values of features. The weight used for a feature is the average of co-occurrence values of the features. The combination of RST and CBR has been applied to real categorical datasets of Wisconsin Breast Cancer, Lymphography, and Primary cancer. The 5-fold cross validation method is used to evaluate the performance of the proposed approach. The results show that this combined approach lowers computational costs and improves performance metrics including accuracy and interpretability compared to other approaches developed in the literature.

Delusional Ideation, Cognitive Processes and Crime Based Reasoning.

Science.gov (United States)

Wilkinson, Dean J; Caulfield, Laura S

2017-08-01

Probabilistic reasoning biases have been widely associated with levels of delusional belief ideation (Galbraith, Manktelow, & Morris, 2010; Lincoln, Ziegler, Mehl, & Rief, 2010; Speechley, Whitman, & Woodward, 2010; White & Mansell, 2009), however, little research has focused on biases occurring during every day reasoning (Galbraith, Manktelow, & Morris, 2011), and moral and crime based reasoning (Wilkinson, Caulfield, & Jones, 2014; Wilkinson, Jones, & Caulfield, 2011). 235 participants were recruited across four experiments exploring crime based reasoning through different modalities and dual processing tasks. Study one explored delusional ideation when completing a visually presented crime based reasoning task. Study two explored the same task in an auditory presentation. Study three utilised a dual task paradigm to explore modality and executive functioning. Study four extended this paradigm to the auditory modality. The results indicated that modality and delusional ideation have a significant effect on individuals reasoning about violent and non-violent crime (p < .05), which could have implication for the presentation of evidence in applied setting such as the courtroom.

A Clinical Reasoning Tool for Virtual Patients: Design-Based Research Study.

Science.gov (United States)

Hege, Inga; Kononowicz, Andrzej A; Adler, Martin

2017-11-02

Clinical reasoning is a fundamental process medical students have to learn during and after medical school. Virtual patients (VP) are a technology-enhanced learning method to teach clinical reasoning. However, VP systems do not exploit their full potential concerning the clinical reasoning process; for example, most systems focus on the outcome and less on the process of clinical reasoning. Keeping our concept grounded in a former qualitative study, we aimed to design and implement a tool to enhance VPs with activities and feedback, which specifically foster the acquisition of clinical reasoning skills. We designed the tool by translating elements of a conceptual clinical reasoning learning framework into software requirements. The resulting clinical reasoning tool enables learners to build their patient's illness script as a concept map when they are working on a VP scenario. The student's map is compared with the experts' reasoning at each stage of the VP, which is technically enabled by using Medical Subject Headings, which is a comprehensive controlled vocabulary published by the US National Library of Medicine. The tool is implemented using Web technologies, has an open architecture that enables its integration into various systems through an open application program interface, and is available under a Massachusetts Institute of Technology license. We conducted usability tests following a think-aloud protocol and a pilot field study with maps created by 64 medical students. The results show that learners interact with the tool but create less nodes and connections in the concept map than an expert. Further research and usability tests are required to analyze the reasons. The presented tool is a versatile, systematically developed software component that specifically supports the clinical reasoning skills acquisition. It can be plugged into VP systems or used as stand-alone software in other teaching scenarios. The modular design allows an extension with new

Case Studies of Secondary School Teachers Designing Socioscientific Issues-Based Instruction and Their Students' Socioscientific Reasoning

Science.gov (United States)

Karahan, Engin

Addressing socioscientific issues (SSI) has been one of the main focuses in science education since the Science, Technology, and Society (STS) movement in the 1970s (Levinson, 2006); however, teaching controversial socioscientific issues has always been challenging for teachers (Dillon, 1994; Osborne, Duschl, & Fairbrother, 2002). Although teachers exhibit positive attitudes for using controversial socioscientific issues in their science classrooms, only a small percentage of them actually incorporate SSI content into their science curricula on a regular basis (Sadler, Amirshokoohi, Kazempour, & Allspaw, 2006; Lee & Witz, 2009). The literature in science education has highlighted the signi?cant relationships among teacher beliefs, teaching practices, and student learning (Bryan & Atwater, 2002; King, Shumow, & Lietz, 2001; Lederman, 1992). Despite the fact that the case studies present a relatively detailed picture of teachers' values and motivations for teaching SSI (e.g. Lee, 2006; Lee & Witz, 2009; Reis & Galvao, 2004), these studies still miss the practices of these teachers and potential outcomes for their students. Therefore, there is a great need for in-depth case studies that would focus on teachers' practices of designing and teaching SSI-based learning environments, their deeper beliefs and motivations for teaching SSI, and their students' response to these practices (Lee, 2006). This dissertation is structured as three separate, but related, studies about secondary school teachers' experiences of designing and teaching SSI-based classes and their students' understanding of science and SSI reasoning. The case studies in this dissertation seek answers for (1) teachers' practices of designing and teaching SSI-based instruction, as well as its relation to their deeper personal beliefs and motivations to teach SSI, and (2) how their students respond to their approaches of teaching SSI in terms of their science understanding and SSI reasoning. The first paper

Penerapan Case-Based Reasoning Pada Sistem Cerdas Untuk Pendeteksian dan Penanganan Dini Penyakit Sapi

Directory of Open Access Journals (Sweden)

Irlando Moggi Prakoso

2012-09-01

Full Text Available Penyakit sapi memberikan dampak yang signifikan terhadap penurunan produksi daging bagi para peternak sapi. Untuk meminimalisir dampak dari penyakit perlu dilakukan pendeteksian dan penanganan dini untuk mencegah tingginya kerugian yang terjadi. Sistem cerdas dapat memudahkan peternak sapi untuk mendiagnosa secara mandiri. Penelitian sebelumnya menghasilkan sistem cerdas  untuk mendiagnosa penyakit sapi menggunakan algoritma Backpropagation Artificial neural Network(ANN. Namun ANN bersifat black-box karena kita tidak dapat melihat informasi yang mendasari hasil diagnosa. Tugas akhir ini memiliki tujuan untuk menjawab permasalahan tersebut, yakni dengan membuat sistem cerdas berbasis Cased-Based Reasoning(CBR untuk menyempurnakan sistem cerdas yang sebelumnya dibuat menggunakan ANN. CBR memberikan hasil diagnosa berdasarkan permasalahan terdahulu yang dapat direvisi untuk memecahkan permasalahan terbaru. Dari ketiga uji coba dengan case didalam case memory(skenario 1, diluar case memory(skenario 2, dan gejala parsial dari case memory(skenario 3 mendapatkan hasil yang baik dengan nilai precision 100% dan 95.83% untuk skenario 1 dan 3.   Serta nilai precision yang memang kurang baik untuk skenario 2 sebesar 59.31%. Dengan demikian, sistem cerdas ini dapat memberikan hasil diagnosa yang akurat dan memudahkan peternak sapi dalam mendiagnosa secara mandiri.

Inductive reasoning.

Science.gov (United States)

Hayes, Brett K; Heit, Evan; Swendsen, Haruka

2010-03-01

Inductive reasoning entails using existing knowledge or observations to make predictions about novel cases. We review recent findings in research on category-based induction as well as theoretical models of these results, including similarity-based models, connectionist networks, an account based on relevance theory, Bayesian models, and other mathematical models. A number of touchstone empirical phenomena that involve taxonomic similarity are described. We also examine phenomena involving more complex background knowledge about premises and conclusions of inductive arguments and the properties referenced. Earlier models are shown to give a good account of similarity-based phenomena but not knowledge-based phenomena. Recent models that aim to account for both similarity-based and knowledge-based phenomena are reviewed and evaluated. Among the most important new directions in induction research are a focus on induction with uncertain premise categories, the modeling of the relationship between inductive and deductive reasoning, and examination of the neural substrates of induction. A common theme in both the well-established and emerging lines of induction research is the need to develop well-articulated and empirically testable formal models of induction. Copyright © 2010 John Wiley & Sons, Ltd. For further resources related to this article, please visit the WIREs website. Copyright © 2010 John Wiley & Sons, Ltd.

Learning and case-based reasoning for faults diagnosis-aiding in nuclear power plants

International Nuclear Information System (INIS)

Nicolini, C.

1998-01-01

The aim of this thesis is the design of a faults diagnosis-aiding system in a nuclear facility of the Cea. Actually the existing system allows the optimization of the production processes in regular operating conditions. Meanwhile during accidental events, the alarms, managed by threshold, are bringing no relevant information. To increase the reliability and the safety, the human operator needs a faults diagnosis-aiding system. The developed system, SECAPI, combines problem solving techniques and automatic learning techniques, that allow the diagnosis and the the simulation of various faults happening on nuclear facilities. Its reasoning principle uses case-based and rules-based techniques. SECAPI owns a learning module which reads out knowledge connected with faults. It can then simulate various faults, using the inductive logical computing. SECAPI has been applied on a radioactive tritium treatment operating channel, at the Cea with good results. (A.L.B.)

An ontological case base engineering methodology for diabetes management.

Science.gov (United States)

El-Sappagh, Shaker H; El-Masri, Samir; Elmogy, Mohammed; Riad, A M; Saddik, Basema

2014-08-01

Ontology engineering covers issues related to ontology development and use. In Case Based Reasoning (CBR) system, ontology plays two main roles; the first as case base and the second as domain ontology. However, the ontology engineering literature does not provide adequate guidance on how to build, evaluate, and maintain ontologies. This paper proposes an ontology engineering methodology to generate case bases in the medical domain. It mainly focuses on the research of case representation in the form of ontology to support the case semantic retrieval and enhance all knowledge intensive CBR processes. A case study on diabetes diagnosis case base will be provided to evaluate the proposed methodology.

Hybrid Genetic Algorithm Optimization for Case Based Reasoning Systems

International Nuclear Information System (INIS)

Mohamed, A.H.

2008-01-01

The success of a CBR system largely depen ds on an effective retrieval of useful prior case for the problem. Nearest neighbor and induction are the main CBR retrieval algorithms. Each of them can be more suitable in different situations. Integrated the two retrieval algorithms can catch the advantages of both of them. But, they still have some limitations facing the induction retrieval algorithm when dealing with a noisy data, a large number of irrelevant features, and different types of data. This research utilizes a hybrid approach using genetic algorithms (GAs) to case-based induction retrieval of the integrated nearest neighbor - induction algorithm in an attempt to overcome these limitations and increase the overall classification accuracy. GAs can be used to optimize the search space of all the possible subsets of the features set. It can deal with the irrelevant and noisy features while still achieving a significant improvement of the retrieval accuracy. Therefore, the proposed CBR-GA introduces an effective general purpose retrieval algorithm that can improve the performance of CBR systems. It can be applied in many application areas. CBR-GA has proven its success when applied for different problems in real-life

A Case-based Reasoning Approach to Validate Grammatical Gender and Number Agreement in Spanish language

Directory of Open Access Journals (Sweden)

Jorge Bacca

2013-03-01

Full Text Available Across Latin America 420 indigenous languages are spoken. Spanish is considered a second language in indigenous communities and is progressively introduced in education. However, most of the tools to support teaching processes of a second language have been developed for the most common languages such as English, French, German, Italian, etc. As a result, only a small amount of learning objects and authoring tools have been developed for indigenous people considering the specific needs of their population. This paper introduces Multilingual–Tiny as a web authoring tool to support the virtual experience of indigenous students and teachers when they are creating learning objects in indigenous languages or in Spanish language, in particular, when they have to deal with the grammatical structures of Spanish. Multilingual–Tiny has a module based on the Case-based Reasoning technique to provide recommendations in real time when teachers and students write texts in Spanish. An experiment was performed in order to compare some local similarity functions to retrieve cases from the case library taking into account the grammatical structures. As a result we found the similarity function with the best performance

Model Based Temporal Reasoning

Science.gov (United States)

Rabin, Marla J.; Spinrad, Paul R.; Fall, Thomas C.

1988-03-01

Systems that assess the real world must cope with evidence that is uncertain, ambiguous, and spread over time. Typically, the most important function of an assessment system is to identify when activities are occurring that are unusual or unanticipated. Model based temporal reasoning addresses both of these requirements. The differences among temporal reasoning schemes lies in the methods used to avoid computational intractability. If we had n pieces of data and we wanted to examine how they were related, the worst case would be where we had to examine every subset of these points to see if that subset satisfied the relations. This would be 2n, which is intractable. Models compress this; if several data points are all compatible with a model, then that model represents all those data points. Data points are then considered related if they lie within the same model or if they lie in models that are related. Models thus address the intractability problem. They also address the problem of determining unusual activities if the data do not agree with models that are indicated by earlier data then something out of the norm is taking place. The models can summarize what we know up to that time, so when they are not predicting correctly, either something unusual is happening or we need to revise our models. The model based reasoner developed at Advanced Decision Systems is thus both intuitive and powerful. It is currently being used on one operational system and several prototype systems. It has enough power to be used in domains spanning the spectrum from manufacturing engineering and project management to low-intensity conflict and strategic assessment.

Modelling Legal Argument: Reasoning with Cases and Hypotheticals

Science.gov (United States)

1988-02-01

case- based reasoning plays an important role in such diverse domains as law [Levi, 1949), historical political analysis [Neustadt and May, 1986; Alker...contained information on physical, economic and political disputes and common mediation 5 tactics, their failures and corrections for those failures...library of 13 Wall Street. He had opera tickets in his pocket for 8:00 that night - "Pagliacci" - and his socialite fiance and her parents were to

A fuzzy ontology modeling for case base knowledge in diabetes mellitus domain

Directory of Open Access Journals (Sweden)

Shaker El-Sappagh

2017-06-01

Full Text Available Knowledge-Intensive Case-Based Reasoning Systems (KI-CBR mainly depend on ontologies. Ontology can play the role of case-base knowledge. The combination of ontology and fuzzy logic reasoning is critical in the medical domain. Case-base representation based on fuzzy ontology is expected to enhance the semantic and storage of CBR knowledge-base. This paper provides an advancement to the research of diabetes diagnosis CBR by proposing a novel case-base fuzzy OWL2 ontology (CBRDiabOnto. This ontology can be considered as the first fuzzy case-base ontology in the medical domain. It is based on a case-base fuzzy Extended Entity Relation (EER data model. It contains 63 (fuzzy classes, 54 (fuzzy object properties, 138 (fuzzy datatype properties, and 105 fuzzy datatypes. We populated the ontology with 60 cases and used SPARQL-DL for its query. The evaluation of CBRDiabOnto shows that it is accurate, consistent, and cover terminologies and logic of diabetes mellitus diagnosis.

Understanding clinical reasoning in osteopathy: a qualitative research approach.

Science.gov (United States)

Grace, Sandra; Orrock, Paul; Vaughan, Brett; Blaich, Raymond; Coutts, Rosanne

2016-01-01

Clinical reasoning has been described as a process that draws heavily on the knowledge, skills and attributes that are particular to each health profession. However, the clinical reasoning processes of practitioners of different disciplines demonstrate many similarities, including hypothesis generation and reflective practice. The aim of this study was to understand clinical reasoning in osteopathy from the perspective of osteopathic clinical educators and the extent to which it was similar or different from clinical reasoning in other health professions. This study was informed by constructivist grounded theory. Participants were clinical educators in osteopathic teaching institutions in Australia, New Zealand and the UK. Focus groups and written critical reflections provided a rich data set. Data were analysed using constant comparison to develop inductive categories. According to participants, clinical reasoning in osteopathy is different from clinical reasoning in other health professions. Osteopaths use a two-phase approach: an initial biomedical screen for serious pathology, followed by use of osteopathic reasoning models that are based on the relationship between structure and function in the human body. Clinical reasoning in osteopathy was also described as occurring in a number of contexts (e.g. patient, practitioner and community) and drawing on a range of metaskills (e.g. hypothesis generation and reflexivity) that have been described in other health professions. The use of diagnostic reasoning models that are based on the relationship between structure and function in the human body differentiated clinical reasoning in osteopathy. These models were not used to name a medical condition but rather to guide the selection of treatment approaches. If confirmed by further research that clinical reasoning in osteopathy is distinct from clinical reasoning in other health professions, then osteopaths may have a unique perspective to bring to multidisciplinary

Reasons for placement of restorations on previously unrestored tooth surfaces by dentists in The Dental Practice-Based Research Network

DEFF Research Database (Denmark)

Nascimento, Marcelle M; Gordan, Valeria V; Qvist, Vibeke

2010-01-01

The authors conducted a study to identify and quantify the reasons used by dentists in The Dental Practice-Based Research Network (DPBRN) for placing restorations on unrestored permanent tooth surfaces and the dental materials they used in doing so....

MTK: An AI tool for model-based reasoning

Science.gov (United States)

Erickson, William K.; Schwartz, Mary R.

1987-01-01

A 1988 goal for the Systems Autonomy Demonstration Project Office of the NASA Ames Research Center is to apply model-based representation and reasoning techniques in a knowledge-based system that will provide monitoring, fault diagnosis, control and trend analysis of the space station Thermal Management System (TMS). A number of issues raised during the development of the first prototype system inspired the design and construction of a model-based reasoning tool called MTK, which was used in the building of the second prototype. These issues are outlined, along with examples from the thermal system to highlight the motivating factors behind them. An overview of the capabilities of MTK is given.

Rule Based Reasoning Untuk Monitoring Distribusi Bahan Bakar Minyak Secara Online dan Realtime menggunakan Radio Frequency Identification

Directory of Open Access Journals (Sweden)

Mokhamad Iklil Mustofa

2017-05-01

Full Text Available The scarcity of fuel oil in Indonesia often occurs due to delays in delivery caused by natural factors or transportation constraints. Theaim of this  research is to develop systems of fuel distribution monitoring online and realtime using rule base reasoning method and radio frequency identification technology. The rule-based reasoning method is used as a rule-based reasoning model used for monitoring distribution and determine rule-based safety stock. The monitoring system program is run with a web-based computer application. Radio frequency identification technology is used by utilizing radio waves as an media identification. This technology is used as a system of tracking and gathering information from objects automatically. The research data uses data of delayed distribution of fuel from fuel terminal to consumer. The monitoring technique uses the time of departure, the estimated time to arrive, the route / route passed by a fuel tanker attached to the radio frequency Identification tag. This monitoring system is carried out by the radio frequency identification reader connected online at any gas station or specified position that has been designed with study case in Semarang. The results of the research covering  the status of rule based reasoning that sends status, that is timely and appropriate paths, timely and truncated pathways, late and on track, late and cut off, and tank lost. The monitoring system is also used in determining the safety stock warehouse, with the safety stock value determined based on the condition of the stock warehouse rules.

A review of practical reasoning in child and youth research

DEFF Research Database (Denmark)

Ljungdalh, Anders Kruse

2016-01-01

The purpose of the review is to investigate various relations between the concepts of competence and participation found within child and youth research with the aim of identifying differences in practical reasoning of the various kinds of child research. The search identified 260 articles, and a...... different ways of understanding means and ends in child research. The review thereby offers an understanding of how and why interdisciplinary problems sometimes occur in education and child care.......The purpose of the review is to investigate various relations between the concepts of competence and participation found within child and youth research with the aim of identifying differences in practical reasoning of the various kinds of child research. The search identified 260 articles......, and an in-depth analysis of 39 articles was conducted, elaborating the conceptual differences inherent in the different child research fields. Based on a philosophy of practice, the analysis identified 3 different causal connections between the concepts of competence and participation, indicating 3...

Cognitive Trait Modelling: The Case of Inductive Reasoning Ability

Science.gov (United States)

Kinshuk, Taiyu Lin; McNab, Paul

2006-01-01

Researchers have regarded inductive reasoning as one of the seven primary mental abilities that account for human intelligent behaviours. Researchers have also shown that inductive reasoning ability is one of the best predictors for academic performance. Modelling of inductive reasoning is therefore an important issue for providing adaptivity in…

Case based reasoning applied to medical diagnosis using multi-class classifier: A preliminary study

Directory of Open Access Journals (Sweden)

D. Viveros-Melo

2017-02-01

Full Text Available Case-based reasoning (CBR is a process used for computer processing that tries to mimic the behavior of a human expert in making decisions regarding a subject and learn from the experience of past cases. CBR has demonstrated to be appropriate for working with unstructured domains data or difficult knowledge acquisition situations, such as medical diagnosis, where it is possible to identify diseases such as: cancer diagnosis, epilepsy prediction and appendicitis diagnosis. Some of the trends that may be developed for CBR in the health science are oriented to reduce the number of features in highly dimensional data. An important contribution may be the estimation of probabilities of belonging to each class for new cases. In this paper, in order to adequately represent the database and to avoid the inconveniences caused by the high dimensionality, noise and redundancy, a number of algorithms are used in the preprocessing stage for performing both variable selection and dimension reduction procedures. Also, a comparison of the performance of some representative multi-class classifiers is carried out to identify the most effective one to include within a CBR scheme. Particularly, four classification techniques and two reduction techniques are employed to make a comparative study of multiclass classifiers on CBR

Monitoring progression of clinical reasoning skills during health sciences education using the case method - a qualitative observational study.

Science.gov (United States)

Orban, Kristina; Ekelin, Maria; Edgren, Gudrun; Sandgren, Olof; Hovbrandt, Pia; Persson, Eva K

2017-09-11

Outcome- or competency-based education is well established in medical and health sciences education. Curricula are based on courses where students develop their competences and assessment is also usually course-based. Clinical reasoning is an important competence, and the aim of this study was to monitor and describe students' progression in professional clinical reasoning skills during health sciences education using observations of group discussions following the case method. In this qualitative study students from three different health education programmes were observed while discussing clinical cases in a modified Harvard case method session. A rubric with four dimensions - problem-solving process, disciplinary knowledge, character of discussion and communication - was used as an observational tool to identify clinical reasoning. A deductive content analysis was performed. The results revealed the students' transition over time from reasoning based strictly on theoretical knowledge to reasoning ability characterized by clinical considerations and experiences. Students who were approaching the end of their education immediately identified the most important problem and then focused on this in their discussion. Practice knowledge increased over time, which was seen as progression in the use of professional language, concepts, terms and the use of prior clinical experience. The character of the discussion evolved from theoretical considerations early in the education to clinical reasoning in later years. Communication within the groups was supportive and conducted with a professional tone. Our observations revealed progression in several aspects of students' clinical reasoning skills on a group level in their discussions of clinical cases. We suggest that the case method can be a useful tool in assessing quality in health sciences education.

It's not all about moral reasoning: Understanding the content of Moral Case Deliberation.

Science.gov (United States)

Svantesson, Mia; Silén, Marit; James, Inger

2018-03-01

Moral Case Deliberation is one form of clinical ethics support described as a facilitator-led collective moral reasoning by healthcare professionals on a concrete moral question connected to their practice. Evaluation research is needed, but, as human interaction is difficult to standardise, there is a need to capture the content beyond moral reasoning. This allows for a better understanding of Moral Case Deliberation, which may contribute to further development of valid outcome criteria and stimulate the normative discussion of what Moral Case Deliberation should contain. To explore and compare the content beyond moral reasoning in the dialogue in Moral Case Deliberation at Swedish workplaces. A mixed-methods approach was applied for analysing audio-recordings of 70 periodic Moral Case Deliberation meetings at 10 Swedish workplaces. Moral Case Deliberation facilitators and various healthcare professions participated, with registered nurses comprising the majority. Ethical considerations: No objection to the study was made by an Ethical Review Board. After oral and written information was provided, consent to be recorded was assumed by virtue of participation. Other than 'moral reasoning' (median (md): 45% of the spoken time), the Moral Case Deliberations consisted of 'reflections on the psychosocial work environment' to a varying extent (md: 29%). Additional content comprised 'assumptions about the patient's psychosocial situation' (md: 6%), 'facts about the patient's situation' (md: 5%), 'concrete problem-solving' (md: 6%) and 'process' (md: 3%). The findings suggest that a restorative function of staff's wellbeing in Moral Case Deliberation is needed, as this might contribute to good patient care. This supports outcome criteria of improved emotional support, which may include relief of moral distress. However, facilitators need a strategy for how to proceed from the participants' own emotional needs and to develop the use of their emotional knowing to focus on

Screening of pollution control and clean-up materials for river chemical spills using the multiple case-based reasoning method with a difference-driven revision strategy.

Science.gov (United States)

Liu, Rentao; Jiang, Jiping; Guo, Liang; Shi, Bin; Liu, Jie; Du, Zhaolin; Wang, Peng

2016-06-01

In-depth filtering of emergency disposal technology (EDT) and materials has been required in the process of environmental pollution emergency disposal. However, an urgent problem that must be solved is how to quickly and accurately select the most appropriate materials for treating a pollution event from the existing spill control and clean-up materials (SCCM). To meet this need, the following objectives were addressed in this study. First, the material base and a case base for environment pollution emergency disposal were established to build a foundation and provide material for SCCM screening. Second, the multiple case-based reasoning model method with a difference-driven revision strategy (DDRS-MCBR) was applied to improve the original dual case-based reasoning model method system, and screening and decision-making was performed for SCCM using this model. Third, an actual environmental pollution accident from 2012 was used as a case study to verify the material base, case base, and screening model. The results demonstrated that the DDRS-MCBR method was fast, efficient, and practical. The DDRS-MCBR method changes the passive situation in which the choice of SCCM screening depends only on the subjective experience of the decision maker and offers a new approach to screening SCCM.

DALI - drilling advisor with logic interpretations: methodological issues for designing underbalanced drilling operations. Improving efficiency using case-based reasonic

Energy Technology Data Exchange (ETDEWEB)

Santana, Gustavo A.; Velazquez C, David [Mexican Oil Institute, Mexico DF (Mexico)

2004-07-01

A system that applies a method of knowledge-intensive case-based reasoning, for repair and prevention of unwanted events in the domain of offshore oil well drilling, has been developed in cooperation with an oil company. From several reoccurring problems during oil well drilling the problem of 'lost circulation', i.e. loss of circulating drilling fluid into the geological formation, was picked out as a pilot problem. An extensive general knowledge model was developed for the domain of oil well drilling. Different cases were created on the basis of information from one Mexican Gulf operator. When the completed CBR-system was tested against a new case, cases with descending similarity were selected by the tool. In an informal evaluation, the two best fitting cases proved to give the operator valuable advise on how to go about solving the new case (author)

Emotional reasoning and parent-based reasoning in normal children.

OpenAIRE

Morren, M.; Muris, P.; Kindt, M.

2004-01-01

A previous study by Muris, Merckelbach, and Van Spauwen demonstrated that children display emotional reasoning irrepective of their anxiety levels. That is when estimating whether a situation is dangerous, childen not only rely on objective danger information but also on their own anciety-response. The present study further examined emotional reasoning in childeren aged 7-13 years (N=508). In addition, it was investigated whether children also show parent-based reasoning, which can be defined...

Using Computer Simulations for Promoting Model-based Reasoning. Epistemological and Educational Dimensions

Science.gov (United States)

Develaki, Maria

2017-11-01

Scientific reasoning is particularly pertinent to science education since it is closely related to the content and methodologies of science and contributes to scientific literacy. Much of the research in science education investigates the appropriate framework and teaching methods and tools needed to promote students' ability to reason and evaluate in a scientific way. This paper aims (a) to contribute to an extended understanding of the nature and pedagogical importance of model-based reasoning and (b) to exemplify how using computer simulations can support students' model-based reasoning. We provide first a background for both scientific reasoning and computer simulations, based on the relevant philosophical views and the related educational discussion. This background suggests that the model-based framework provides an epistemologically valid and pedagogically appropriate basis for teaching scientific reasoning and for helping students develop sounder reasoning and decision-taking abilities and explains how using computer simulations can foster these abilities. We then provide some examples illustrating the use of computer simulations to support model-based reasoning and evaluation activities in the classroom. The examples reflect the procedure and criteria for evaluating models in science and demonstrate the educational advantages of their application in classroom reasoning activities.

MANAGEMENT OF A GUILLAIN BARRE SYNDROME PATIENT THROUGH THREE TRACK REASONING: A CASE STUDY

Directory of Open Access Journals (Sweden)

Shamima Islam Nipa

2015-12-01

Full Text Available Background: Clinical reasoning is a thinking and decision making process which occur in clinical practice. It helps the health care providers to solve the clinical problem by using their reasoning process in an effective and efficient manner. Three track reasoning in one of the clinical reasoning process which includes the procedural, interactive and conditional reasoning to diagnose as well as ensure proper rehabilitation service according to patient and patient’s family members’ needs. Methods: A single case based study through the three track reasoning process. The purpose of this study was to explore the management strategies of a Gullian Barrie Syndrome (GBS patient through three track reasoning. We have tried to show how the basic idea behind the reasoning process helped to determine the reasoning process and diagnosis. However it has performed through theory and observation. We have also showed how we used the reasoning process through with the common sense reasoning. However it was the part of procedural reasoning in three track clinical reasoning. In three track reasoning, there is also interactive and procedural reasoning part through which we told patient story about his condition, identified his and his family members expectations and to establish hypothesis as GBS. So three track reasoning also supported us to do reasoning process rather than selecting another reasoning process. Results: After analyzing the reasoning process it was identified that to be strict in a single reasoning process is very difficult. Clinical reasoning is the clinician’s ability through which they can consider the interpretation of different clinical findings. An expert clinician must have critical thinking skill rather than ignoring any symptoms or overemphasize the symptoms. In addition, patient’s knowledge, believes and reasoning was found an important part of clinical reasoning process in this study. Conclusion: We have been practicing clinical

Rule-Based Reasoning Is Fast and Belief-Based Reasoning Can Be Slow: Challenging Current Explanations of Belief-Bias and Base-Rate Neglect

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Newman, Ian R.; Gibb, Maia; Thompson, Valerie A.

2017-01-01

It is commonly assumed that belief-based reasoning is fast and automatic, whereas rule-based reasoning is slower and more effortful. Dual-Process theories of reasoning rely on this speed-asymmetry explanation to account for a number of reasoning phenomena, such as base-rate neglect and belief-bias. The goal of the current study was to test this…

Intertwining evidence- and model-based reasoning in physics sensemaking: An example from electrostatics

Science.gov (United States)

Russ, Rosemary S.; Odden, Tor Ole B.

2017-12-01

Our field has long valued the goal of teaching students not just the facts of physics, but also the thinking and reasoning skills of professional physicists. The complexity inherent in scientific reasoning demands that we think carefully about how we conceptualize for ourselves, enact in our classes, and encourage in our students the relationship between the multifaceted practices of professional science. The current study draws on existing research in the philosophy of science and psychology to advocate for intertwining two important aspects of scientific reasoning: using evidence from experimentation and modeling. We present a case from an undergraduate physics course to illustrate how these aspects can be intertwined productively and describe specific ways in which these aspects of reasoning can mutually reinforce one another in student learning. We end by discussing implications for this work for instruction in introductory physics courses and for research on scientific reasoning at the undergraduate level.

A Framework of Combining Case-Based Reasoning with a Work Breakdown Structure for Estimating the Cost of Online Course Production Projects

Science.gov (United States)

He, Wu

2014-01-01

Currently, a work breakdown structure (WBS) approach is used as the most common cost estimation approach for online course production projects. To improve the practice of cost estimation, this paper proposes a novel framework to estimate the cost for online course production projects using a case-based reasoning (CBR) technique and a WBS. A…

Objectivist case study research

DEFF Research Database (Denmark)

Ridder, Hanne Mette Ochsner; Fachner, Jörg

2016-01-01

be achieved through the use of objectivist case study research. The strength of the case study design is that it allows for uncovering or suggesting causal relationships in real-life settings through an intensive and rich collection of data. According to Hilliard (1993), the opposite applies for extensive......In order to comprehend the impact of music therapy or music therapy processes, a researcher might look for an approach where the topic under investigation can be understood within a broader context. This calls for a rich inclusion of data and consequently a limited number of participants and may...... designs, in which a small amount of data is gathered on a large number of subjects. With the richness of data, the intensive design is ―the primary pragmatic reason for engaging in single-case or small N research‖ (p. 374) and for working from an idiographic rather than a nomothetic perspective....

Promoting student case creation to enhance instruction of clinical reasoning skills: a pilot feasibility study.

Science.gov (United States)

Chandrasekar, Hamsika; Gesundheit, Neil; Nevins, Andrew B; Pompei, Peter; Bruce, Janine; Merrell, Sylvia Bereknyei

2018-01-01

It is a common educational practice for medical students to engage in case-based learning (CBL) exercises by working through clinical cases that have been developed by faculty. While such faculty-developed exercises have educational strengths, there are at least two major drawbacks to learning by this method: the number and diversity of cases is often limited; and students decrease their engagement with CBL cases as they grow accustomed to the teaching method. We sought to explore whether student case creation can address both of these limitations. We also compared student case creation to traditional clinical reasoning sessions in regard to tutorial group effectiveness, perceived gains in clinical reasoning, and quality of student-faculty interaction. Ten first-year medical students participated in a feasibility study wherein they worked in small groups to develop their own patient case around a preassigned diagnosis. Faculty provided feedback on case quality afterwards. Students completed pre- and post-self-assessment surveys. Students and faculty also participated in separate focus groups to compare their case creation experience to traditional CBL sessions. Students reported high levels of team engagement and peer learning, as well as increased ownership over case content and understanding of clinical reasoning nuances. However, students also reported decreases in student-faculty interaction and the use of visual aids ( P study suggest that student-generated cases can be a valuable adjunct to traditional clinical reasoning instruction by increasing content ownership, encouraging student-directed learning, and providing opportunities to explore clinical nuances. However, these gains may reduce student-faculty interaction. Future studies may be able to identify an improved model of faculty participation, the ideal timing for incorporation of this method in a medical curriculum, and a more rigorous assessment of the impact of student case creation on the

Technology-based strategies for promoting clinical reasoning skills in nursing education.

Science.gov (United States)

Shellenbarger, Teresa; Robb, Meigan

2015-01-01

Faculty face the demand of preparing nursing students for the constantly changing health care environment. Effective use of online, classroom, and clinical conferencing opportunities helps to enhance nursing students' clinical reasoning capabilities needed for practice. The growth of technology creates an avenue for faculty to develop engaging learning opportunities. This article presents technology-based strategies such as electronic concept mapping, electronic case histories, and digital storytelling that can be used to facilitate clinical reasoning skills.

Improving case-based reasoning systems by combining k-nearest neighbour algorithm with logistic regression in the prediction of patients' registration on the renal transplant waiting list.

Directory of Open Access Journals (Sweden)

Boris Campillo-Gimenez

Full Text Available Case-based reasoning (CBR is an emerging decision making paradigm in medical research where new cases are solved relying on previously solved similar cases. Usually, a database of solved cases is provided, and every case is described through a set of attributes (inputs and a label (output. Extracting useful information from this database can help the CBR system providing more reliable results on the yet to be solved cases.We suggest a general framework where a CBR system, viz. K-Nearest Neighbour (K-NN algorithm, is combined with various information obtained from a Logistic Regression (LR model, in order to improve prediction of access to the transplant waiting list.LR is applied, on the case database, to assign weights to the attributes as well as the solved cases. Thus, five possible decision making systems based on K-NN and/or LR were identified: a standalone K-NN, a standalone LR and three soft K-NN algorithms that rely on the weights based on the results of the LR. The evaluation was performed under two conditions, either using predictive factors known to be related to registration, or using a combination of factors related and not related to registration.The results show that our suggested approach, where the K-NN algorithm relies on both weighted attributes and cases, can efficiently deal with non relevant attributes, whereas the four other approaches suffer from this kind of noisy setups. The robustness of this approach suggests interesting perspectives for medical problem solving tools using CBR methodology.

Risk Factors Analysis and Death Prediction in Some Life-Threatening Ailments Using Chi-Square Case-Based Reasoning (χ2 CBR) Model.

Science.gov (United States)

Adeniyi, D A; Wei, Z; Yang, Y

2018-01-30

A wealth of data are available within the health care system, however, effective analysis tools for exploring the hidden patterns in these datasets are lacking. To alleviate this limitation, this paper proposes a simple but promising hybrid predictive model by suitably combining the Chi-square distance measurement with case-based reasoning technique. The study presents the realization of an automated risk calculator and death prediction in some life-threatening ailments using Chi-square case-based reasoning (χ 2 CBR) model. The proposed predictive engine is capable of reducing runtime and speeds up execution process through the use of critical χ 2 distribution value. This work also showcases the development of a novel feature selection method referred to as frequent item based rule (FIBR) method. This FIBR method is used for selecting the best feature for the proposed χ 2 CBR model at the preprocessing stage of the predictive procedures. The implementation of the proposed risk calculator is achieved through the use of an in-house developed PHP program experimented with XAMP/Apache HTTP server as hosting server. The process of data acquisition and case-based development is implemented using the MySQL application. Performance comparison between our system, the NBY, the ED-KNN, the ANN, the SVM, the Random Forest and the traditional CBR techniques shows that the quality of predictions produced by our system outperformed the baseline methods studied. The result of our experiment shows that the precision rate and predictive quality of our system in most cases are equal to or greater than 70%. Our result also shows that the proposed system executes faster than the baseline methods studied. Therefore, the proposed risk calculator is capable of providing useful, consistent, faster, accurate and efficient risk level prediction to both the patients and the physicians at any time, online and on a real-time basis.

Case-Based Reasoning on E-Community Knowledge

OpenAIRE

Gaillard , Emmanuelle; Lieber , Jean; Naudet , Yannick; Nauer , Emmanuel

2013-01-01

International audience; This paper presents MKM, a meta-knowledge model to manage knowledge reliability, in order to extend a CBR system so that it can reason on partially reliable, non expert, knowledge from the Web. Knowledge reliability is considered from the point of view of the decision maker using the CBR system. It is captured by the MKM model including notions such as belief, trust, reputation and quality, as well as their relationships and rules to evaluate knowledge reliability. We ...

Designing Intelligent Tutoring Systems: A Personalization Strategy using Case-Based Reasoning and Multi-Agent Systems

Directory of Open Access Journals (Sweden)

Rosalía LAZA

2013-05-01

Full Text Available Intelligent Tutoring Systems (ITSs are educational systems that use artificial intelligence techniques for representing the knowledge. ITSs design is often criticized for being a complex and challenging process. In this article, we propose a framework for the ITSs design using Case Based Reasoning (CBR and Multiagent systems (MAS. The major advantage of using CBR is to allow the intelligent system to propose smart and quick solutions to problems, even in complex domains, avoiding the time necessary to derive those solutions from scratch. The use of intelligent agents and MAS architectures supports the retrieval of similar students models and the adaptation of teaching strategies according to the student profile. We describe deeply how the combination of both technologies helps to simplify the design of new ITSs and personalize the e-learning process for each student

A research on applications of qualitative reasoning techniques in Human Acts Simulation Program

International Nuclear Information System (INIS)

Far, B.H.

1992-04-01

Human Acts Simulation Program (HASP) is a ten-year research project of the Computing and Information Systems Center of JAERI. In HASP the goal is developing programs for an advanced intelligent robot to accomplish multiple instructions (for instance, related to surveillance, inspection and maintenance) in nuclear power plants. Some recent artificial intelligence techniques can contribute to this project. This report introduces some original contributions concerning application of Qualitative Reasoning (QR) techniques in HASP. The focus is on the knowledge-intensive tasks, including model-based reasoning, analytic learning, fault diagnosis and functional reasoning. The multi-level extended qualitative modeling for the Skill-Rule-Knowledge (S-R-K) based reasoning, that included the coordination and timing of events, Qualitative Sensitivity analysis (Q S A), Subjective Qualitative Fault Diagnosis (S Q F D) and Qualitative Function Formation (Q F F ) techniques are introduced. (author) 123 refs

Reciprocity-based reasons for benefiting research participants: most fail, the most plausible is problematic.

Science.gov (United States)

Sofaer, Neema

2014-11-01

A common reason for giving research participants post-trial access (PTA) to the trial intervention appeals to reciprocity, the principle, stated most generally, that if one person benefits a second, the second should reciprocate: benefit the first in return. Many authors consider it obvious that reciprocity supports PTA. Yet their reciprocity principles differ, with many authors apparently unaware of alternative versions. This article is the first to gather the range of reciprocity principles. It finds that: (1) most are false. (2) The most plausible principle, which is also problematic, applies only when participants experience significant net risks or burdens. (3) Seldom does reciprocity support PTA for participants or give researchers stronger reason to benefit participants than equally needy non-participants. (4) Reciprocity fails to explain the common view that it is bad when participants in a successful trial have benefited from the trial intervention but lack PTA to it. © 2013 John Wiley & Sons Ltd.

Single-Case Research Design: An Alternative Strategy for Evidence-Based Practice

Science.gov (United States)

Stapleton, Drue; Hawkins, Andrew

2015-01-01

Objective: The trend of utilizing evidence-based practice (EBP) in athletic training is now requiring clinicians, researchers, educators, and students to be equipped to both engage in and make judgments about research evidence. Single-case design (SCD) research may provide an alternative approach to develop such skills and inform clinical and…

The clustering-based case-based reasoning for imbalanced business failure prediction: a hybrid approach through integrating unsupervised process with supervised process

Science.gov (United States)

Li, Hui; Yu, Jun-Ling; Yu, Le-An; Sun, Jie

2014-05-01

Case-based reasoning (CBR) is one of the main forecasting methods in business forecasting, which performs well in prediction and holds the ability of giving explanations for the results. In business failure prediction (BFP), the number of failed enterprises is relatively small, compared with the number of non-failed ones. However, the loss is huge when an enterprise fails. Therefore, it is necessary to develop methods (trained on imbalanced samples) which forecast well for this small proportion of failed enterprises and performs accurately on total accuracy meanwhile. Commonly used methods constructed on the assumption of balanced samples do not perform well in predicting minority samples on imbalanced samples consisting of the minority/failed enterprises and the majority/non-failed ones. This article develops a new method called clustering-based CBR (CBCBR), which integrates clustering analysis, an unsupervised process, with CBR, a supervised process, to enhance the efficiency of retrieving information from both minority and majority in CBR. In CBCBR, various case classes are firstly generated through hierarchical clustering inside stored experienced cases, and class centres are calculated out by integrating cases information in the same clustered class. When predicting the label of a target case, its nearest clustered case class is firstly retrieved by ranking similarities between the target case and each clustered case class centre. Then, nearest neighbours of the target case in the determined clustered case class are retrieved. Finally, labels of the nearest experienced cases are used in prediction. In the empirical experiment with two imbalanced samples from China, the performance of CBCBR was compared with the classical CBR, a support vector machine, a logistic regression and a multi-variant discriminate analysis. The results show that compared with the other four methods, CBCBR performed significantly better in terms of sensitivity for identifying the

Promoting student case creation to enhance instruction of clinical reasoning skills: a pilot feasibility study

Directory of Open Access Journals (Sweden)

Chandrasekar H

2018-04-01

Full Text Available Hamsika Chandrasekar,1 Neil Gesundheit,2 Andrew B Nevins,3 Peter Pompei,4 Janine Bruce,5 Sylvia Bereknyei Merrell6 1Department of Pediatrics, Boston Children’s Hospital, Boston, MA, USA; 2Department of Medicine, Division of Endocrinology, Stanford University School of Medicine, Stanford, CA, USA; 3Department of Medicine, Division of Infectious Diseases, Stanford University School of Medicine, Stanford, CA, USA; 4Department of Medicine, Division of Primary Care and Population Health, Stanford University School of Medicine, Stanford, CA, USA; 5Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA; 6Department of Surgery, Stanford University School of Medicine, Stanford, CA, USA Background: It is a common educational practice for medical students to engage in case-based learning (CBL exercises by working through clinical cases that have been developed by faculty. While such faculty-developed exercises have educational strengths, there are at least two major drawbacks to learning by this method: the number and diversity of cases is often limited; and students decrease their engagement with CBL cases as they grow accustomed to the teaching method. We sought to explore whether student case creation can address both of these limitations. We also compared student case creation to traditional clinical reasoning sessions in regard to tutorial group effectiveness, perceived gains in clinical reasoning, and quality of student–faculty interaction. Methods: Ten first-year medical students participated in a feasibility study wherein they worked in small groups to develop their own patient case around a preassigned diagnosis. Faculty provided feedback on case quality afterwards. Students completed pre- and post-self-assessment surveys. Students and faculty also participated in separate focus groups to compare their case creation experience to traditional CBL sessions. Results: Students reported high levels of team engagement

Dynamic reasoning in a knowledge-based system

Science.gov (United States)

Rao, Anand S.; Foo, Norman Y.

1988-01-01

Any space based system, whether it is a robot arm assembling parts in space or an onboard system monitoring the space station, has to react to changes which cannot be foreseen. As a result, apart from having domain-specific knowledge as in current expert systems, a space based AI system should also have general principles of change. This paper presents a modal logic which can not only represent change but also reason with it. Three primitive operations, expansion, contraction and revision are introduced and axioms which specify how the knowledge base should change when the external world changes are also specified. Accordingly the notion of dynamic reasoning is introduced, which unlike the existing forms of reasoning, provide general principles of change. Dynamic reasoning is based on two main principles, namely minimize change and maximize coherence. A possible-world semantics which incorporates the above two principles is also discussed. The paper concludes by discussing how the dynamic reasoning system can be used to specify actions and hence form an integral part of an autonomous reasoning and planning system.

A robot sets a table: a case for hybrid reasoning with different types of knowledge

Science.gov (United States)

Mansouri, Masoumeh; Pecora, Federico

2016-09-01

An important contribution of AI to Robotics is the model-centred approach, whereby competent robot behaviour stems from automated reasoning in models of the world which can be changed to suit different environments, physical capabilities and tasks. However models need to capture diverse (and often application-dependent) aspects of the robot's environment and capabilities. They must also have good computational properties, as robots need to reason while they act in response to perceived context. In this article, we investigate the use of a meta-CSP-based technique to interleave reasoning in diverse knowledge types. We reify the approach through a robotic waiter case study, for which a particular selection of spatial, temporal, resource and action KR formalisms is made. Using this case study, we discuss general principles pertaining to the selection of appropriate KR formalisms and jointly reasoning about them. The resulting integration is evaluated both formally and experimentally on real and simulated robotic platforms.

Development of abstract mathematical reasoning: the case of algebra.

Science.gov (United States)

Susac, Ana; Bubic, Andreja; Vrbanc, Andrija; Planinic, Maja

2014-01-01

Algebra typically represents the students' first encounter with abstract mathematical reasoning and it therefore causes significant difficulties for students who still reason concretely. The aim of the present study was to investigate the developmental trajectory of the students' ability to solve simple algebraic equations. 311 participants between the ages of 13 and 17 were given a computerized test of equation rearrangement. Equations consisted of an unknown and two other elements (numbers or letters), and the operations of multiplication/division. The obtained results showed that younger participants are less accurate and slower in solving equations with letters (symbols) than those with numbers. This difference disappeared for older participants (16-17 years), suggesting that they had reached an abstract reasoning level, at least for this simple task. A corresponding conclusion arises from the analysis of their strategies which suggests that younger participants mostly used concrete strategies such as inserting numbers, while older participants typically used more abstract, rule-based strategies. These results indicate that the development of algebraic thinking is a process which unfolds over a long period of time. In agreement with previous research, we can conclude that, on average, children at the age of 15-16 transition from using concrete to abstract strategies while solving the algebra problems addressed within the present study. A better understanding of the timing and speed of students' transition from concrete arithmetic reasoning to abstract algebraic reasoning might help in designing better curricula and teaching materials that would ease that transition.

Evidential reasoning research on intrusion detection

Science.gov (United States)

Wang, Xianpei; Xu, Hua; Zheng, Sheng; Cheng, Anyu

2003-09-01

In this paper, we mainly aim at D-S theory of evidence and the network intrusion detection these two fields. It discusses the method how to apply this probable reasoning as an AI technology to the Intrusion Detection System (IDS). This paper establishes the application model, describes the new mechanism of reasoning and decision-making and analyses how to implement the model based on the synscan activities detection on the network. The results suggest that if only rational probability values were assigned at the beginning, the engine can, according to the rules of evidence combination and hierarchical reasoning, compute the values of belief and finally inform the administrators of the qualities of the traced activities -- intrusions, normal activities or abnormal activities.

Scientific Reasoning and Argumentation: Advancing an Interdisciplinary Research Agenda in Education

Science.gov (United States)

Fischer, Frank; Kollar, Ingo; Ufer, Stefan; Sodian, Beate; Hussmann, Heinrich; Pekrun, Reinhard; Neuhaus, Birgit; Dorner, Birgit; Pankofer, Sabine; Fischer, Martin; Strijbos, Jan-Willem; Heene, Moritz; Eberle, Julia

2014-01-01

Scientific reasoning and scientific argumentation are highly valued outcomes of K-12 and higher education. In this article, we first review main topics and key findings of three different strands of research, namely research on the development of scientific reasoning, research on scientific argumentation, and research on approaches to support…

Computational approaches to analogical reasoning current trends

CERN Document Server

Richard, Gilles

2014-01-01

Analogical reasoning is known as a powerful mode for drawing plausible conclusions and solving problems. It has been the topic of a huge number of works by philosophers, anthropologists, linguists, psychologists, and computer scientists. As such, it has been early studied in artificial intelligence, with a particular renewal of interest in the last decade. The present volume provides a structured view of current research trends on computational approaches to analogical reasoning. It starts with an overview of the field, with an extensive bibliography. The 14 collected contributions cover a large scope of issues. First, the use of analogical proportions and analogies is explained and discussed in various natural language processing problems, as well as in automated deduction. Then, different formal frameworks for handling analogies are presented, dealing with case-based reasoning, heuristic-driven theory projection, commonsense reasoning about incomplete rule bases, logical proportions induced by similarity an...

Solving probability reasoning based on DNA strand displacement and probability modules.

Science.gov (United States)

Zhang, Qiang; Wang, Xiaobiao; Wang, Xiaojun; Zhou, Changjun

2017-12-01

In computation biology, DNA strand displacement technology is used to simulate the computation process and has shown strong computing ability. Most researchers use it to solve logic problems, but it is only rarely used in probabilistic reasoning. To process probabilistic reasoning, a conditional probability derivation model and total probability model based on DNA strand displacement were established in this paper. The models were assessed through the game "read your mind." It has been shown to enable the application of probabilistic reasoning in genetic diagnosis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Continuity and change in the development of category-based induction: The test case of diversity-based reasoning.

Science.gov (United States)

Rhodes, Marjorie; Liebenson, Peter

2015-11-01

The present research examined the extent to which the cognitive mechanisms available to support inductive inference stay constant across development or undergo fundamental change. Four studies tested how children (ages 5-10) incorporate information about sample composition into their category-based generalizations. Children's use of sample composition varied across age and type of category. For familiar natural kinds, children ages 5-8 generalized similarly from diverse and non-diverse samples of evidence, whereas older children generalized more broadly from more diverse sets. In contrast, for novel categories, children of each age made broader generalizations from diverse than non-diverse samples. These studies provide the first clear evidence that young children are able to incorporate sample diversity into their inductive reasoning. These findings suggest developmental continuity in the cognitive mechanisms available for inductive inference, but developmental changes in the role that prior knowledge plays in shaping these processes. Copyright © 2015 Elsevier Inc. All rights reserved.

Investigating Students' Reasoning about Acid-Base Reactions

Science.gov (United States)

Cooper, Melanie M.; Kouyoumdjian, Hovig; Underwood, Sonia M.

2016-01-01

Acid-base chemistry is central to a wide range of reactions. If students are able to understand how and why acid-base reactions occur, it should provide a basis for reasoning about a host of other reactions. Here, we report the development of a method to characterize student reasoning about acid-base reactions based on their description of…

Neural Correlates of Post-Conventional Moral Reasoning: A Voxel-Based Morphometry Study

Science.gov (United States)

Prehn, Kristin; Korczykowski, Marc; Rao, Hengyi; Fang, Zhuo; Detre, John A.; Robertson, Diana C.

2015-01-01

Going back to Kohlberg, moral development research affirms that people progress through different stages of moral reasoning as cognitive abilities mature. Individuals at a lower level of moral reasoning judge moral issues mainly based on self-interest (personal interests schema) or based on adherence to laws and rules (maintaining norms schema), whereas individuals at the post-conventional level judge moral issues based on deeper principles and shared ideals. However, the extent to which moral development is reflected in structural brain architecture remains unknown. To investigate this question, we used voxel-based morphometry and examined the brain structure in a sample of 67 Master of Business Administration (MBA) students. Subjects completed the Defining Issues Test (DIT-2) which measures moral development in terms of cognitive schema preference. Results demonstrate that subjects at the post-conventional level of moral reasoning were characterized by increased gray matter volume in the ventromedial prefrontal cortex and subgenual anterior cingulate cortex, compared with subjects at a lower level of moral reasoning. Our findings support an important role for both cognitive and emotional processes in moral reasoning and provide first evidence for individual differences in brain structure according to the stages of moral reasoning first proposed by Kohlberg decades ago. PMID:26039547

Neural correlates of post-conventional moral reasoning: a voxel-based morphometry study.

Directory of Open Access Journals (Sweden)

Kristin Prehn

Full Text Available Going back to Kohlberg, moral development research affirms that people progress through different stages of moral reasoning as cognitive abilities mature. Individuals at a lower level of moral reasoning judge moral issues mainly based on self-interest (personal interests schema or based on adherence to laws and rules (maintaining norms schema, whereas individuals at the post-conventional level judge moral issues based on deeper principles and shared ideals. However, the extent to which moral development is reflected in structural brain architecture remains unknown. To investigate this question, we used voxel-based morphometry and examined the brain structure in a sample of 67 Master of Business Administration (MBA students. Subjects completed the Defining Issues Test (DIT-2 which measures moral development in terms of cognitive schema preference. Results demonstrate that subjects at the post-conventional level of moral reasoning were characterized by increased gray matter volume in the ventromedial prefrontal cortex and subgenual anterior cingulate cortex, compared with subjects at a lower level of moral reasoning. Our findings support an important role for both cognitive and emotional processes in moral reasoning and provide first evidence for individual differences in brain structure according to the stages of moral reasoning first proposed by Kohlberg decades ago.

Neural correlates of post-conventional moral reasoning: a voxel-based morphometry study.

Science.gov (United States)

Prehn, Kristin; Korczykowski, Marc; Rao, Hengyi; Fang, Zhuo; Detre, John A; Robertson, Diana C

2015-01-01

Going back to Kohlberg, moral development research affirms that people progress through different stages of moral reasoning as cognitive abilities mature. Individuals at a lower level of moral reasoning judge moral issues mainly based on self-interest (personal interests schema) or based on adherence to laws and rules (maintaining norms schema), whereas individuals at the post-conventional level judge moral issues based on deeper principles and shared ideals. However, the extent to which moral development is reflected in structural brain architecture remains unknown. To investigate this question, we used voxel-based morphometry and examined the brain structure in a sample of 67 Master of Business Administration (MBA) students. Subjects completed the Defining Issues Test (DIT-2) which measures moral development in terms of cognitive schema preference. Results demonstrate that subjects at the post-conventional level of moral reasoning were characterized by increased gray matter volume in the ventromedial prefrontal cortex and subgenual anterior cingulate cortex, compared with subjects at a lower level of moral reasoning. Our findings support an important role for both cognitive and emotional processes in moral reasoning and provide first evidence for individual differences in brain structure according to the stages of moral reasoning first proposed by Kohlberg decades ago.

Catching the Drift : Using Feature-Free Case-Based Reasoning for Spam Filtering.

OpenAIRE

Delany, Sarah Jane; Bridge, Derek

2007-01-01

n this paper, we compare case-based spam filters, focusing on their resilience to concept drift. In particular, we evaluate how to track concept drift using a case-based spam filter that uses a feature-free distance measure based on text compression. In our experiments, we compare two ways to normalise such a distance measure, finding that the one proposed in [1] performs better. We show that a policy as simple as retaining misclassified examples has a hugely beneficial effect on handling con...

Development of Reasoning Test Instruments Based on TIMSS Framework for Measuring Reasoning Ability of Senior High School Student on the Physics Concept

Science.gov (United States)

Muslim; Suhandi, A.; Nugraha, M. G.

2017-02-01

The purposes of this study are to determine the quality of reasoning test instruments that follow the framework of Trends in International Mathematics and Science Study (TIMSS) as a development results and to analyse the profile of reasoning skill of senior high school students on physics materials. This research used research and development method (R&D), furthermore the subject were 104 students at three senior high schools in Bandung selected by random sampling technique. Reasoning test instruments are constructed following the TIMSS framework in multiple choice forms in 30 questions that cover five subject matters i.e. parabolic motion and circular motion, Newton’s law of gravity, work and energy, harmonic oscillation, as well as the momentum and impulse. The quality of reasoning tests were analysed using the Content Validity Ratio (CVR) and classic test analysis include the validity of item, level of difficulty, discriminating power, reliability and Ferguson’s delta. As for the students’ reasoning skills profiles were analysed by the average score of achievements on eight aspects of the reasoning TIMSS framework. The results showed that reasoning test have a good quality as instruments to measure reasoning skills of senior high school students on five matters physics which developed and able to explore the reasoning of students on all aspects of reasoning based on TIMSS framework.

Improving the learning of clinical reasoning through computer-based cognitive representation.

Science.gov (United States)

Wu, Bian; Wang, Minhong; Johnson, Janice M; Grotzer, Tina A

2014-01-01

Clinical reasoning is usually taught using a problem-solving approach, which is widely adopted in medical education. However, learning through problem solving is difficult as a result of the contextualization and dynamic aspects of actual problems. Moreover, knowledge acquired from problem-solving practice tends to be inert and fragmented. This study proposed a computer-based cognitive representation approach that externalizes and facilitates the complex processes in learning clinical reasoning. The approach is operationalized in a computer-based cognitive representation tool that involves argument mapping to externalize the problem-solving process and concept mapping to reveal the knowledge constructed from the problems. Twenty-nine Year 3 or higher students from a medical school in east China participated in the study. Participants used the proposed approach implemented in an e-learning system to complete four learning cases in 4 weeks on an individual basis. For each case, students interacted with the problem to capture critical data, generate and justify hypotheses, make a diagnosis, recall relevant knowledge, and update their conceptual understanding of the problem domain. Meanwhile, students used the computer-based cognitive representation tool to articulate and represent the key elements and their interactions in the learning process. A significant improvement was found in students' learning products from the beginning to the end of the study, consistent with students' report of close-to-moderate progress in developing problem-solving and knowledge-construction abilities. No significant differences were found between the pretest and posttest scores with the 4-week period. The cognitive representation approach was found to provide more formative assessment. The computer-based cognitive representation approach improved the learning of clinical reasoning in both problem solving and knowledge construction.

Research of Uncertainty Reasoning in Pineapple Disease Identification System

Science.gov (United States)

Liu, Liqun; Fan, Haifeng

In order to deal with the uncertainty of evidences mostly existing in pineapple disease identification system, a reasoning model based on evidence credibility factor was established. The uncertainty reasoning method is discussed,including: uncertain representation of knowledge, uncertain representation of rules, uncertain representation of multi-evidences and update of reasoning rules. The reasoning can fully reflect the uncertainty in disease identification and reduce the influence of subjective factors on the accuracy of the system.

A Framework for a Clinical Reasoning Knowledge Warehouse

DEFF Research Database (Denmark)

Vilstrup Pedersen, Klaus; Boye, Niels

2004-01-01

is stored and made accessible when relevant to the reasoning context and the specific patient case. Furthermore, the information structure supports the creation of new generalized knowledge using data mining tools. The patient case is divided into an observation level and an opinion level. At the opinion......, Knowledge Management Systems and Business Intelligence to make context based, patient case specific analysis and knowledge management. The knowledge base integrates three sources of information that supports clinical reasoning: general information, guidelines and health records. New generalized knowledge...... level, reasoning participants can express their argument based opinions about a patient case, thereby enhancing the knowledge about the state of and plans for the patient. An opinion language that supports expressing a possible imprecise/uncertain opinion based on imprecise...

A knowledge-based system for prototypical reasoning

Science.gov (United States)

Lieto, Antonio; Minieri, Andrea; Piana, Alberto; Radicioni, Daniele P.

2015-04-01

In this work we present a knowledge-based system equipped with a hybrid, cognitively inspired architecture for the representation of conceptual information. The proposed system aims at extending the classical representational and reasoning capabilities of the ontology-based frameworks towards the realm of the prototype theory. It is based on a hybrid knowledge base, composed of a classical symbolic component (grounded on a formal ontology) with a typicality based one (grounded on the conceptual spaces framework). The resulting system attempts to reconcile the heterogeneous approach to the concepts in Cognitive Science with the dual process theories of reasoning and rationality. The system has been experimentally assessed in a conceptual categorisation task where common sense linguistic descriptions were given in input, and the corresponding target concepts had to be identified. The results show that the proposed solution substantially extends the representational and reasoning 'conceptual' capabilities of standard ontology-based systems.

The intersection between Descriptivism and Meliorism in reasoning research: further proposals in support of 'soft normativism'.

Science.gov (United States)

Stupple, Edward J N; Ball, Linden J

2014-01-01

The rationality paradox centers on the observation that people are highly intelligent, yet show evidence of errors and biases in their thinking when measured against normative standards. Elqayam and Evans' (2011) reject normative standards in the psychological study of thinking, reasoning and deciding in favor of a 'value-free' descriptive approach to studying high-level cognition. In reviewing Elqayam and Evans' (2011) position, we defend an alternative to descriptivism in the form of 'soft normativism,' which allows for normative evaluations alongside the pursuit of descriptive research goals. We propose that normative theories have considerable value provided that researchers: (1) are alert to the philosophical quagmire of strong relativism; (2) are mindful of the biases that can arise from utilizing normative benchmarks; and (3) engage in a focused analysis of the processing approach adopted by individual reasoners. We address the controversial 'is-ought' inference in this context and appeal to a 'bridging solution' to this contested inference that is based on the concept of 'informal reflective equilibrium.' Furthermore, we draw on Elqayam and Evans' (2011) recognition of a role for normative benchmarks in research programs that are devised to enhance reasoning performance and we argue that such Meliorist research programs have a valuable reciprocal relationship with descriptivist accounts of reasoning. In sum, we believe that descriptions of reasoning processes are fundamentally enriched by evaluations of reasoning quality, and argue that if such standards are discarded altogether then our explanations and descriptions of reasoning processes are severely undermined.

Meta-Reasoning: Monitoring and Control of Thinking and Reasoning.

Science.gov (United States)

Ackerman, Rakefet; Thompson, Valerie A

2017-08-01

Meta-Reasoning refers to the processes that monitor the progress of our reasoning and problem-solving activities and regulate the time and effort devoted to them. Monitoring processes are usually experienced as feelings of certainty or uncertainty about how well a process has, or will, unfold. These feelings are based on heuristic cues, which are not necessarily reliable. Nevertheless, we rely on these feelings of (un)certainty to regulate our mental effort. Most metacognitive research has focused on memorization and knowledge retrieval, with little attention paid to more complex processes, such as reasoning and problem solving. In that context, we recently developed a Meta-Reasoning framework, used here to review existing findings, consider their consequences, and frame questions for future research. Copyright © 2017 Elsevier Ltd. All rights reserved.

Case-Based Analogical Reasoning: A Pedagogical Tool for Promotion of Clinical Reasoning

Science.gov (United States)

Speicher, Timothy E.; Bell, Alexandra; Kehrhahn, Marijke; Casa, Douglas J.

2012-01-01

Context: One of the most common instructional methods utilized to promote learning transfer in health profession education is examination of a single patient case. However, in non-healthcare settings this practice has shown to be less effective in promoting learning than the examination of multiple cases with cueing. Objective(s): The primary…

Estimation of the monthly average daily solar radiation using geographic information system and advanced case-based reasoning.

Science.gov (United States)

Koo, Choongwan; Hong, Taehoon; Lee, Minhyun; Park, Hyo Seon

2013-05-07

The photovoltaic (PV) system is considered an unlimited source of clean energy, whose amount of electricity generation changes according to the monthly average daily solar radiation (MADSR). It is revealed that the MADSR distribution in South Korea has very diverse patterns due to the country's climatic and geographical characteristics. This study aimed to develop a MADSR estimation model for the location without the measured MADSR data, using an advanced case based reasoning (CBR) model, which is a hybrid methodology combining CBR with artificial neural network, multiregression analysis, and genetic algorithm. The average prediction accuracy of the advanced CBR model was very high at 95.69%, and the standard deviation of the prediction accuracy was 3.67%, showing a significant improvement in prediction accuracy and consistency. A case study was conducted to verify the proposed model. The proposed model could be useful for owner or construction manager in charge of determining whether or not to introduce the PV system and where to install it. Also, it would benefit contractors in a competitive bidding process to accurately estimate the electricity generation of the PV system in advance and to conduct an economic and environmental feasibility study from the life cycle perspective.

Case Based Asset Maintenance for the Electric Equipment

International Nuclear Information System (INIS)

Kim, Ji-Hyeon; Jung, Jae-Cheon; Chang, Young-Woo; Chang, Hoon-Seon; Kim, Jae-Cheol; Kim, Hang-Bae; Kim, Kyu-Ho; Hur, Yong; Lee, Dong-Chul

2006-01-01

The electric equipment maintenance strategies are changing from PM(Preventive Maintenance) or CM(Corrective Maintenance) to CBM(Condition Based Maintenance). The main benefits of CBM are reduced possibility of service failures of critical equipment and reduced costs or maintenance work. In CBM, the equipment status need to be monitored continuously and a decision should be made whether an equipment need to be repaired or replaced. For the maintenance decision making, the CBR(Case Base Reasoning) system is introduced. The CBR system receives the current equipment status and retrieves the case based historic database to determine any possible equipment failure under current conditions. In retrieving the case based historic data, the suggested DSS(Decision Support System) uses a reasoning engine with an equipment/asset ontology that describes the equipment subsumption relationships

Improving the learning of clinical reasoning through computer-based cognitive representation

Directory of Open Access Journals (Sweden)

Bian Wu

2014-12-01

Full Text Available Objective: Clinical reasoning is usually taught using a problem-solving approach, which is widely adopted in medical education. However, learning through problem solving is difficult as a result of the contextualization and dynamic aspects of actual problems. Moreover, knowledge acquired from problem-solving practice tends to be inert and fragmented. This study proposed a computer-based cognitive representation approach that externalizes and facilitates the complex processes in learning clinical reasoning. The approach is operationalized in a computer-based cognitive representation tool that involves argument mapping to externalize the problem-solving process and concept mapping to reveal the knowledge constructed from the problems. Methods: Twenty-nine Year 3 or higher students from a medical school in east China participated in the study. Participants used the proposed approach implemented in an e-learning system to complete four learning cases in 4 weeks on an individual basis. For each case, students interacted with the problem to capture critical data, generate and justify hypotheses, make a diagnosis, recall relevant knowledge, and update their conceptual understanding of the problem domain. Meanwhile, students used the computer-based cognitive representation tool to articulate and represent the key elements and their interactions in the learning process. Results: A significant improvement was found in students’ learning products from the beginning to the end of the study, consistent with students’ report of close-to-moderate progress in developing problem-solving and knowledge-construction abilities. No significant differences were found between the pretest and posttest scores with the 4-week period. The cognitive representation approach was found to provide more formative assessment. Conclusions: The computer-based cognitive representation approach improved the learning of clinical reasoning in both problem solving and knowledge

Inductive reasoning 2.0.

Science.gov (United States)

Hayes, Brett K; Heit, Evan

2018-05-01

Inductive reasoning entails using existing knowledge to make predictions about novel cases. The first part of this review summarizes key inductive phenomena and critically evaluates theories of induction. We highlight recent theoretical advances, with a special emphasis on the structured statistical approach, the importance of sampling assumptions in Bayesian models, and connectionist modeling. A number of new research directions in this field are identified including comparisons of inductive and deductive reasoning, the identification of common core processes in induction and memory tasks and induction involving category uncertainty. The implications of induction research for areas as diverse as complex decision-making and fear generalization are discussed. This article is categorized under: Psychology > Reasoning and Decision Making Psychology > Learning. © 2017 Wiley Periodicals, Inc.

Measuring Relational Reasoning

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Alexander, Patricia A.; Dumas, Denis; Grossnickle, Emily M.; List, Alexandra; Firetto, Carla M.

2016-01-01

Relational reasoning is the foundational cognitive ability to discern meaningful patterns within an informational stream, but its reliable and valid measurement remains problematic. In this investigation, the measurement of relational reasoning unfolded in three stages. Stage 1 entailed the establishment of a research-based conceptualization of…

MANAGEMENT OF AN ATYPICAL ANKLE SPRAIN PATIENT THROUGH HYPOTHETICO DEDUCTIVE REASONING MODEL OF CLINICAL REASONING IMPLEMENTED BY INTERNATIONAL CLASSIFICATION OF FUNCTIONING DISABILITY AND HEALTH A CASE STUDY

Directory of Open Access Journals (Sweden)

Mohammad Habibur Rahman

2016-09-01

Full Text Available Background: Clinical reasoning is a process by which physiotherapists interacted with patients, their family and other health- care professionals. It is the thinking process that professionals tend to apply in clinical practice. Given that novice as well as expert practitioners prefer to go through some steps while they were dealing with unfamiliar cases. This process is known as hypothetico deductive reasoning. This reasoning approach involved the generation of hypothesis based on clinical data and knowledge and testing of hypothesis through further inquiry. We are expert in musculoskeletal physiotherapy treatment and favoring the atypical history of patient we went through step by step from assessment to discharge Methods: A case based study through hypothetico deductive reasoning model of clinical reasoning. The objective of the study was to investigate the physiotherapy management strategies of an atypical ankle sprain patient through hypothetico deductive reasoning which comprised of cue acquisition, hypothesis generation, cue interpretation and hypothesis evaluation by implementing International Classification of Functioning, Disability and Health (ICF. Results: The patient responded well to treatment as patient reported that 100% swelling decreased, could bear more weight (95% on foot, decrease pain (1 cm on 10 cm VAS scale, improved muscle strength by manual muscle testing by grade V in ankle planter flexors (PF as well as dorsiflexors (DF, invertors as well as evertors and the functional status of patient was improved by 80% according to lower extremity functional scale. Conclusion: Clinical reasoning is an important approach in physiotherapy. It helps the practitioners in decision making and choosing the best alternative options for the well being of patients. We think it is necessary for all practitioners to have sound propositional and non-propositional knowledge in order to provide effective management protocol for patients focusing

Reasons for Whistleblowing: A Qualitative Study

Directory of Open Access Journals (Sweden)

Ali BALTACI

2017-04-01

Full Text Available Whistleblowing has become a commonly encountered concept in recent times. Negative behaviors and actions can be experienced in any organization, and whistleblowing, as a communication process, is a kind of ethical behavior. Whistleblowing is the transmission of an unfavorable situation discovered in the organization to either internal or external authorities. An examination of the reasons for the employee’s whistleblowing is important for a better understanding of this concept; hence, this research focuses on the reasons for whistleblowing. In addition, the reasons for avoiding whistleblowing were also investigated. This research, which is designed as a qualitative study, is based on the phenomenological approach. Interviews were conducted with open-ended, semi-structured interview form in the study. The research was conducted on 20 teachers, 12 administrators, and 7 inspectors. The data were analyzed using the content analysis method. As a result of the research, the individual, organizational and social reasons for whistleblowing have been differentiated. Among the individual reasons for whistleblowing are the considerations of protecting and gaining interests. Organizational reasons include business ethics and the expectation of subsequent promotion. Social reasons encompass social benefits, social justice, and religious belief. Reasons for avoiding whistleblowing vary based on retaliation and worry. This research is considered important because as it is believed to be the first qualitative research to approach the reasons for whistleblowing. The results of this research have revealed gaps in the understanding of this area for future studies.

Research ethics in dissertations: ethical issues and complexity of reasoning.

Science.gov (United States)

Kjellström, S; Ross, S N; Fridlund, B

2010-07-01

Conducting ethically sound research is a fundamental principle of scientific inquiry. Recent research has indicated that ethical concerns are insufficiently dealt with in dissertations. To examine which research ethical topics were addressed and how these were presented in terms of complexity of reasoning in Swedish nurses' dissertations. Analyses of ethical content and complexity of ethical reasoning were performed on 64 Swedish nurses' PhD dissertations dated 2007. A total of seven ethical topics were identified: ethical approval (94% of the dissertations), information and informed consent (86%), confidentiality (67%), ethical aspects of methods (61%), use of ethical principles and regulations (39%), rationale for the study (20%) and fair participant selection (14%). Four of those of topics were most frequently addressed: the majority of dissertations (72%) included 3-5 issues. While many ethical concerns, by their nature, involve systematic concepts or metasystematic principles, ethical reasoning scored predominantly at lesser levels of complexity: abstract (6% of the dissertations), formal (84%) and systematic (10%). Research ethics are inadequately covered in most dissertations by nurses in Sweden. Important ethical concerns are missing, and the complexity of reasoning on ethical principles, motives and implications is insufficient. This is partly due to traditions and norms that discount ethical concerns but is probably also a reflection of the ability of PhD students and supervisors to handle complexity in general. It is suggested that the importance of ethical considerations should be emphasised in graduate and post-graduate studies and that individuals with capacity to deal with systematic and metasystematic concepts are recruited to senior research positions.

Case-Base Maintenance for CCBR-Based Process Evolution

NARCIS (Netherlands)

Weber, B.; Reichert, M.U.; Wild, W.; Roth-Berghofer, T.; Göker, M.H.; Güvenir, H.A.

2006-01-01

The success of a company more and more depends on its ability to flexibly and quickly react to changes. Combining process management techniques and conversational case-based reasoning (CCBR) allows for flexibly aligning the business processes to new requirements by providing integrated process life

Clinical reasoning in nursing, a think-aloud study using virtual patients - a base for an innovative assessment.

Science.gov (United States)

Forsberg, Elenita; Ziegert, Kristina; Hult, Håkan; Fors, Uno

2014-04-01

In health-care education, it is important to assess the competencies that are essential for the professional role. To develop clinical reasoning skills is crucial for nursing practice and therefore an important learning outcome in nursing education programmes. Virtual patients (VPs) are interactive computer simulations of real-life clinical scenarios and have been suggested for use not only for learning, but also for assessment of clinical reasoning. The aim of this study was to investigate how experienced paediatric nurses reason regarding complex VP cases and how they make clinical decisions. The study was also aimed to give information about possible issues that should be assessed in clinical reasoning exams for post-graduate students in diploma specialist paediatric nursing education. The information from this study is believed to be of high value when developing scoring and grading models for a VP-based examination for the specialist diploma in paediatric nursing education. Using the think-aloud method, data were collected from 30 RNs working in Swedish paediatric departments, and child or school health-care centres. Content analysis was used to analyse the data. The results indicate that experienced nurses try to consolidate their hypotheses by seeing a pattern and judging the value of signs, symptoms, physical examinations, laboratory tests and radiology. They show high specific competence but earlier experience of similar cases was also of importance for the decision making. The nurses thought it was an innovative assessment focusing on clinical reasoning and clinical decision making. They thought it was an enjoyable way to be assessed and that all three main issues could be assessed using VPs. In conclusion, VPs seem to be a possible model for assessing the clinical reasoning process and clinical decision making, but how to score and grade such exams needs further research. © 2013.

Modeling and knowledge acquisition processes using case-based inference

Directory of Open Access Journals (Sweden)

Ameneh Khadivar

2017-03-01

Full Text Available The method of acquisition and presentation of the organizational Process Knowledge has considered by many KM researches. In this research a model for process knowledge acquisition and presentation has been presented by using the approach of Case Base Reasoning. The validation of the presented model was evaluated by conducting an expert panel. Then a software has been developed based on the presented model and implemented in Eghtesad Novin Bank of Iran. In this company, based on the stages of the presented model, first the knowledge intensive processes has been identified, then the Process Knowledge was stored in a knowledge base in the format of problem/solution/consequent .The retrieval of the knowledge was done based on the similarity of the nearest neighbor algorithm. For validating of the implemented system, results of the system has compared by the results of the decision making of the expert of the process.

Cultural Diversity and Reasonable Accommodation. An Approach based on Freedom as Non-domination

Directory of Open Access Journals (Sweden)

Isabel Wences

2015-12-01

Full Text Available One of the challenges that culturally diverse societies now face is that of learning to live with differences. Harmonization practices such as concerted adjustment and reasonable accommodation are some of the mechanisms proposed by cultural diversity management policies to deal with this contemporary situation. In the case of reasonable accommodation, this practice can be justified not only because it is based on a recognition of equality in difference, but also on a belief in freedom as a form of non domination, given the inequality present in power relations.

Problem Solving Reasoning and Problem Based Instruction in Geometry Learning

Science.gov (United States)

Sulistyowati, F.; Budiyono, B.; Slamet, I.

2017-09-01

This research aims to analyze the comparison Problem Solving Reasoning (PSR) and Problem Based Instruction (PBI) on problem solving and mathematical communication abilities viewed from Self-Regulated Learning (SRL). Learning was given to grade 8th junior high school students. This research uses quasi experimental method, and then with descriptive analysis. Data were analyzed using two-ways multivariate analysis of variance (MANOVA) and one-way analysis of variance (ANOVA) with different cells. The result of data analysis were learning model gives different effect, level of SRL gives the same effect, and there is no interaction between the learning model with the SRL on the problem solving and mathematical communication abilities. The t-test statistic was used to find out more effective learning model. Based on the test, regardless of the level of SRL, PSR is more effective than PBI for problemsolving ability. The result of descriptive analysis was PSR had the advantage in creating learning that optimizing the ability of learners in reasoning to solve a mathematical problem. Consequently, the PSR is the right learning model to be applied in the classroom to improve problem solving ability of learners.

Ferris Wheels and Filling Bottles: A Case of a Student's Transfer of Covariational Reasoning across Tasks with Different Backgrounds and Features

Science.gov (United States)

Johnson, Heather Lynn; McClintock, Evan; Hornbein, Peter

2017-01-01

Using an actor-oriented perspective on transfer, we report a case of a student's transfer of covariational reasoning across tasks involving different backgrounds and features. In this study, we investigated the research question: How might a student's covariational reasoning on Ferris wheel tasks, involving attributes of distance, width, and…

Longitudinal Assessment of Progress in Reasoning Capacity and Relation with Self-Estimation of Knowledge Base

Science.gov (United States)

Collard, Anne; Mélot, France; Bourguignon, Jean-Pierre

2015-01-01

The aim of the study was to investigate progress in reasoning capacity and knowledge base appraisal in a longitudinal analysis of data from summative evaluation throughout a medical problem-based learning curriculum. The scores in multidisciplinary discussion of a clinical case and multiple choice questionnaires (MCQs) were studied longitudinally…

Teaching clinical reasoning by making thinking visible: an action research project with allied health clinical educators.

Science.gov (United States)

Delany, Clare; Golding, Clinton

2014-01-30

Clinical reasoning is fundamental to all forms of professional health practice, however it is also difficult to teach and learn because it is complex, tacit, and effectively invisible for students. In this paper we present an approach for teaching clinical reasoning based on making expert thinking visible and accessible to students. Twenty-one experienced allied health clinical educators from three tertiary Australian hospitals attended up to seven action research discussion sessions, where they developed a tentative heuristic of their own clinical reasoning, trialled it with students, evaluated if it helped their students to reason clinically, and then refined it so the heuristic was targeted to developing each student's reasoning skills. Data included participants' written descriptions of the thinking routines they developed and trialed with their students and the transcribed action research discussion sessions. Content analysis was used to summarise this data and categorise themes about teaching and learning clinical reasoning. Two overriding themes emerged from participants' reports about using the 'making thinking visible approach'. The first was a specific focus by participating educators on students' understanding of the reasoning process and the second was heightened awareness of personal teaching styles and approaches to teaching clinical reasoning. We suggest that the making thinking visible approach has potential to assist educators to become more reflective about their clinical reasoning teaching and acts as a scaffold to assist them to articulate their own expert reasoning and for students to access and use.

Examining Preservice Teachers' Classroom Management Decisions in Three Case-Based Teaching Approaches

Science.gov (United States)

Cevik, Yasemin Demiraslan; Andre, Thomas

2013-01-01

This study was aimed at comparing the impact of three types of case-based approaches (worked example, faded work example, and case-based reasoning) on preservice teachers' decision making and reasoning skills related to realistic classroom management situations. Participants in this study received a short-term implementation of one of these three…

Drawing-to-Learn: A Framework for Using Drawings to Promote Model-Based Reasoning in Biology

Science.gov (United States)

Quillin, Kim; Thomas, Stephen

2015-01-01

The drawing of visual representations is important for learners and scientists alike, such as the drawing of models to enable visual model-based reasoning. Yet few biology instructors recognize drawing as a teachable science process skill, as reflected by its absence in the Vision and Change report’s Modeling and Simulation core competency. Further, the diffuse research on drawing can be difficult to access, synthesize, and apply to classroom practice. We have created a framework of drawing-to-learn that defines drawing, categorizes the reasons for using drawing in the biology classroom, and outlines a number of interventions that can help instructors create an environment conducive to student drawing in general and visual model-based reasoning in particular. The suggested interventions are organized to address elements of affect, visual literacy, and visual model-based reasoning, with specific examples cited for each. Further, a Blooming tool for drawing exercises is provided, as are suggestions to help instructors address possible barriers to implementing and assessing drawing-to-learn in the classroom. Overall, the goal of the framework is to increase the visibility of drawing as a skill in biology and to promote the research and implementation of best practices. PMID:25713094

The Intersection between Descriptivism and Meliorism in Reasoning Research: Further Proposals in Support of ‘Soft Normativism

Directory of Open Access Journals (Sweden)

Edward J. N. Stupple

2014-11-01

Full Text Available The rationality paradox centres on the observation that people are highly intelligent, yet show evidence of errors and biases in their thinking when measured against normative standards. Elqayam and Evans (e.g., 2011 reject normative standards in the psychological study of thinking, reasoning and deciding in favour of a ‘value-free’ descriptive approach to studying high-level cognition. In reviewing Elqayam and Evans’ position, we defend an alternative to descriptivism in the form of ‘soft normativism’, which allows for normative evaluations alongside the pursuit of descriptive research goals. We propose that normative theories have considerable value provided that researchers: (1 are alert to the philosophical quagmire of strong relativism; (2 are mindful of the biases that can arise from utilising normative benchmarks; and (3 engage in a focused analysis of the processing approach adopted by individual reasoners. We address the controversial ‘is–ought’ inference in this context and appeal to a ‘bridging solution’ to this contested inference that is based on the concept of ‘informal reflective equilibrium’. Furthermore, we draw on Elqayam and Evans’ recognition of a role for normative benchmarks in research programmes that are devised to enhance reasoning performance and we argue that such Meliorist research programmes have a valuable reciprocal relationship with descriptivist accounts of reasoning. In sum, we believe that descriptions of reasoning processes are fundamentally enriched by evaluations of reasoning quality, and argue that if such standards are discarded altogether then our explanations and descriptions of reasoning processes are severely undermined.

The intersection between Descriptivism and Meliorism in reasoning research: further proposals in support of ‘soft normativism’

Science.gov (United States)

Stupple, Edward J. N.; Ball, Linden J.

2014-01-01

The rationality paradox centers on the observation that people are highly intelligent, yet show evidence of errors and biases in their thinking when measured against normative standards. Elqayam and Evans’ (2011) reject normative standards in the psychological study of thinking, reasoning and deciding in favor of a ‘value-free’ descriptive approach to studying high-level cognition. In reviewing Elqayam and Evans’ (2011) position, we defend an alternative to descriptivism in the form of ‘soft normativism,’ which allows for normative evaluations alongside the pursuit of descriptive research goals. We propose that normative theories have considerable value provided that researchers: (1) are alert to the philosophical quagmire of strong relativism; (2) are mindful of the biases that can arise from utilizing normative benchmarks; and (3) engage in a focused analysis of the processing approach adopted by individual reasoners. We address the controversial ‘is–ought’ inference in this context and appeal to a ‘bridging solution’ to this contested inference that is based on the concept of ‘informal reflective equilibrium.’ Furthermore, we draw on Elqayam and Evans’ (2011) recognition of a role for normative benchmarks in research programs that are devised to enhance reasoning performance and we argue that such Meliorist research programs have a valuable reciprocal relationship with descriptivist accounts of reasoning. In sum, we believe that descriptions of reasoning processes are fundamentally enriched by evaluations of reasoning quality, and argue that if such standards are discarded altogether then our explanations and descriptions of reasoning processes are severely undermined. PMID:25414687

Conceptualizing Rolling Motion through an Extreme Case Reasoning Approach

Science.gov (United States)

Hasovic, Elvedin; Mešic, Vanes; Erceg, Nataša

2017-01-01

In this paper we are going to show how learning about some counterintuitive aspects of rolling motion can be facilitated by combining the use of analogies with extreme case reasoning. Specifically, the intuitively comprehensible examples of "rolling" polygonal prisms are used as an analogical anchor that is supposed to help the students…

Theoretical and practical significance of formal reasoning

Science.gov (United States)

Linn, Marcia C.

Piaget's theory has profoundly influenced science education research. Following Piaget, researchers have focused on content-free strategies, developmentally based mechanisms, and structural models of each stage of reasoning. In practice, factors besides those considered in Piaget's theory influence whether or not a theoretically available strategy is used. Piaget's focus has minimized the research attention placed on what could be called practical factors in reasoning. Practical factors are factors that influence application of a theoretically available strategy, for example, previous experience with the task content, familiarity with task instructions, or personality style of the student. Piagetian theory has minimized the importance of practical factors and discouraged investigation of (1) the role of factual knowledge in reasoning, (2) the diagnosis of specific, task-based errors in reasoning, (3) the influence of individual aptitudes on reasoning (e.g., field dependence-independence), and (4) the effect of educational interventions designed to change reasoning. This article calls for new emphasis on practical factors in reasoning and suggests why research on practical factors in reasoning will enhance our understanding of how scientific reasoning is acquired and of how science education programs can foster it.

Semantic reasoning with XML-based biomedical information models.

Science.gov (United States)

O'Connor, Martin J; Das, Amar

2010-01-01

The Extensible Markup Language (XML) is increasingly being used for biomedical data exchange. The parallel growth in the use of ontologies in biomedicine presents opportunities for combining the two technologies to leverage the semantic reasoning services provided by ontology-based tools. There are currently no standardized approaches for taking XML-encoded biomedical information models and representing and reasoning with them using ontologies. To address this shortcoming, we have developed a workflow and a suite of tools for transforming XML-based information models into domain ontologies encoded using OWL. In this study, we applied semantics reasoning methods to these ontologies to automatically generate domain-level inferences. We successfully used these methods to develop semantic reasoning methods for information models in the HIV and radiological image domains.

Reasoning over taxonomic change: exploring alignments for the Perelleschus use case.

Science.gov (United States)

Franz, Nico M; Chen, Mingmin; Yu, Shizhuo; Kianmajd, Parisa; Bowers, Shawn; Ludäscher, Bertram

2015-01-01

Classifications and phylogenetic inferences of organismal groups change in light of new insights. Over time these changes can result in an imperfect tracking of taxonomic perspectives through the re-/use of Code-compliant or informal names. To mitigate these limitations, we introduce a novel approach for aligning taxonomies through the interaction of human experts and logic reasoners. We explore the performance of this approach with the Perelleschus use case of Franz & Cardona-Duque (2013). The use case includes six taxonomies published from 1936 to 2013, 54 taxonomic concepts (i.e., circumscriptions of names individuated according to their respective source publications), and 75 expert-asserted Region Connection Calculus articulations (e.g., congruence, proper inclusion, overlap, or exclusion). An Open Source reasoning toolkit is used to analyze 13 paired Perelleschus taxonomy alignments under heterogeneous constraints and interpretations. The reasoning workflow optimizes the logical consistency and expressiveness of the input and infers the set of maximally informative relations among the entailed taxonomic concepts. The latter are then used to produce merge visualizations that represent all congruent and non-congruent taxonomic elements among the aligned input trees. In this small use case with 6-53 input concepts per alignment, the information gained through the reasoning process is on average one order of magnitude greater than in the input. The approach offers scalable solutions for tracking provenance among succeeding taxonomic perspectives that may have differential biases in naming conventions, phylogenetic resolution, ingroup and outgroup sampling, or ostensive (member-referencing) versus intensional (property-referencing) concepts and articulations.

Problem Representation, Background Evidence, Analysis, Recommendation: An Oral Case Presentation Tool to Promote Diagnostic Reasoning.

Science.gov (United States)

Carter, Cristina; Akar-Ghibril, Nicole; Sestokas, Jeff; Dixon, Gabrina; Bradford, Wilhelmina; Ottolini, Mary

2018-03-01

Oral case presentations provide an opportunity for trainees to communicate diagnostic reasoning at the bedside. However, few tools exist to enable faculty to provide effective feedback. We developed a tool to assess diagnostic reasoning and communication during oral case presentations. Published by Elsevier Inc.

How clear is transparent? Reporting expert reasoning in legal cases

NARCIS (Netherlands)

Sjerps, M.J.; Berger, C.E.H.

2012-01-01

Experts providing evidence in legal cases are universally recommended to be transparent, particularly in their reasoning, so that legal practitioners can critically check whether the conclusions are adequately supported by the results. However, when exploring the practical meaning of this

Gifts to the Future: Design Reasoning, Design Research, and Critical Design Practitioners

Directory of Open Access Journals (Sweden)

Janet McDonnell

Full Text Available Set in the context of a particular orthodoxy about the history of design research over the last 50 years, this opinion piece selectively surveys some of the significant findings from research into what expert design reasoning entails. Using the conceit of a pool of knowledge—which has come about from many different design research agendas, using multiple methods, and with differing foci of attention—it indicates some of what we know about design reasoning as a phenomenon by taking three “scoops” from the pool. These scoops, respectively characterize design reasoning as navigating the swamp; having negative capability; and being concerned with framing. This material is then used to contrast expert design reasoning with salient features of some popular characterizations of design thinking. The contribution concludes with some comments on designer formation, centered on the necessity of proficiency in reflection implied by any goal to nurture critical design practitioners.

Analogical reasoning and the nature of context: a research note.

Science.gov (United States)

Richardson, K; Webster, D S

1996-03-01

Recent theorising about children's reasoning has tended to move towards a 'contextualist' view of cognition and away from the idea of an overall, context-free, mechanism, varying in efficiency, which is the presupposition underlying traditional standardised reasoning tests. An earlier study suggesting improved reasoning performance among children on socio-cognitively meaningful versions of Raven's Matrices tended to support this shift. The main purpose of the study reported here was to observe whether a similar improvement would be found with contextually-based analogical reasoning problems as well. Ten analogy items from a standardised test were administered to 11-year-olds together with 10 structurally-equivalent knowledge-based items. The results reflected improved performance on the latter, overall, and additional analyses led to further suggestions about the nature of the 'contextual advantage' and the origins of item difficulty.

Understanding Gaps in Research Networks: Using "Spatial Reasoning" as a Window into the Importance of Networked Educational Research

Science.gov (United States)

Bruce, Catherine D.; Davis, Brent; Sinclair, Nathalie; McGarvey, Lynn; Hallowell, David; Drefs, Michelle; Francis, Krista; Hawes, Zachary; Moss, Joan; Mulligan, Joanne; Okamoto, Yukari; Whiteley, Walter; Woolcott, Geoff

2017-01-01

This paper finds its origins in a multidisciplinary research group's efforts to assemble a review of research in order to better appreciate how "spatial reasoning" is understood and investigated across academic disciplines. We first collaborated to create a historical map of the development of spatial reasoning across key disciplines…

Model-Based Reasoning in Humans Becomes Automatic with Training.

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Marcos Economides

2015-09-01

Full Text Available Model-based and model-free reinforcement learning (RL have been suggested as algorithmic realizations of goal-directed and habitual action strategies. Model-based RL is more flexible than model-free but requires sophisticated calculations using a learnt model of the world. This has led model-based RL to be identified with slow, deliberative processing, and model-free RL with fast, automatic processing. In support of this distinction, it has recently been shown that model-based reasoning is impaired by placing subjects under cognitive load--a hallmark of non-automaticity. Here, using the same task, we show that cognitive load does not impair model-based reasoning if subjects receive prior training on the task. This finding is replicated across two studies and a variety of analysis methods. Thus, task familiarity permits use of model-based reasoning in parallel with other cognitive demands. The ability to deploy model-based reasoning in an automatic, parallelizable fashion has widespread theoretical implications, particularly for the learning and execution of complex behaviors. It also suggests a range of important failure modes in psychiatric disorders.

Scientific reasoning abilities of nonscience majors in physics-based courses

Science.gov (United States)

Moore, J. Christopher; Rubbo, Louis J.

2012-06-01

We have found that non-STEM (science, technology, engineering, and mathematics) majors taking either a conceptual physics or astronomy course at two regional comprehensive institutions score significantly lower preinstruction on the Lawson’s Classroom Test of Scientific Reasoning (LCTSR) in comparison to national average STEM majors. Based on LCTSR score, the majority of non-STEM students can be classified as either concrete operational or transitional reasoners in Piaget’s theory of cognitive development, whereas in the STEM population formal operational reasoners are far more prevalent. In particular, non-STEM students demonstrate significant difficulty with proportional and hypothetico-deductive reasoning. Prescores on the LCTSR are correlated with normalized learning gains on various concept inventories. The correlation is strongest for content that can be categorized as mostly theoretical, meaning a lack of directly observable exemplars, and weakest for content categorized as mostly descriptive, where directly observable exemplars are abundant. Although the implementation of research-verified, interactive engagement pedagogy can lead to gains in content knowledge, significant gains in theoretical content (such as force and energy) are more difficult with non-STEM students. We also observe no significant gains on the LCTSR without explicit instruction in scientific reasoning patterns. These results further demonstrate that differences in student populations are important when comparing normalized gains on concept inventories, and the achievement of significant gains in scientific reasoning requires a reevaluation of the traditional approach to physics for non-STEM students.

Scientific reasoning abilities of nonscience majors in physics-based courses

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J. Christopher Moore

2012-02-01

Full Text Available We have found that non-STEM (science, technology, engineering, and mathematics majors taking either a conceptual physics or astronomy course at two regional comprehensive institutions score significantly lower preinstruction on the Lawson’s Classroom Test of Scientific Reasoning (LCTSR in comparison to national average STEM majors. Based on LCTSR score, the majority of non-STEM students can be classified as either concrete operational or transitional reasoners in Piaget’s theory of cognitive development, whereas in the STEM population formal operational reasoners are far more prevalent. In particular, non-STEM students demonstrate significant difficulty with proportional and hypothetico-deductive reasoning. Prescores on the LCTSR are correlated with normalized learning gains on various concept inventories. The correlation is strongest for content that can be categorized as mostly theoretical, meaning a lack of directly observable exemplars, and weakest for content categorized as mostly descriptive, where directly observable exemplars are abundant. Although the implementation of research-verified, interactive engagement pedagogy can lead to gains in content knowledge, significant gains in theoretical content (such as force and energy are more difficult with non-STEM students. We also observe no significant gains on the LCTSR without explicit instruction in scientific reasoning patterns. These results further demonstrate that differences in student populations are important when comparing normalized gains on concept inventories, and the achievement of significant gains in scientific reasoning requires a reevaluation of the traditional approach to physics for non-STEM students.

The Relationship between American Sign Language Vocabulary and the Development of Language-Based Reasoning Skills in Deaf Children

Science.gov (United States)

Henner, Jonathan

2016-01-01

The language-based analogical reasoning abilities of Deaf children are a controversial topic. Researchers lack agreement about whether Deaf children possess the ability to reason using language-based analogies, or whether this ability is limited by a lack of access to vocabulary, both written and signed. This dissertation examines factors that…

Student use of model-based reasoning when troubleshooting an electronic circuit

Science.gov (United States)

Lewandowski, Heather; Stetzer, Mackenzie; van de Bogart, Kevin; Dounas-Frazer, Dimitri

2016-03-01

Troubleshooting systems is an integral part of experimental physics in both research and educational settings. Accordingly, ability to troubleshoot is an important learning goal for undergraduate physics lab courses. We investigate students' model-based reasoning on a troubleshooting task using data collected in think-aloud interviews during which pairs of students from two institutions attempted to diagnose and repair a malfunctioning circuit. Our analysis scheme was informed by the Experimental Modeling Framework, which describes physicists' use of mathematical and conceptual models when reasoning about experimental systems. We show that system and subsystem models were crucial for the evaluation of repairs to the circuit and played an important role in some troubleshooting strategies. Finally, drawing on data from interviews with electronics instructors from a broad range of institution types, we outline recommendations for model-based approaches to teaching and learning troubleshooting skills.

Student use of model-based reasoning when troubleshooting an electric circuit

Science.gov (United States)

Dounas-Frazer, Dimitri

2016-05-01

Troubleshooting systems is an integral part of experimental physics in both research and educational settings. Accordingly, ability to troubleshoot is an important learning goal for undergraduate physics lab courses. We investigate students' model-based reasoning on a troubleshooting task using data collected in think-aloud interviews during which pairs of students from two institutions attempted to diagnose and repair a malfunctioning circuit. Our analysis scheme was informed by the Experimental Modeling Framework, which describes physicists' use of mathematical and conceptual models when reasoning about experimental systems. We show that system and subsystem models were crucial for the evaluation of repairs to the circuit and played an important role in some troubleshooting strategies. Finally, drawing on data from interviews with electronics instructors from a broad range of institution types, we outline recommendations for model-based approaches to teaching and learning troubleshooting skills.

The effect of multiple external representations (MERs) worksheets toward complex system reasoning achievement

Science.gov (United States)

Sumarno; Ibrahim, M.; Supardi, Z. A. I.

2018-03-01

The application of a systems approach to assessing biological systems provides hope for a coherent understanding of cell dynamics patterns and their relationship to plant life. This action required the reasoning about complex systems. In other sides, there were a lot of researchers who provided the proof about the instructional successions. They involved the multiple external representations which improved the biological learning. The researcher conducted an investigation using one shoot case study design which involved 30 students in proving that the MERs worksheets could affect the student's achievement of reasoning about complex system. The data had been collected based on test of reasoning about complex system and student's identification result who worked through MERs. The result showed that only partially students could achieve reasoning about system complex, but their MERs skill could support their reasoning ability of complex system. This study could bring a new hope to develop the MERs worksheet as a tool to facilitate the reasoning about complex system.

Unified modeling language and design of a case-based retrieval system in medical imaging.

Science.gov (United States)

LeBozec, C; Jaulent, M C; Zapletal, E; Degoulet, P

1998-01-01

One goal of artificial intelligence research into case-based reasoning (CBR) systems is to develop approaches for designing useful and practical interactive case-based environments. Explaining each step of the design of the case-base and of the retrieval process is critical for the application of case-based systems to the real world. We describe herein our approach to the design of IDEM--Images and Diagnosis from Examples in Medicine--a medical image case-based retrieval system for pathologists. Our approach is based on the expressiveness of an object-oriented modeling language standard: the Unified Modeling Language (UML). We created a set of diagrams in UML notation illustrating the steps of the CBR methodology we used. The key aspect of this approach was selecting the relevant objects of the system according to user requirements and making visualization of cases and of the components of the case retrieval process. Further evaluation of the expressiveness of the design document is required but UML seems to be a promising formalism, improving the communication between the developers and users.

Facilitating progress in health behaviour theory development and modification: the reasoned action approach as a case study.

Science.gov (United States)

Head, Katharine J; Noar, Seth M

2014-01-01

This paper explores the question: what are barriers to health behaviour theory development and modification, and what potential solutions can be proposed? Using the reasoned action approach (RAA) as a case study, four areas of theory development were examined: (1) the theoretical domain of a theory; (2) tension between generalisability and utility, (3) criteria for adding/removing variables in a theory, and (4) organisational tracking of theoretical developments and formal changes to theory. Based on a discussion of these four issues, recommendations for theory development are presented, including: (1) the theoretical domain for theories such as RAA should be clarified; (2) when there is tension between generalisability and utility, utility should be given preference given the applied nature of the health behaviour field; (3) variables should be formally removed/amended/added to a theory based on their performance across multiple studies and (4) organisations and researchers with a stake in particular health areas may be best suited for tracking the literature on behaviour-specific theories and making refinements to theory, based on a consensus approach. Overall, enhancing research in this area can provide important insights for more accurately understanding health behaviours and thus producing work that leads to more effective health behaviour change interventions.

Developing Teaching Material Based on Realistic Mathematics Andoriented to the Mathematical Reasoning and Mathematical Communication

OpenAIRE

Habsah, Fitria

2017-01-01

This research aims to produce mathematics textbook for grade VII junior high school students based on realistic mathematics and oriented to the mathematical reasoning and mathematical communication. The quality is determined based on Nieveen criteria, including validity, practicality, and effectiveness.This study was a research and development and used Borg & Gall model. The subject of this research were the students of SMPN 2 Pujon-Kabupaten Malang, that is 30 students in an experimental cla...

Pisa Question and Reasoning Skill

Directory of Open Access Journals (Sweden)

Ersoy Esen

2017-01-01

Full Text Available The objective of the study is to determine the level of the reasoning skills of the secondary school students. This research has been conducted during the academic year of 2015-2016 with the participation of 51 students in total, from a province in the Black Sea region of Turkey by using random sampling method. Case study method has been used in this study, since it explains an existing situation. In this study, content analysis from the qualitative research methods was carried out. In order to ensure the validity of the scope, agreement percentage formula was used and expert opinions were sought.The problem named Holiday from the Chapter 1 of the normal units in Problem Solving Questions from PISA (Program for International Student Assessments [35] are used as the data collection tool for the study. The problem named Holiday consists of two questions. Applied problems were evaluated according to the mathematical reasoning stages of TIMSS (2003. The findings suggest that the students use proportional reasoning while solving the problems and use the geometric shapes to facilitate the solution of the problem. When they come across problems related to each other, it is observed that they create connections between the problems based on the results of the previous problem. In conclusion, the students perform crosscheck to ensure that their solutions to the problems are accurate.

Script-theory virtual case: A novel tool for education and research.

Science.gov (United States)

Hayward, Jake; Cheung, Amandy; Velji, Alkarim; Altarejos, Jenny; Gill, Peter; Scarfe, Andrew; Lewis, Melanie

2016-11-01

Context/Setting: The script theory of diagnostic reasoning proposes that clinicians evaluate cases in the context of an "illness script," iteratively testing internal hypotheses against new information eventually reaching a diagnosis. We present a novel tool for teaching diagnostic reasoning to undergraduate medical students based on an adaptation of script theory. We developed a virtual patient case that used clinically authentic audio and video, interactive three-dimensional (3D) body images, and a simulated electronic medical record. Next, we used interactive slide bars to record respondents' likelihood estimates of diagnostic possibilities at various stages of the case. Responses were dynamically compared to data from expert clinicians and peers. Comparative frequency distributions were presented to the learner and final diagnostic likelihood estimates were analyzed. Detailed student feedback was collected. Over two academic years, 322 students participated. Student diagnostic likelihood estimates were similar year to year, but were consistently different from expert clinician estimates. Student feedback was overwhelmingly positive: students found the case was novel, innovative, clinically authentic, and a valuable learning experience. We demonstrate the successful implementation of a novel approach to teaching diagnostic reasoning. Future study may delineate reasoning processes associated with differences between novice and expert responses.

Towards Cache-Enabled, Order-Aware, Ontology-Based Stream Reasoning Framework

Energy Technology Data Exchange (ETDEWEB)

Yan, Rui; Praggastis, Brenda L.; Smith, William P.; McGuinness, Deborah L.

2016-08-16

While streaming data have become increasingly more popular in business and research communities, semantic models and processing software for streaming data have not kept pace. Traditional semantic solutions have not addressed transient data streams. Semantic web languages (e.g., RDF, OWL) have typically addressed static data settings and linked data approaches have predominantly addressed static or growing data repositories. Streaming data settings have some fundamental differences; in particular, data are consumed on the fly and data may expire. Stream reasoning, a combination of stream processing and semantic reasoning, has emerged with the vision of providing "smart" processing of streaming data. C-SPARQL is a prominent stream reasoning system that handles semantic (RDF) data streams. Many stream reasoning systems including C-SPARQL use a sliding window and use data arrival time to evict data. For data streams that include expiration times, a simple arrival time scheme is inadequate if the window size does not match the expiration period. In this paper, we propose a cache-enabled, order-aware, ontology-based stream reasoning framework. This framework consumes RDF streams with expiration timestamps assigned by the streaming source. Our framework utilizes both arrival and expiration timestamps in its cache eviction policies. In addition, we introduce the notion of "semantic importance" which aims to address the relevance of data to the expected reasoning, thus enabling the eviction algorithms to be more context- and reasoning-aware when choosing what data to maintain for question answering. We evaluate this framework by implementing three different prototypes and utilizing five metrics. The trade-offs of deploying the proposed framework are also discussed.

The reasonable woman standard: effects on sexual harassment court decisions.

Science.gov (United States)

Perry, Elissa L; Kulik, Carol T; Bourhis, Anne C

2004-02-01

Some federal courts have used a reasonable woman standard rather than the traditional reasonable man or reasonable person standard to determine whether hostile environment sexual harassment has occurred. The current research examined the impact of the reasonable woman standard on federal district court decisions, controlling for other factors found to affect sexual harassment court decisions. Results indicated that there was a weak relationship between whether a case followed a reasonable woman precedent-setting case and the likelihood that the court decision favored the plaintiff. The implications of our findings for individuals and organizations involved in sexual harassment claims are discussed.

Model-Based Reasoning

Science.gov (United States)

Ifenthaler, Dirk; Seel, Norbert M.

2013-01-01

In this paper, there will be a particular focus on mental models and their application to inductive reasoning within the realm of instruction. A basic assumption of this study is the observation that the construction of mental models and related reasoning is a slowly developing capability of cognitive systems that emerges effectively with proper…

Relations between Inductive Reasoning and Deductive Reasoning

Science.gov (United States)

Heit, Evan; Rotello, Caren M.

2010-01-01

One of the most important open questions in reasoning research is how inductive reasoning and deductive reasoning are related. In an effort to address this question, we applied methods and concepts from memory research. We used 2 experiments to examine the effects of logical validity and premise-conclusion similarity on evaluation of arguments.…

Moral reasoning about great apes in research

Science.gov (United States)

Okamoto, Carol Midori

2006-04-01

This study explored how individuals (biomedical scientists, Great Ape Project activists, lay adults, undergraduate biology and environmental studies students, and Grade 12 and 9 biology students) morally judge and reason about using great apes in biomedical and language research. How these groups perceived great apes' mental capacities (e.g., pain, logical thinking) and how these perceptions related to their judgments were investigated through two scenarios. In addition, the kinds of informational statements (e.g., biology, economics) that may affect individuals' scenario judgments were investigated. A negative correlation was found between mental attributions and scenario judgments while no clear pattern occurred for the informational statements. For the biomedical scenario, all groups significantly differed in mean judgment ratings except for the biomedical scientists, GAP activists and Grade 9 students. For the language scenario, all groups differed except for the GAP activists, and undergraduate environmental studies and Grade 9 students. An in-depth qualitative analysis showed that although the biomedical scientists, GAP activists and Grade 9 students had similar judgments, they produced different mean percentages of justifications under four moral frameworks (virtue, utilitarianism, deontology, and welfare). The GAP activists used more virtue reasoning while the biomedical scientists and Grade 9 students used more utilitarian and welfare reasoning, respectively. The results are discussed in terms of developing environmental/humane education curricula.

Emotional Reasoning and Parent-Based Reasoning in Non-Clinical Children, and Their Prospective Relationships with Anxiety Symptoms

Science.gov (United States)

Morren, Mattijn; Muris, Peter; Kindt, Merel; Schouten, Erik; van den Hout, Marcel

2008-01-01

Emotional and parent-based reasoning refer to the tendency to rely on personal or parental anxiety response information rather than on objective danger information when estimating the dangerousness of a situation. This study investigated the prospective relationships of emotional and parent-based reasoning with anxiety symptoms in a sample of…

The Milling Assistant, Case-Based Reasoning, and machining strategy: A report on the development of automated numerical control programming systems at New Mexico State University

Energy Technology Data Exchange (ETDEWEB)

Burd, W. [Sandia National Labs., Albuquerque, NM (United States); Culler, D.; Eskridge, T.; Cox, L.; Slater, T. [New Mexico State Univ., Las Cruces, NM (United States)

1993-08-01

The Milling Assistant (MA) programming system demonstrates the automated development of tool paths for Numerical Control (NC) machine tools. By integrating a Case-Based Reasoning decision processor with a commercial CAD/CAM software, intelligent tool path files for milled and point-to-point features can be created. The operational system is capable of reducing the time required to program a variety of parts and improving product quality by collecting and utilizing ``best of practice`` machining strategies.

Machine Learning-based Intelligent Formal Reasoning and Proving System

Science.gov (United States)

Chen, Shengqing; Huang, Xiaojian; Fang, Jiaze; Liang, Jia

2018-03-01

The reasoning system can be used in many fields. How to improve reasoning efficiency is the core of the design of system. Through the formal description of formal proof and the regular matching algorithm, after introducing the machine learning algorithm, the system of intelligent formal reasoning and verification has high efficiency. The experimental results show that the system can verify the correctness of propositional logic reasoning and reuse the propositional logical reasoning results, so as to obtain the implicit knowledge in the knowledge base and provide the basic reasoning model for the construction of intelligent system.

Agent Based Reasoning in Multilevel Flow Modeling

DEFF Research Database (Denmark)

Lind, Morten; Zhang, Xinxin

2012-01-01

to launch the MFM Workbench into an agent based environment, which can complement disadvantages of the original software. The agent-based MFM Workbench is centered on a concept called “Blackboard System” and use an event based mechanism to arrange the reasoning tasks. This design will support the new...

A Web-Based Rice Plant Expert System Using Rule-Based Reasoning

Directory of Open Access Journals (Sweden)

Anton Setiawan Honggowibowo

2009-12-01

Full Text Available Rice plants can be attacked by various kinds of diseases which are possible to be determined from their symptoms. However, it is to recognize that to find out the exact type of disease, an agricultural expert’s opinion is needed, meanwhile the numbers of agricultural experts are limited and there are too many problems to be solved at the same time. This makes a system with a capability as an expert is required. This system must contain the knowledge of the diseases and symptom of rice plants as an agricultural expert has to have. This research designs a web-based expert system using rule-based reasoning. The rule are modified from the method of forward chaining inference and backward chaining in order to to help farmers in the rice plant disease diagnosis. The web-based rice plants disease diagnosis expert system has the advantages to access and use easily. With web-based features inside, it is expected that the farmer can accesse the expert system everywhere to overcome the problem to diagnose rice diseases.

Developing teaching material based on realistic mathematics andoriented to the mathematical reasoning and mathematical communication

Directory of Open Access Journals (Sweden)

Fitria Habsah

2017-05-01

Full Text Available This research aims to produce mathematics textbook for grade VII junior high school students based on realistic mathematics and oriented to the mathematical reasoning and mathematical communication. The quality is determined based on Nieveen criteria, including validity, practicality, and effectiveness.This study was a research and development and used Borg & Gall model. The subject of this research were the students of SMPN 2 Pujon-Kabupaten Malang, that is 30 students in an experimental class (using the developed textbook and 29 students in a control class (using BSE book from the government. The teaching material was categorized valid if the expert's judgment at least is categorized as “good”. The teaching material was categorized practical if both of teachers and students assessment at least categorized as “good”. The teaching material was categorized effectively if minimum 75% of student scores at least is categorized as “good” for the mathematical reasoning test and mathematical communication test. This research resulted in a valid, practical, and effective teaching material. The resulted of the validation show that material teaching is valid. The resulted of teachers and students assessment show that the product is practical. The tests scores show that the product is effective. Percentage of students who categorized at least as “good” is 83,33% for the mathematical reasoning and 86,67% for the mathematical communication. The resulted of statistic test shows that the product more effective than the BSE book from the government in terms of mathematical reasoning and mathematical communication.

Explicit Knowledge-based Reasoning for Visual Question Answering

OpenAIRE

Wang, Peng; Wu, Qi; Shen, Chunhua; Hengel, Anton van den; Dick, Anthony

2015-01-01

We describe a method for visual question answering which is capable of reasoning about contents of an image on the basis of information extracted from a large-scale knowledge base. The method not only answers natural language questions using concepts not contained in the image, but can provide an explanation of the reasoning by which it developed its answer. The method is capable of answering far more complex questions than the predominant long short-term memory-based approach, and outperform...

Effects of Inquiry-Based Agriscience Instruction on Student Scientific Reasoning

Science.gov (United States)

Thoron, Andrew C.; Myers, Brian E.

2012-01-01

The purpose of this study was to determine the effect of inquiry-based agriscience instruction on student scientific reasoning. Scientific reasoning is defined as the use of the scientific method, inductive, and deductive reasoning to develop and test hypothesis. Developing scientific reasoning skills can provide learners with a connection to the…

Writing case studies in information systems research

NARCIS (Netherlands)

van der Blonk, H.C.

Case study research can be reported in different ways. This paper explores the various ways in which researchers may choose to write down their case studies and then introduces a subsequent typology of writing case studies. The typology is based on a 2 x 2 matrix, resulting in four forms of writing

Visual Reasoning in Computational Environment: A Case of Graph Sketching

Science.gov (United States)

Leung, Allen; Chan, King Wah

2004-01-01

This paper reports the case of a form six (grade 12) Hong Kong student's exploration of graph sketching in a computational environment. In particular, the student summarized his discovery in the form of two empirical laws. The student was interviewed and the interviewed data were used to map out a possible path of his visual reasoning. Critical…

Energy Optimization Using a Case-Based Reasoning Strategy.

Science.gov (United States)

González-Briones, Alfonso; Prieto, Javier; De La Prieta, Fernando; Herrera-Viedma, Enrique; Corchado, Juan M

2018-03-15

At present, the domotization of homes and public buildings is becoming increasingly popular. Domotization is most commonly applied to the field of energy management, since it gives the possibility of managing the consumption of the devices connected to the electric network, the way in which the users interact with these devices, as well as other external factors that influence consumption. In buildings, Heating, Ventilation and Air Conditioning (HVAC) systems have the highest consumption rates. The systems proposed so far have not succeeded in optimizing the energy consumption associated with a HVAC system because they do not monitor all the variables involved in electricity consumption. For this reason, this article presents an agent approach that benefits from the advantages provided by a Multi-Agent architecture (MAS) deployed in a Cloud environment with a wireless sensor network (WSN) in order to achieve energy savings. The agents of the MAS learn social behavior thanks to the collection of data and the use of an artificial neural network (ANN). The proposed system has been assessed in an office building achieving an average energy savings of 41% in the experimental group offices.

Energy Optimization Using a Case-Based Reasoning Strategy

Science.gov (United States)

Herrera-Viedma, Enrique

2018-01-01

At present, the domotization of homes and public buildings is becoming increasingly popular. Domotization is most commonly applied to the field of energy management, since it gives the possibility of managing the consumption of the devices connected to the electric network, the way in which the users interact with these devices, as well as other external factors that influence consumption. In buildings, Heating, Ventilation and Air Conditioning (HVAC) systems have the highest consumption rates. The systems proposed so far have not succeeded in optimizing the energy consumption associated with a HVAC system because they do not monitor all the variables involved in electricity consumption. For this reason, this article presents an agent approach that benefits from the advantages provided by a Multi-Agent architecture (MAS) deployed in a Cloud environment with a wireless sensor network (WSN) in order to achieve energy savings. The agents of the MAS learn social behavior thanks to the collection of data and the use of an artificial neural network (ANN). The proposed system has been assessed in an office building achieving an average energy savings of 41% in the experimental group offices. PMID:29543729

Energy Optimization Using a Case-Based Reasoning Strategy

Directory of Open Access Journals (Sweden)

Alfonso González-Briones

2018-03-01

Full Text Available At present, the domotization of homes and public buildings is becoming increasingly popular. Domotization is most commonly applied to the field of energy management, since it gives the possibility of managing the consumption of the devices connected to the electric network, the way in which the users interact with these devices, as well as other external factors that influence consumption. In buildings, Heating, Ventilation and Air Conditioning (HVAC systems have the highest consumption rates. The systems proposed so far have not succeeded in optimizing the energy consumption associated with a HVAC system because they do not monitor all the variables involved in electricity consumption. For this reason, this article presents an agent approach that benefits from the advantages provided by a Multi-Agent architecture (MAS deployed in a Cloud environment with a wireless sensor network (WSN in order to achieve energy savings. The agents of the MAS learn social behavior thanks to the collection of data and the use of an artificial neural network (ANN. The proposed system has been assessed in an office building achieving an average energy savings of 41% in the experimental group offices.

THE EFFECT OF INQUIRY BASED LEARNING ON THE REASONING ABILITY OF GRADE VII STUDENTS ABOUT HEAT CONCEPT

Directory of Open Access Journals (Sweden)

N. A. C. Damawati

2016-01-01

Full Text Available This study aimed to analyze the effect of Inquiry Based Learningon the reasoning ability of grade 7 students about heat concept. This study is a quasi-experimental research design with non-equivalent post-test only controls group design. Two groups of seventh grade students were included as samples, which receive the experimental class of Inquiry Based Learning treatment while the other group acted as a control group who received the learning process in accordance with the applicable provisions of the curriculum. The data collected in this study is the students reasoning ability which obtained from the test of reasoning ability. Data were analyzed using descriptive statistics and statistical parametric t-test. Results of independet research shows that there are significant differences in reasoning abilities between the experimental class and control class. In this research, the experiment class perform more better reasoning skills than the control class.Penelitian ini bertujuan untuk menganalisis pengaruh Inquiry Based Learning terhadap kemampuan penalaran siswa kelas VII pada materi Kalor. Penelitian ini merupakan penelitian eksperimen semu dengan rancangan non-equivalent post-test only control group design.  Dua kelompok siswa kelas VII  dilibatkan sebagai sampel penelitian, dimana kelas eksperimen menerima perlakuan Inquiry Based Learning sementara kelompok lainnya bertindak sebagai kelas kontrol yang menerima proses pembelajaran sesuai dengan ketentuan kurikulum yang berlaku di sekolah tempat penelitian dilaksanakan. Data yang dikumpulkan dalam penelitian ini adalah kemampuan penalaran siswa yang diperoleh dari hasil tes kemampuan penalaran. Data dianalisis dengan menggunakan statistik deskriptif dan statistik parametrik Independent t-test. Hasil penelitian menunjukkan bahwa terdapat perbedaan kemampuan penalaran yang signifikan antara kelas eksperimen dan kelas kontrol Kelas eksperimen menunjukkan kemampuan penalaran yang lebih baik

Enhancements to knowledge discovery framework of SOPHIA textual case-based reasoning

Directory of Open Access Journals (Sweden)

Islam Elhalwany

2014-11-01

This paper contributes to propose enhancements to SOPHIA approach that aims to enhance the retrieval efficiency and increase the precision degree. It also aimed to grantee that all results will have the same subject of the user query. The enhancements include performing an automatic classification to the case-base before the clustering step in the indexing stage, and include performing an automatic classification to the user query before the retrieval stage. Moreover, proofing that SOPHIA approach is a domain and language independent by applying it in the domain of Islamic jurisprudence in Arabic language.

Stimulating Scientific Reasoning with Drawing-Based Modeling

Science.gov (United States)

Heijnes, Dewi; van Joolingen, Wouter; Leenaars, Frank

2018-01-01

We investigate the way students' reasoning about evolution can be supported by drawing-based modeling. We modified the drawing-based modeling tool SimSketch to allow for modeling evolutionary processes. In three iterations of development and testing, students in lower secondary education worked on creating an evolutionary model. After each…

A Model-based Avionic Prognostic Reasoner (MAPR)

Data.gov (United States)

National Aeronautics and Space Administration — The Model-based Avionic Prognostic Reasoner (MAPR) presented in this paper is an innovative solution for non-intrusively monitoring the state of health (SoH) and...

A public health decision support system model using reasoning methods.

Science.gov (United States)

Mera, Maritza; González, Carolina; Blobel, Bernd

2015-01-01

Public health programs must be based on the real health needs of the population. However, the design of efficient and effective public health programs is subject to availability of information that can allow users to identify, at the right time, the health issues that require special attention. The objective of this paper is to propose a case-based reasoning model for the support of decision-making in public health. The model integrates a decision-making process and case-based reasoning, reusing past experiences for promptly identifying new population health priorities. A prototype implementation of the model was performed, deploying the case-based reasoning framework jColibri. The proposed model contributes to solve problems found today when designing public health programs in Colombia. Current programs are developed under uncertain environments, as the underlying analyses are carried out on the basis of outdated and unreliable data.

Registered nurses' clinical reasoning skills and reasoning process: A think-aloud study.

Science.gov (United States)

Lee, JuHee; Lee, Young Joo; Bae, JuYeon; Seo, Minjeong

2016-11-01

As complex chronic diseases are increasing, nurses' prompt and accurate clinical reasoning skills are essential. However, little is known about the reasoning skills of registered nurses. This study aimed to determine how registered nurses use their clinical reasoning skills and to identify how the reasoning process proceeds in the complex clinical situation of hospital setting. A qualitative exploratory design was used with a think-aloud method. A total of 13 registered nurses (mean years of experience=11.4) participated in the study, solving an ill-structured clinical problem based on complex chronic patients cases in a hospital setting. Data were analyzed using deductive content analysis. Findings showed that the registered nurses used a variety of clinical reasoning skills. The most commonly used skill was 'checking accuracy and reliability.' The reasoning process of registered nurses covered assessment, analysis, diagnosis, planning/implementation, and evaluation phase. It is critical that registered nurses apply appropriate clinical reasoning skills in complex clinical practice. The main focus of registered nurses' reasoning in this study was assessing a patient's health problem, and their reasoning process was cyclic, rather than linear. There is a need for educational strategy development to enhance registered nurses' competency in determining appropriate interventions in a timely and accurate fashion. Copyright © 2016 Elsevier Ltd. All rights reserved.

Building theories from case study research: the progressive case study

NARCIS (Netherlands)

Steenhuis, H.J.; de Bruijn, E.J.

2006-01-01

Meredith (1998) argues for more case and field research studies in the field of operations management. Based on a literature review, we discuss several existing approaches to case studies and their characteristics. These approaches include; the Grounded Theory approach which proposes no prior

The Process of Clinical Reasoning among Medical Students

Directory of Open Access Journals (Sweden)

Djon Machado Lopes

Full Text Available ABSTRACT Introduction: Research in the field of medical reasoning has shed light on the reasoning process used by medical students. The strategies in this process are related to the analytical [hypothetical-deductive (HD] and nonanalytic [scheme-inductive (SI] systems, and pattern recognition (PR]. Objective: To explore the clinical reasoning process of students from the fifth year of medical school at the end of the clinical cycle of medical internship, and to identify the strategies used in preparing diagnostic hypotheses, knowledge organization and content. Method: Qualitative research conducted in 2014 at a Brazilian public university with medical interns. Following Stamm's method, a case in internal medicine (IM was built based on the theory of prototypes (Group 1 = 47 interns, in which the interns listed, according to their own perceptions, the signs, symptoms, syndromes, and diseases typical of internal medicine. This case was used for evaluating the clinical reasoning process of Group 2 (30 students = simple random sample obtained with the "think aloud" process. The verbalizations were transcribed and evaluated by Bardin's thematic analysis. The content analysis were approved by two experts at the beginning and at the end of the analysis process. Results: The interns developed 164 primary and secondary hypotheses when solving the case. The SI strategy prevailed with 48.8%, followed by PR (35.4%, HD (12.2%, and mixed (1.8 % each: SI + HD and HD + PR. The students built 146 distinct semantic axes, resulting in an average of 4.8/ participant. During the analysis, 438 interpretation processes were executed (average of 14.6/participant, and 124 combination processes (average of 4.1/participant. Conclusions: The nonanalytic strategies prevailed with the PR being the most used in the development of primary hypotheses (46.8% and the SI in secondary hypotheses (93%. The interns showed a strong semantic network and did three and a half times more

Data science in R a case studies approach to computational reasoning and problem solving

CERN Document Server

Nolan, Deborah

2015-01-01

Effectively Access, Transform, Manipulate, Visualize, and Reason about Data and ComputationData Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving illustrates the details involved in solving real computational problems encountered in data analysis. It reveals the dynamic and iterative process by which data analysts approach a problem and reason about different ways of implementing solutions. The book's collection of projects, comprehensive sample solutions, and follow-up exercises encompass practical topics pertaining to data processing, including: Non-standar

Drawing-to-learn: a framework for using drawings to promote model-based reasoning in biology.

Science.gov (United States)

Quillin, Kim; Thomas, Stephen

2015-03-02

The drawing of visual representations is important for learners and scientists alike, such as the drawing of models to enable visual model-based reasoning. Yet few biology instructors recognize drawing as a teachable science process skill, as reflected by its absence in the Vision and Change report's Modeling and Simulation core competency. Further, the diffuse research on drawing can be difficult to access, synthesize, and apply to classroom practice. We have created a framework of drawing-to-learn that defines drawing, categorizes the reasons for using drawing in the biology classroom, and outlines a number of interventions that can help instructors create an environment conducive to student drawing in general and visual model-based reasoning in particular. The suggested interventions are organized to address elements of affect, visual literacy, and visual model-based reasoning, with specific examples cited for each. Further, a Blooming tool for drawing exercises is provided, as are suggestions to help instructors address possible barriers to implementing and assessing drawing-to-learn in the classroom. Overall, the goal of the framework is to increase the visibility of drawing as a skill in biology and to promote the research and implementation of best practices. © 2015 K. Quillin and S. Thomas. CBE—Life Sciences Education © 2015 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Children's Gender-Based Reasoning about Toys.

Science.gov (United States)

Martin, Carol Lynn; And Others

1995-01-01

Three studies examined how preschool children used gender-based reasoning in making judgments about toy preferences for themselves and for others. Found that children used gender labels to guide their own preferences and their expectations of others. Even with very attractive toys, children liked the toys less if they were labeled as being for the…

Education research: a case-based bioethics curriculum for neurology residents.

Science.gov (United States)

Tolchin, Benjamin; Willey, Joshua Z; Prager, Kenneth

2015-03-31

In 2012, the American Academy of Neurology (AAN) updated and expanded its ethics curriculum into Practical Ethics in Clinical Neurology, a case-based ethics curriculum for neurologists. We piloted a case-based bioethics curriculum for neurology residents using the framework and topics recommended by the AAN, matched to clinical cases drawn from Columbia's neurologic services. Our primary outcome was residents' ability to analyze and manage ethically complex cases as measured on precurriculum and postcurriculum multiple-choice quizzes. Secondary outcomes included precurriculum and postcurriculum self-assessed comfort in discussing and managing ethically complex cases, as well as attendance at ethics discussion sessions as compared to attendance at other didactic sessions. Resident performance on quizzes improved from 75.8% to 86.7% (p = 0.02). Comfort in discussing ethically complex cases improved from 6.4 to 7.4 on a 10-point scale (p = 0.03). Comfort in managing such cases trended toward improvement but did not reach statistical significance. Attendance was significantly better at ethics discussions (73.5%) than at other didactic sessions (61.7%, p = 0.04). Our formal case-based ethics curriculum for neurology residents, based on core topics drawn from the AAN's published curricula, was successfully piloted. Our study showed a statistically significant improvement in residents' ability to analyze and manage ethically complex cases as measured by multiple-choice tests and self-assessments. © 2015 American Academy of Neurology.

An approach to the verification of a fault-tolerant, computer-based reactor safety system: A case study using automated reasoning: Volume 1: Interim report

International Nuclear Information System (INIS)

Chisholm, G.H.; Kljaich, J.; Smith, B.T.; Wojcik, A.S.

1987-01-01

The purpose of this project is to explore the feasibility of automating the verification process for computer systems. The intent is to demonstrate that both the software and hardware that comprise the system meet specified availability and reliability criteria, that is, total design analysis. The approach to automation is based upon the use of Automated Reasoning Software developed at Argonne National Laboratory. This approach is herein referred to as formal analysis and is based on previous work on the formal verification of digital hardware designs. Formal analysis represents a rigorous evaluation which is appropriate for system acceptance in critical applications, such as a Reactor Safety System (RSS). This report describes a formal analysis technique in the context of a case study, that is, demonstrates the feasibility of applying formal analysis via application. The case study described is based on the Reactor Safety System (RSS) for the Experimental Breeder Reactor-II (EBR-II). This is a system where high reliability and availability are tantamount to safety. The conceptual design for this case study incorporates a Fault-Tolerant Processor (FTP) for the computer environment. An FTP is a computer which has the ability to produce correct results even in the presence of any single fault. This technology was selected as it provides a computer-based equivalent to the traditional analog based RSSs. This provides a more conservative design constraint than that imposed by the IEEE Standard, Criteria For Protection Systems For Nuclear Power Generating Stations (ANSI N42.7-1972)

An Automated Approach to Reasoning Under Multiple Perspectives

Science.gov (United States)

deBessonet, Cary

2004-01-01

This is the final report with emphasis on research during the last term. The context for the research has been the development of an automated reasoning technology for use in SMS (symbolic Manipulation System), a system used to build and query knowledge bases (KBs) using a special knowledge representation language SL (Symbolic Language). SMS interpreters assertive SL input and enters the results as components of its universe. The system operates in two basic models: 1) constructive mode (for building KBs); and 2) query/search mode (for querying KBs). Query satisfaction consists of matching query components with KB components. The system allows "penumbral matches," that is, matches that do not exactly meet the specifications of the query, but which are deemed relevant for the conversational context. If the user wants to know whether SMS has information that holds, say, for "any chow," the scope of relevancy might be set so that the system would respond based on a finding that it has information that holds for "most dogs," although this is not exactly what was called for by the query. The response would be qualified accordingly, as would normally be the case in ordinary human conversation. The general goal of the research was to develop an approach by which assertive content could be interpreted from multiple perspectives so that reasoning operations could be successfully conducted over the results. The interpretation of an SL statement such as, "{person believes [captain (asserted (perhaps)) (astronaut saw (comet (bright)))]}," which in English would amount to asserting something to the effect that, "Some person believes that a captain perhaps asserted that an astronaut saw a bright comet," would require the recognition of multiple perspectives, including some that are: a) epistemically-based (focusing on "believes"); b) assertion-based (focusing on "asserted"); c) perception-based (focusing on "saw"); d) adjectivally-based (focusing on "bight"); and e) modally-based

On Derek Parfit' s Objectivist Theory of Reasons for Action:Desire-based or Value-based?

Institute of Scientific and Technical Information of China (English)

Zhang Jieting

2017-01-01

The issue of the sources of normativity has been a very hot topic in contem-porary Anglo-American ethics. Some scholars believe that the normativity should be interpre-ted as a reason-implying concept and it can be analyzed further as moral reasons. So,to better understand the sources of normativity,we have to explore the sources of the reasons further. Generally,there are two competing views on the sources of reasons:subjectivism and objectiv-ism. Subjectivism argues that the reasons for action are ultimately based on desires or facts a-bout desires. Objectivism argues that the reasons are given by the objects,determined by the value of the relevant facts about desired objects. Parfit proposed an objectivist theory of reasons for action,and he tried to prove that reasons are external,objective,and value-based,through his three arguments,i. e. ,the agony argument,the all or none argument,and the incoherence argument. He finally demonstrated that what can determine reasons for action are facts rather than desires.

Reasoning in explanation-based decision making.

Science.gov (United States)

Pennington, N; Hastie, R

1993-01-01

A general theory of explanation-based decision making is outlined and the multiple roles of inference processes in the theory are indicated. A typology of formal and informal inference forms, originally proposed by Collins (1978a, 1978b), is introduced as an appropriate framework to represent inferences that occur in the overarching explanation-based process. Results from the analysis of verbal reports of decision processes are presented to demonstrate the centrality and systematic character of reasoning in a representative legal decision-making task.

CASE-BASED PRODUCT CONFIGURATION AND REUSE IN MASS CUSTOMIZATION

Institute of Scientific and Technical Information of China (English)

Wang Shiwei; Tan Jianrong; Zhang Shuyou; Wang Xin; He Chenqi

2004-01-01

The increasing complexity and size of configuration knowledge bases requires the provision of advanced methods supporting the development of the actual configuration process and design reuse.A new framework to find a feasible and practical product configuration method is presented in mass customization.The basic idea of the approach is to integrate case-based reasoning (CBR) with a constraint satisfaction problem(CSP).The similarity measure between a crisp and range is also given,which is common in case retrieves.Based on the configuration model,a product platform and customer needs,case adaptation is carried out with the repair-based algorithm.Lastly,the methodology in the elevator configuration design domain is tested.

A Rule-Based Spatial Reasoning Approach for OpenStreetMap Data Quality Enrichment; Case Study of Routing and Navigation

Science.gov (United States)

2017-01-01

Finding relevant geospatial information is increasingly critical because of the growing volume of geospatial data available within the emerging “Big Data” era. Users are expecting that the availability of massive datasets will create more opportunities to uncover hidden information and answer more complex queries. This is especially the case with routing and navigation services where the ability to retrieve points of interest and landmarks make the routing service personalized, precise, and relevant. In this paper, we propose a new geospatial information approach that enables the retrieval of implicit information, i.e., geospatial entities that do not exist explicitly in the available source. We present an information broker that uses a rule-based spatial reasoning algorithm to detect topological relations. The information broker is embedded into a framework where annotations and mappings between OpenStreetMap data attributes and external resources, such as taxonomies, support the enrichment of queries to improve the ability of the system to retrieve information. Our method is tested with two case studies that leads to enriching the completeness of OpenStreetMap data with footway crossing points-of-interests as well as building entrances for routing and navigation purposes. It is concluded that the proposed approach can uncover implicit entities and contribute to extract required information from the existing datasets. PMID:29088125

A Rule-Based Spatial Reasoning Approach for OpenStreetMap Data Quality Enrichment; Case Study of Routing and Navigation

Directory of Open Access Journals (Sweden)

Amin Mobasheri

2017-10-01

Full Text Available Finding relevant geospatial information is increasingly critical because of the growing volume of geospatial data available within the emerging “Big Data” era. Users are expecting that the availability of massive datasets will create more opportunities to uncover hidden information and answer more complex queries. This is especially the case with routing and navigation services where the ability to retrieve points of interest and landmarks make the routing service personalized, precise, and relevant. In this paper, we propose a new geospatial information approach that enables the retrieval of implicit information, i.e., geospatial entities that do not exist explicitly in the available source. We present an information broker that uses a rule-based spatial reasoning algorithm to detect topological relations. The information broker is embedded into a framework where annotations and mappings between OpenStreetMap data attributes and external resources, such as taxonomies, support the enrichment of queries to improve the ability of the system to retrieve information. Our method is tested with two case studies that leads to enriching the completeness of OpenStreetMap data with footway crossing points-of-interests as well as building entrances for routing and navigation purposes. It is concluded that the proposed approach can uncover implicit entities and contribute to extract required information from the existing datasets.

Intelligent Case Based Decision Support System for Online Diagnosis of Automated Production System

International Nuclear Information System (INIS)

Ben Rabah, N; Saddem, R; Carre-Menetrier, V; Ben Hmida, F; Tagina, M

2017-01-01

Diagnosis of Automated Production System (APS) is a decision-making process designed to detect, locate and identify a particular failure caused by the control law. In the literature, there are three major types of reasoning for industrial diagnosis: the first is model-based, the second is rule-based and the third is case-based. The common and major limitation of the first and the second reasonings is that they do not have automated learning ability. This paper presents an interactive and effective Case Based Decision Support System for online Diagnosis (CB-DSSD) of an APS. It offers a synergy between the Case Based Reasoning (CBR) and the Decision Support System (DSS) in order to support and assist Human Operator of Supervision (HOS) in his/her decision process. Indeed, the experimental evaluation performed on an Interactive Training System for PLC (ITS PLC) that allows the control of a Programmable Logic Controller (PLC), simulating sensors or/and actuators failures and validating the control algorithm through a real time interactive experience, showed the efficiency of our approach. (paper)

Connecting Mathematics Learning through Spatial Reasoning

Science.gov (United States)

Mulligan, Joanne; Woolcott, Geoffrey; Mitchelmore, Michael; Davis, Brent

2018-01-01

Spatial reasoning, an emerging transdisciplinary area of interest to mathematics education research, is proving integral to all human learning. It is particularly critical to science, technology, engineering and mathematics (STEM) fields. This project will create an innovative knowledge framework based on spatial reasoning that identifies new…

The Effect of Origami-Based Instruction on Spatial Visualization, Geometry Achievement, and Geometric Reasoning

Science.gov (United States)

Arici, Sevil; Aslan-Tutak, Fatma

2015-01-01

This research study examined the effect of origami-based geometry instruction on spatial visualization, geometry achievement, and geometric reasoning of tenth-grade students in Turkey. The sample ("n" = 184) was chosen from a tenth-grade population of a public high school in Turkey. It was a quasi-experimental pretest/posttest design. A…

Improving the Reliability of Case-Based Reasoning Systems

Directory of Open Access Journals (Sweden)

Xu Xu

2010-09-01

also discussed in this paper, especially the property that whether inter-feature of case exists redundancy. After that, the reliability of an individual suggested solution is studied. To illustrate these ideas, some experiments and their results are discussed in this paper. The results of experiments show a new route concerning on how to improve the reliability of a CBR system at an overall level.

EMOTIONS AND REASONING IN MORAL DECISION MAKING

Directory of Open Access Journals (Sweden)

V. V. Nadurak

2016-12-01

Full Text Available Purpose of the research is the study of relationship between emotional and rational factors in moral decisions making. Methodology. The work is primarily based on the analysis and synthesis of the main empirical studies of the problem, each of which uses the methods of those sciences in which they were conducted (neurosciences. Originality. In general, the process of moral decision making cannot be described by a single simple model that would see only emotional or rational factor in foundation of this process. Moral decision making is characterized by different types of interaction between emotions and rational considerations. The influence of emotional and rational factors on moral decision is nonlinear: moral decision, which person makes, isn’t proportional to those emotions that preceded it and isn't unambiguously determined by them, because rational reasoning and contextual factors can significantly change it. Similarly, the reasoning that precede the decision is not necessarily reflected in the decision, because it can be significantly corrected by those emotions that accompany it. Conclusions. The process of moral decision making involves complex, heterogeneous interaction between emotional and rational factors. There are three main types of such interaction: first, the reasoning serves to rationalize prior emotional response; second, there are cases when reasoning precedes emotional reactions and determines it; third, interaction between these factors is characterized by cyclic causality (emotion impacts reasoning, which in turn impacts emotions. The influence of emotions or rational reasoning on moral decision is nonlinear.

Protection as care: moral reasoning and moral orientation among ethnically and socioeconomically diverse older women.

Science.gov (United States)

Dakin, Emily

2014-01-01

This study examined moral reasoning among ethnically and socioeconomically diverse older women based on the care and justice moral orientations reflecting theoretical frameworks developed by Carol Gilligan and Lawrence Kohlberg, respectively. A major gap in this area of research and theory development has been the lack of examination of moral reasoning in later life. This study addressed this gap by assessing socioeconomically and ethnically diverse older women's reasoning in response to ethical dilemmas showing conflict between autonomy, representative of Kohlberg's justice orientation, and protection, representative of Gilligan's care orientation. The dilemmas used in this study came from adult protective services (APS), the U.S. system that investigates and intervenes in cases of elder abuse and neglect. Subjects were 88 African American, Latina, and Caucasian women age 60 or over from varying socioeconomic status backgrounds who participated in eight focus groups. Overall, participants favored protection over autonomy in responding to the case scenarios. Their reasoning in responding to these dilemmas reflected an ethic of care and responsibility and a recognition of the limitations of autonomy. This reasoning is highly consistent with the care orientation. Variations in the overall ethic of care and responsibility based on ethnicity and SES also are discussed. Copyright © 2013. Published by Elsevier Inc.

Memory, reasoning, and categorization: parallels and common mechanisms.

Science.gov (United States)

Hayes, Brett K; Heit, Evan; Rotello, Caren M

2014-01-01

Traditionally, memory, reasoning, and categorization have been treated as separate components of human cognition. We challenge this distinction, arguing that there is broad scope for crossover between the methods and theories developed for each task. The links between memory and reasoning are illustrated in a review of two lines of research. The first takes theoretical ideas (two-process accounts) and methodological tools (signal detection analysis, receiver operating characteristic curves) from memory research and applies them to important issues in reasoning research: relations between induction and deduction, and the belief bias effect. The second line of research introduces a task in which subjects make either memory or reasoning judgments for the same set of stimuli. Other than broader generalization for reasoning than memory, the results were similar for the two tasks, across a variety of experimental stimuli and manipulations. It was possible to simultaneously explain performance on both tasks within a single cognitive architecture, based on exemplar-based comparisons of similarity. The final sections explore evidence for empirical and processing links between inductive reasoning and categorization and between categorization and recognition. An important implication is that progress in all three of these fields will be expedited by further investigation of the many commonalities between these tasks.

Memory, reasoning and categorization: Parallels and common mechanisms

Directory of Open Access Journals (Sweden)

BRETT eHAYES

2014-06-01

Full Text Available Traditionally, memory, reasoning and categorization have been treated as separate components of human cognition. We challenge this distinction, arguing that there is broad scope for crossover between the methods and theories developed for each task. The links between memory and reasoning are illustrated in a review of two lines of research. The first takes theoretical ideas (two-process accounts and methodological tools (signal detection analysis, receiver operating characteristic curves from memory research and applies them to important issues in reasoning research: relations between induction and deduction, and the belief bias effect. The second line of research introduces a task in which subjects make either memory or reasoning judgments for the same set of stimuli. Other than broader generalization for reasoning than memory, the results were similar for the two tasks, across a variety of experimental stimuli and manipulations. It was possible to simultaneously explain performance on both tasks within a single cognitive architecture, based on exemplar-based comparisons of similarity. The final sections explore evidence for empirical and processing links between inductive reasoning and categorization and between categorization and recognition. An important implication is that progress in all three of these fields will be expedited by further investigation of the many commonalities between these tasks.

Inverse reasoning processes in obsessive-compulsive disorder.

Science.gov (United States)

Wong, Shiu F; Grisham, Jessica R

2017-04-01

The inference-based approach (IBA) is one cognitive model that aims to explain the aetiology and maintenance of obsessive-compulsive disorder (OCD). The model proposes that certain reasoning processes lead an individual with OCD to confuse an imagined possibility with an actual probability, a state termed inferential confusion. One such reasoning process is inverse reasoning, in which hypothetical causes form the basis of conclusions about reality. Although previous research has found associations between a self-report measure of inferential confusion and OCD symptoms, evidence of a specific association between inverse reasoning and OCD symptoms is lacking. In the present study, we developed a task-based measure of inverse reasoning in order to investigate whether performance on this task is associated with OCD symptoms in an online sample. The results provide some evidence for the IBA assertion: greater endorsement of inverse reasoning was significantly associated with OCD symptoms, even when controlling for general distress and OCD-related beliefs. Future research is needed to replicate this result in a clinical sample and to investigate a potential causal role for inverse reasoning in OCD. Copyright © 2016 Elsevier Ltd. All rights reserved.

Using Analytics to Transform a Problem-Based Case Library: An Educational Design Research Approach

Science.gov (United States)

Schmidt, Matthew; Tawfik, Andrew A.

2018-01-01

This article describes the iterative design, development, and evaluation of a case-based learning environment focusing on an ill-structured sales management problem. We discuss our processes and situate them within the broader framework of educational design research. The learning environment evolved over the course of three design phases. A…

Applying Case-Based Method in Designing Self-Directed Online Instruction: A Formative Research Study

Science.gov (United States)

Luo, Heng; Koszalka, Tiffany A.; Arnone, Marilyn P.; Choi, Ikseon

2018-01-01

This study investigated the case-based method (CBM) instructional-design theory and its application in designing self-directed online instruction. The purpose of this study was to validate and refine the theory for a self-directed online instruction context. Guided by formative research methodology, this study first developed an online tutorial…

Applying Case-Based Reasoning in Supporting Strategy Decisions

OpenAIRE

S. M. Seyedhosseini; A. Makui; M. Ghadami

2011-01-01

Globalization and therefore increasing tight competition among companies, have resulted to increase the importance of making well-timed decision. Devising and employing effective strategies, that are flexible and adaptive to changing market, stand a greater chance of being effective in the long-term. In other side, a clear focus on managing the entire product lifecycle has emerged as critical areas for investment. Therefore, applying wellorganized tools to employ past experience in new case, ...

Nurses' ethical reasoning in cases of physical restraint in acute elderly care: a qualitative study.

Science.gov (United States)

Goethals, Sabine; Dierckx de Casterlé, Bernadette; Gastmans, Chris

2013-11-01

In their practice, nurses make daily decisions that are ethically informed. An ethical decision is the result of a complex reasoning process based on knowledge and experience and driven by ethical values. Especially in acute elderly care and more specifically decisions concerning the use of physical restraint require a thoughtful deliberation of the different values at stake. Qualitative evidence concerning nurses' decision-making in cases of physical restraint provided important insights in the complexity of decision-making as a trajectory. However a nuanced and refined understanding of the reasoning process in terms of ethical values is still lacking. A qualitative interview design, inspired by the Grounded Theory approach, was carried out to explore nurses' reasoning process in terms of ethical values. We interviewed 21 acute geriatric nurses from 12 hospitals in different regions in Flanders, Belgium in the period October 2009-April 2011. The Qualitative Analysis Guide of Leuven was used to analyse interview data. Nurses' decision-making is characterized as an ethical deliberation process where different values are identified and where the process of balancing these values forms the essence of ethical deliberation. Ethical decision-making in cases of physical restraint implies that nurses have to choose which values receive priority in the process, which entails that not all values can be respected to the same degree. As a result, decision making can be experienced as difficult, even as a dilemma. Driven by the overwhelming goal of protecting physical integrity, nurses took into account the values of dignity and justice more implicitly and less dominantly.

Using Relational Reasoning Strategies to Help Improve Clinical Reasoning Practice.

Science.gov (United States)

Dumas, Denis; Torre, Dario M; Durning, Steven J

2018-05-01

Clinical reasoning-the steps up to and including establishing a diagnosis and/or therapy-is a fundamentally important mental process for physicians. Unfortunately, mounting evidence suggests that errors in clinical reasoning lead to substantial problems for medical professionals and patients alike, including suboptimal care, malpractice claims, and rising health care costs. For this reason, cognitive strategies by which clinical reasoning may be improved-and that many expert clinicians are already using-are highly relevant for all medical professionals, educators, and learners.In this Perspective, the authors introduce one group of cognitive strategies-termed relational reasoning strategies-that have been empirically shown, through limited educational and psychological research, to improve the accuracy of learners' reasoning both within and outside of the medical disciplines. The authors contend that relational reasoning strategies may help clinicians to be metacognitive about their own clinical reasoning; such strategies may also be particularly well suited for explicitly organizing clinical reasoning instruction for learners. Because the particular curricular efforts that may improve the relational reasoning of medical students are not known at this point, the authors describe the nature of previous research on relational reasoning strategies to encourage the future design, implementation, and evaluation of instructional interventions for relational reasoning within the medical education literature. The authors also call for continued research on using relational reasoning strategies and their role in clinical practice and medical education, with the long-term goal of improving diagnostic accuracy.

Use of case-based reasoning to enhance intensive management of patients on insulin pump therapy.

Science.gov (United States)

Schwartz, Frank L; Shubrook, Jay H; Marling, Cynthia R

2008-07-01

This study was conducted to develop case-based decision support software to improve glucose control in patients with type 1 diabetes mellitus (T1DM) on insulin pump therapy. While the benefits of good glucose control are well known, achieving and maintaining good glucose control remains a difficult task. Case-based decision support software may assist by recalling past problems in glucose control and their associated therapeutic adjustments. Twenty patients with T1DM on insulin pumps were enrolled in a 6-week study. Subjects performed self-glucose monitoring and provided daily logs via the Internet, tracking insulin dosages, work, sleep, exercise, meals, stress, illness, menstrual cycles, infusion set changes, pump problems, hypoglycemic episodes, and other events. Subjects wore a continuous glucose monitoring system at weeks 1, 3, and 6. Clinical data were interpreted by physicians, who explained the relationship between life events and observed glucose patterns as well as treatment rationales to knowledge engineers. Knowledge engineers built a prototypical system that contained cases of problems in glucose control together with their associated solutions. Twelve patients completed the study. Fifty cases of clinical problems and solutions were developed and stored in a case base. The prototypical system detected 12 distinct types of clinical problems. It displayed the stored problems that are most similar to the problems detected, and offered learned solutions as decision support to the physician. This software can screen large volumes of clinical data and glucose levels from patients with T1DM, identify clinical problems, and offer solutions. It has potential application in managing all forms of diabetes.

Relations between inductive reasoning and deductive reasoning.

Science.gov (United States)

Heit, Evan; Rotello, Caren M

2010-05-01

One of the most important open questions in reasoning research is how inductive reasoning and deductive reasoning are related. In an effort to address this question, we applied methods and concepts from memory research. We used 2 experiments to examine the effects of logical validity and premise-conclusion similarity on evaluation of arguments. Experiment 1 showed 2 dissociations: For a common set of arguments, deduction judgments were more affected by validity, and induction judgments were more affected by similarity. Moreover, Experiment 2 showed that fast deduction judgments were like induction judgments-in terms of being more influenced by similarity and less influenced by validity, compared with slow deduction judgments. These novel results pose challenges for a 1-process account of reasoning and are interpreted in terms of a 2-process account of reasoning, which was implemented as a multidimensional signal detection model and applied to receiver operating characteristic data. PsycINFO Database Record (c) 2010 APA, all rights reserved.

Model-based reasoning and the control of process plants

International Nuclear Information System (INIS)

Vaelisuo, Heikki

1993-02-01

In addition to feedback control, safe and economic operation of industrial process plants requires discrete-event type logic control like for example automatic control sequences, interlocks, etc. A lot of complex routine reasoning is involved in the design and verification and validation (VandV) of such automatics. Similar reasoning tasks are encountered during plant operation in action planning and fault diagnosis. The low-level part of the required problem solving is so straightforward that it could be accomplished by a computer if only there were plant models which allow versatile mechanised reasoning. Such plant models and corresponding inference algorithms are the main subject of this report. Deep knowledge and qualitative modelling play an essential role in this work. Deep knowledge refers to mechanised reasoning based on the first principles of the phenomena in the problem domain. Qualitative modelling refers to knowledge representation formalism and related reasoning methods which allow solving problems on an abstraction level higher than for example traditional simulation and optimisation. Prolog is a commonly used platform for artificial intelligence (Al) applications. Constraint logic languages like CLP(R) and Prolog-III extend the scope of logic programming to numeric problem solving. In addition they allow a programming style which often reduces the computational complexity significantly. An approach to model-based reasoning implemented in constraint logic programming language CLP(R) is presented. The approach is based on some of the principles of QSIM, an algorithm for qualitative simulation. It is discussed how model-based reasoning can be applied in the design and VandV of plant automatics and in action planning during plant operation. A prototype tool called ISIR is discussed and some initial results obtained during the development of the tool are presented. The results presented originate from preliminary test results of the prototype obtained

Case-Based Reasoning in Mixed Paradigm Settings and with Learning

Science.gov (United States)

1994-04-30

Learning Prototypical Cases OFF-BROADWAY, MCI and RMHC -* are three CBR-ML systems that learn case prototypes. We feel that methods that enable the...at Irvine Machine Learning Repository, including heart disease and breast cancer databases. OFF-BROADWAY, MCI and RMHC -* made the following notable

Improvement of metacognitive skills and students’ reasoning ability through problem-based learning

Science.gov (United States)

Haryani, S.; Masfufah; Wijayati, N.; Kurniawan, C.

2018-03-01

The aim of this research is to know the influence of PBL application to the improvement of metacognitive skill and students’ reasoning ability on Constanta solubility product (Ksp). The research used mix method with concurrent triangulation strategy and pretest-posttest control group design. Metacognitive skills are known from the results of written tests and questionnaires with N-Gain analysis, t-test, whereas reasoning ability is known from observations and interviews with descriptive analysis. The results showed that the N-Gain effect of PBL on metacognitive skills is 0,59 with medium category and N-Gain value of PBL influence on reasoning ability is 0.71 with the high category. The steps in the PBL affect the metacognitive skills and can train learners to develop their reasoning skills in the solving problems.

Fuzzy Reasoning Based on First-Order Modal Logic,

NARCIS (Netherlands)

Zhang, Xiaoru; Zhang, Z.; Sui, Y.; Huang, Z.

2008-01-01

As an extension of traditional modal logics, this paper proposes a fuzzy first-order modal logic based on believable degree, and gives out a description of the fuzzy first-order modal logic based on constant domain semantics. In order to make the reasoning procedure between the fuzzy assertions

Real-time context aware reasoning in on-board intelligent traffic systems: An Architecture for Ontology-based Reasoning using Finite State Machines

NARCIS (Netherlands)

Stoter, Arjan; Dalmolen, Simon; Drenth, Eduard; Cornelisse, Erik; Mulder, Wico

2011-01-01

In-vehicle information management is vital in intelligent traffic systems. In this paper we motivate an architecture for ontology-based context-aware reasoning for in-vehicle information management. An ontology is essential for system standardization and communication, and ontology-based reasoning

To Reason or Not to Reason: Is Autobiographical Reasoning Always Beneficial?

Science.gov (United States)

McLean, Kate C.; Mansfield, Cade D.

2011-01-01

Autobiographical reasoning has been found to be a critical process in identity development; however, the authors suggest that existing research shows that such reasoning may not always be critical to another important outcome: well-being. The authors describe characteristics of people such as personality and age, contexts such as conversations,…

Incorporating an Interactive Statistics Workshop into an Introductory Biology Course-Based Undergraduate Research Experience (CURE) Enhances Students' Statistical Reasoning and Quantitative Literacy Skills.

Science.gov (United States)

Olimpo, Jeffrey T; Pevey, Ryan S; McCabe, Thomas M

2018-01-01

Course-based undergraduate research experiences (CUREs) provide an avenue for student participation in authentic scientific opportunities. Within the context of such coursework, students are often expected to collect, analyze, and evaluate data obtained from their own investigations. Yet, limited research has been conducted that examines mechanisms for supporting students in these endeavors. In this article, we discuss the development and evaluation of an interactive statistics workshop that was expressly designed to provide students with an open platform for graduate teaching assistant (GTA)-mentored data processing, statistical testing, and synthesis of their own research findings. Mixed methods analyses of pre/post-intervention survey data indicated a statistically significant increase in students' reasoning and quantitative literacy abilities in the domain, as well as enhancement of student self-reported confidence in and knowledge of the application of various statistical metrics to real-world contexts. Collectively, these data reify an important role for scaffolded instruction in statistics in preparing emergent scientists to be data-savvy researchers in a globally expansive STEM workforce.

Achieving Research Impact Through Co-creation in Community-Based Health Services: Literature Review and Case Study.

Science.gov (United States)

Greenhalgh, Trisha; Jackson, Claire; Shaw, Sara; Janamian, Tina

2016-06-01

Co-creation-collaborative knowledge generation by academics working alongside other stakeholders-is an increasingly popular approach to aligning research and service development. It has potential for "moving beyond the ivory towers" to deliver significant societal impact via dynamic, locally adaptive community-academic partnerships. Principles of successful co-creation include a systems perspective, a creative approach to research focused on improving human experience, and careful attention to governance and process. If these principles are not followed, co-creation efforts may fail. Co-creation-collaborative knowledge generation by academics working alongside other stakeholders-reflects a "Mode 2" relationship (knowledge production rather than knowledge translation) between universities and society. Co-creation is widely believed to increase research impact. We undertook a narrative review of different models of co-creation relevant to community-based health services. We contrasted their diverse disciplinary roots and highlighted their common philosophical assumptions, principles of success, and explanations for failures. We applied these to an empirical case study of a community-based research-service partnership led by the Centre of Research Excellence in Quality and Safety in Integrated Primary-Secondary Care at the University of Queensland, Australia. Co-creation emerged independently in several fields, including business studies ("value co-creation"), design science ("experience-based co-design"), computer science ("technology co-design"), and community development ("participatory research"). These diverse models share some common features, which were also evident in the case study. Key success principles included (1) a systems perspective (assuming emergence, local adaptation, and nonlinearity); (2) the framing of research as a creative enterprise with human experience at its core; and (3) an emphasis on process (the framing of the program, the nature of

An Indexing Scheme for Case-Based Manufacturing Vision Development

DEFF Research Database (Denmark)

Wang, Chengbo; Johansen, John; Luxhøj, James T.

2004-01-01

with the competence improvement of an enterprises manufacturing system. There are two types of cases within the CBRM – an event case (EC) and a general supportive case (GSC). We designed one set of indexing vocabulary for the two types of cases, but a different indexing representation structure for each of them......This paper focuses on one critical element, indexing – retaining and representing knowledge in an applied case-based reasoning (CBR) model for supporting strategic manufacturing vision development (CBRM). Manufacturing vision (MV) is a kind of knowledge management concept and process concerned...

What's in a Label? Is Diagnosis the Start or the End of Clinical Reasoning?

Science.gov (United States)

Ilgen, Jonathan S; Eva, Kevin W; Regehr, Glenn

2016-04-01

Diagnostic reasoning has received substantial attention in the literature, yet what we mean by "diagnosis" may vary. Diagnosis can align with assignment of a "label," where a constellation of signs, symptoms, and test results is unified into a solution at a single point in time. This "diagnostic labeling" conceptualization is embodied in our case-based learning curricula, published case reports, and research studies, all of which treat diagnostic accuracy as the primary outcome. However, this conceptualization may oversimplify the richly iterative and evolutionary nature of clinical reasoning in many settings. Diagnosis can also represent a process of guiding one's thoughts by "making meaning" from data that are intrinsically dynamic, experienced idiosyncratically, negotiated among team members, and rich with opportunities for exploration. Thus, there are two complementary constructions of diagnosis: 1) the correct solution resulting from a diagnostic reasoning process, and 2) a dynamic aid to an ongoing clinical reasoning process. This article discusses the importance of recognizing these two conceptualizations of "diagnosis," outlines the unintended consequences of emphasizing diagnostic labeling as the primary goal of clinical reasoning, and suggests how framing diagnosis as an ongoing process of meaning-making might change how we think about teaching and assessing clinical reasoning.

Case base classification on digital mammograms: improving the performance of case base classifier

Science.gov (United States)

Raman, Valliappan; Then, H. H.; Sumari, Putra; Venkatesa Mohan, N.

2011-10-01

Breast cancer continues to be a significant public health problem in the world. Early detection is the key for improving breast cancer prognosis. The aim of the research presented here is in twofold. First stage of research involves machine learning techniques, which segments and extracts features from the mass of digital mammograms. Second level is on problem solving approach which includes classification of mass by performance based case base classifier. In this paper we build a case-based Classifier in order to diagnose mammographic images. We explain different methods and behaviors that have been added to the classifier to improve the performance of the classifier. Currently the initial Performance base Classifier with Bagging is proposed in the paper and it's been implemented and it shows an improvement in specificity and sensitivity.

Reasonable research expenditure in Italy. An assessment model

International Nuclear Information System (INIS)

Pieri, G.

2001-01-01

The percentage of GDP expenses for Research in Italy is commonly thought paltry but it is not so easy to establish which level of expenditure is reasonable for our industrial development and our international role. A direct comparison with other different economic systems can be misleading and the simple claim for an adjustment to the percentages of the greater investors can turn out to be too much ambitious and also ineffective objective. In order to stimulate a debate on such important topic, just as basic argument, it is proposed a simple model developed starting from projects profitability [it

The Analysis of Students Scientific Reasoning Ability in Solving the Modified Lawson Classroom Test of Scientific Reasoning (MLCTSR Problems by Applying the Levels of Inquiry

Directory of Open Access Journals (Sweden)

N. Novia

2017-04-01

Full Text Available This study aims to determine the students’ achievement in answering modified lawson classroom test of scientific reasoning (MLCTSR questions in overall science teaching and by every aspect of scientific reasoning abilities. There are six aspects related to the scientific reasoning abilities that were measured; they are conservatorial reasoning, proportional reasoning, controlling variables, combinatorial reasoning, probabilistic reasoning, correlational reasoning. The research is also conducted to see the development of scientific reasoning by using levels of inquiry models. The students reasoning ability was measured using the Modified Lawson Classroom Test of Scientific Reasoning (MLCTSR. MLCTSR is a test developed based on the test of scientific reasoning of Lawson’s Classroom Test of Scientific Reasoning (LCTSR in 2000 which amounted to 12 multiple-choice questions. The research method chosen in this study is descriptive quantitative research methods. The research design used is One Group Pretest-Posttest Design. The population of this study is the entire junior high students class VII the academic year 2014/2015 in one junior high school in Bandung. The samples in this study are one of class VII, which is class VII C. The sampling method used in this research is purposive sampling. The results showed that there is an increase in quantitative scientific reasoning although its value is not big.

Describing the clinical reasoning process: application of a model of enablement to a pediatric case.

Science.gov (United States)

Furze, Jennifer; Nelson, Kelly; O'Hare, Megan; Ortner, Amanda; Threlkeld, A Joseph; Jensen, Gail M

2013-04-01

Clinical reasoning is a core tenet of physical therapy practice leading to optimal patient care. The purpose of this case was to describe the outcomes, subjective experience, and reflective clinical reasoning process for a child with cerebral palsy using the International Classification of Functioning, Disability, and Health (ICF) model. Application of the ICF framework to a 9-year-old boy with spastic triplegic cerebral palsy was utilized to capture the interwoven factors present in this case. Interventions in the pool occurred twice weekly for 1 h over a 10-week period. Immediately post and 4 months post-intervention, the child made functional and meaningful gains. The family unit also developed an enjoyment of exercising together. Each individual family member described psychological, emotional, or physical health improvements. Reflection using the ICF model as a framework to discuss clinical reasoning can highlight important factors contributing to effective patient management.

Projecting the Future for Design Science Research: An Action‐Case Based Analysis

DEFF Research Database (Denmark)

Baskerville, Richard; Pries-Heje, Jan

2015-01-01

and theories appears to be a key challenge. In this paper we commence with a DESRIST paper from 2012 that instantiated design principles in an artifact for a bank. That paper included plans and techniques for future use of its principles (propagation), including prescriptions for a five-phase adoption process...... or theories have stimulated many actual projections. We demonstrate these concepts in a case study of propagation: a chemical manufacturer and service provider that adopted the design principles arising from that 2012 DESRIST banking-based design science research. We conclude that generalizability is too well...

Towards More Case Study Research in Entrepreneurship

Directory of Open Access Journals (Sweden)

Tom Duxbury

2012-03-01

Full Text Available Entrepreneurship as an emerging discipline has made good strides, but according to some, has fallen short of bringing its theory and literature up to the standards of others in the management sciences. Rich with the descriptive detail needed for insightful theory building in entrepreneurship, scholars have called for more case study research, particularly those incorporating non-retrospective and longitudinal observations. At the same time however, it has become rare to find such research published in A-level journals dedicated to entrepreneurship. A survey presented here of major entrepreneurship journals over the past six years revealed a publication rate of only 3% using the case study method. This presents a major impediment for developing fresh research in this field based upon the study of real cases. The author explores how the case study method has been applied to entrepreneurship research and provides recommendations for improved publication rates.

Are there reasons to challenge a symbolic computationalist approach in explaining deductive reasoning?

Science.gov (United States)

Faiciuc, Lucia E

2008-06-01

The majority of the existing theories explaining deductive reasoning could be included in a classic computationalist approach of the cognitive processes. In fact, deductive reasoning could be seen to be the pinnacle of the symbolic computationalism, its last fortress to be defended in the face of new, dynamic, and ecological perspectives over cognition. But are there weak points in that position regarding deductive reasoning? What would be the reasons for which new perspectives could gain in credibility? What could be their most important tenets? The answers given to those questions in the paper include two main points. The first one is that the present empirical data could not sustain unambiguously one view over the other, that they are obtained in artificial experimental conditions, and that there are data that are not easily explainable using the traditional computationalist paradigm. The second one is that approaching the deductive reasoning from dynamic and ecological perspectives could have significant advantages. The most obvious one is the possibility to integrate more easily the research regarding the deductive reasoning with the results obtained in other domains of the psychology (especially in what respects the lower cognitive processes), in artificial intelligence or in neurophysiology. The reasons for that would be that such perspectives, as they are sketched in the paper, would imply, essentially, processes of second-order pattern formation and recognition (as it is the case for perception), embodied cognition, and dynamic processes as the brain ones are.

Making the Case for Practice-Based Research and the Imperative Role of Design Practitioners.

Science.gov (United States)

Freihoefer, Kara; Zborowsky, Terri

2017-04-01

The purpose of this article is to justify the need for evidence-based design (EBD) in a research-based architecture and design practice. This article examines the current state of practice-based research (PBR), supports the need for EBD, illustrates PBR methods that can be applied to design work, and explores how findings can be used as a decision-making tool during design and as a validation tool during postoccupancy. As a result, design professions' body of knowledge will advance and practitioners will be better informed to protect the health, safety, and welfare of the society. Furthermore, characteristics of Friedman's progressive research program are used as a framework to examine the current state of PBR in design practice. A modified EBD approach is proposed and showcased with a case study of a renovated inpatient unit. The modified approach demonstrates how a highly integrated project team, especially the role of design practitioners, contributed to the success of utilizing baseline findings and evidence in decision-making throughout the design process. Lastly, recommendations and resources for learning research concepts are provided for practitioners. It is the role of practitioners to pave the way for the next generation of design professionals, as the request and expectation for research become more prevalent in design practice.

Executable specifications for hypothesis-based reasoning with Prolog and Constraint Handling Rules

DEFF Research Database (Denmark)

Christiansen, Henning

2009-01-01

Constraint Handling Rules (CHR) is an extension to Prolog which opens up a  spectrum of hypotheses-based reasoning in logic programs without additional interpretation overhead. Abduction with integrity constraints is one example of hypotheses-based reasoning which can be implemented directly...... in Prolog and CHR with a straightforward use of available and efficiently implemented facilities The present paper clarifies the semantic foundations for this way of doing abduction in CHR and Prolog as well as other examples  of hypotheses-based reasoning that is possible, including assumptive logic...

Participatory research, people with intellectual disabilities and ethical approval: making reasonable adjustments to enable participation.

Science.gov (United States)

Northway, Ruth; Howarth, Joyce; Evans, Lynne

2015-02-01

The aim of this paper is to explore how making reasonable adjustments to the process of securing ethical approval for research can facilitate the meaningful involvement of people with intellectual disabilities as members of a research team. This is achieved through critical reflection upon the approach taken within one participatory research study whose objective was to explore how people with intellectual disabilities understand abuse. Internationally participatory research studies (in which active involvement of community members in all stages of the research process is sought) are becoming increasingly common in the context of health care and, more specifically, within research involving people with intellectual disabilities. However, whilst it is acknowledged that participatory research gives rise to specific ethical challenges, how (or if) involvement in securing ethical approval is facilitated, is not discussed in most research reports. The significance of this paper is that it seeks to address this gap by exploring how meaningful participation can be promoted by making reasonable adjustments. Within the study, the research team worked in collaboration with the ethics committee to identify potential barriers that could prevent the participation of members of the research team who had intellectual disabilities. Reasonable adjustments (such as redesigning forms) were made to the processes involved in securing ethical approval. This study demonstrated that it is possible to ensure that ethical standards are upheld and the requirements of ethics committees met whilst also facilitating the meaningful involvement of people with intellectual disabilities. The reasonable adjustments approach explored within this paper can be translated into the context of clinical practice: making changes to the way that services are delivered can promote greater involvement of people with intellectual disabilities in their own health care. © 2014 John Wiley & Sons Ltd.

Intelligent Adaptation Process for Case Based Systems

International Nuclear Information System (INIS)

Nassar, A.M.; Mohamed, A.H.; Mohamed, A.H.

2014-01-01

Case Based Reasoning (CBR) Systems is one of the important decision making systems applied in many fields all over the world. The effectiveness of any CBR system based on the quality of the storage cases in the case library. Similar cases can be retrieved and adapted to produce the solution for the new problem. One of the main issues faced the CBR systems is the difficulties of achieving the useful cases. The proposed system introduces a new approach that uses the genetic algorithm (GA) technique to automate constructing the cases into the case library. Also, it can optimize the best one to be stored in the library for the future uses. However, the proposed system can avoid the problems of the uncertain and noisy cases. Besides, it can simply the retrieving and adaptation processes. So, it can improve the performance of the CBR system. The suggested system can be applied for many real-time problems. It has been applied for diagnosis the faults of the wireless network, diagnosis of the cancer diseases, diagnosis of the debugging of a software as cases of study. The proposed system has proved its performance in this field

REASONING IN THE FUZZY FRONT END OF INNOVATION:

DEFF Research Database (Denmark)

Haase, Louise Møller; Laursen, Linda Nhu

2018-01-01

in the fuzzy front end is the reasoning process: innovation teams are faced with open-ended, ill-defined problems, where they need to make decisions about an unknown future but have only incomplete, ambiguous and contradicting insights available. We study the reasoning of experts, how they frame to make sense...... of all the insights and create a basis for decision-making in relation to a new project. Based on case studies of five innovative products from various industries, we propose a Product DNA model for understanding the reasoning in the fuzzy front end of innovation. The Product DNA Model explains how...... experts reason and what direct their reasoning....

Emotional reasoning and parent-based reasoning in non-clinical children and their prospective relationships with anxiety symptoms

NARCIS (Netherlands)

Morren, M.; Muris, P.; Kindt, M.; Schouten, E.; van den Hout, M.

2008-01-01

Emotional and parent-based reasoning refer to the tendency to rely on personal or parental anxiety response information rather than on objective danger information when estimating the dangerousness of a situation. This study investigated the prospective relationships of emotional and parent-based

Patterns of informal reasoning in the context of socioscientific decision making

Science.gov (United States)

Sadler, Troy D.; Zeidler, Dana L.

2005-01-01

The purpose of this study is to contribute to a theoretical knowledge base through research by examining factors salient to science education reform and practice in the context of socioscientific issues. The study explores how individuals negotiate and resolve genetic engineering dilemmas. A qualitative approach was used to examine patterns of informal reasoning and the role of morality in these processes. Thirty college students participated individually in two semistructured interviews designed to explore their informal reasoning in response to six genetic engineering scenarios. Students demonstrated evidence of rationalistic, emotive, and intuitive forms of informal reasoning. Rationalistic informal reasoning described reason-based considerations; emotive informal reasoning described care-based considerations; and intuitive reasoning described considerations based on immediate reactions to the context of a scenario. Participants frequently relied on combinations of these reasoning patterns as they worked to resolve individual socioscientific scenarios. Most of the participants appreciated at least some of the moral implications of their decisions, and these considerations were typically interwoven within an overall pattern of informal reasoning. These results highlight the need to ensure that science classrooms are environments in which intuition and emotion in addition to reason are valued. Implications and recommendations for future research are discussed.

AUTOMATIC MULTILEVEL IMAGE SEGMENTATION BASED ON FUZZY REASONING

Directory of Open Access Journals (Sweden)

Liang Tang

2011-05-01

Full Text Available An automatic multilevel image segmentation method based on sup-star fuzzy reasoning (SSFR is presented. Using the well-known sup-star fuzzy reasoning technique, the proposed algorithm combines the global statistical information implied in the histogram with the local information represented by the fuzzy sets of gray-levels, and aggregates all the gray-levels into several classes characterized by the local maximum values of the histogram. The presented method has the merits of determining the number of the segmentation classes automatically, and avoiding to calculating thresholds of segmentation. Emulating and real image segmentation experiments demonstrate that the SSFR is effective.

Using Research-Based Video-Cases to Help Pre-Service Primary Teachers Conceptualize a Contemporary View of Mathematics Teaching

Science.gov (United States)

Lin, Pi-Jen

2005-01-01

The study inquired into the effect of research-based video-cases on pre-service teachers conceptualizing their understanding of contemporary mathematics teaching. The 43 participants enrolled in a Mathematics Method Course viewed and discussed 5 video-cases of primary teachers teaching. Journal entries, lesson plans, and microteaching observations…

Incorporating an Interactive Statistics Workshop into an Introductory Biology Course-Based Undergraduate Research Experience (CURE) Enhances Students’ Statistical Reasoning and Quantitative Literacy Skills †

Science.gov (United States)

Olimpo, Jeffrey T.; Pevey, Ryan S.; McCabe, Thomas M.

2018-01-01

Course-based undergraduate research experiences (CUREs) provide an avenue for student participation in authentic scientific opportunities. Within the context of such coursework, students are often expected to collect, analyze, and evaluate data obtained from their own investigations. Yet, limited research has been conducted that examines mechanisms for supporting students in these endeavors. In this article, we discuss the development and evaluation of an interactive statistics workshop that was expressly designed to provide students with an open platform for graduate teaching assistant (GTA)-mentored data processing, statistical testing, and synthesis of their own research findings. Mixed methods analyses of pre/post-intervention survey data indicated a statistically significant increase in students’ reasoning and quantitative literacy abilities in the domain, as well as enhancement of student self-reported confidence in and knowledge of the application of various statistical metrics to real-world contexts. Collectively, these data reify an important role for scaffolded instruction in statistics in preparing emergent scientists to be data-savvy researchers in a globally expansive STEM workforce. PMID:29904549

Knowledge representation to support reasoning based on multiple models

Science.gov (United States)

Gillam, April; Seidel, Jorge P.; Parker, Alice C.

1990-01-01

Model Based Reasoning is a powerful tool used to design and analyze systems, which are often composed of numerous interactive, interrelated subsystems. Models of the subsystems are written independently and may be used together while they are still under development. Thus the models are not static. They evolve as information becomes obsolete, as improved artifact descriptions are developed, and as system capabilities change. Researchers are using three methods to support knowledge/data base growth, to track the model evolution, and to handle knowledge from diverse domains. First, the representation methodology is based on having pools, or types, of knowledge from which each model is constructed. In addition information is explicit. This includes the interactions between components, the description of the artifact structure, and the constraints and limitations of the models. The third principle we have followed is the separation of the data and knowledge from the inferencing and equation solving mechanisms. This methodology is used in two distinct knowledge-based systems: one for the design of space systems and another for the synthesis of VLSI circuits. It has facilitated the growth and evolution of our models, made accountability of results explicit, and provided credibility for the user community. These capabilities have been implemented and are being used in actual design projects.

Policy recommendations for addressing privacy challenges associated with cell-based research and interventions.

Science.gov (United States)

Ogbogu, Ubaka; Burningham, Sarah; Ollenberger, Adam; Calder, Kathryn; Du, Li; El Emam, Khaled; Hyde-Lay, Robyn; Isasi, Rosario; Joly, Yann; Kerr, Ian; Malin, Bradley; McDonald, Michael; Penney, Steven; Piat, Gayle; Roy, Denis-Claude; Sugarman, Jeremy; Vercauteren, Suzanne; Verhenneman, Griet; West, Lori; Caulfield, Timothy

2014-02-03

The increased use of human biological material for cell-based research and clinical interventions poses risks to the privacy of patients and donors, including the possibility of re-identification of individuals from anonymized cell lines and associated genetic data. These risks will increase as technologies and databases used for re-identification become affordable and more sophisticated. Policies that require ongoing linkage of cell lines to donors' clinical information for research and regulatory purposes, and existing practices that limit research participants' ability to control what is done with their genetic data, amplify the privacy concerns. To date, the privacy issues associated with cell-based research and interventions have not received much attention in the academic and policymaking contexts. This paper, arising out of a multi-disciplinary workshop, aims to rectify this by outlining the issues, proposing novel governance strategies and policy recommendations, and identifying areas where further evidence is required to make sound policy decisions. The authors of this paper take the position that existing rules and norms can be reasonably extended to address privacy risks in this context without compromising emerging developments in the research environment, and that exceptions from such rules should be justified using a case-by-case approach. In developing new policies, the broader framework of regulations governing cell-based research and related areas must be taken into account, as well as the views of impacted groups, including scientists, research participants and the general public. This paper outlines deliberations at a policy development workshop focusing on privacy challenges associated with cell-based research and interventions. The paper provides an overview of these challenges, followed by a discussion of key themes and recommendations that emerged from discussions at the workshop. The paper concludes that privacy risks associated with cell-based

Three cases of engaged research

DEFF Research Database (Denmark)

Hansen, Louise Ejgod

2015-01-01

frameworks for the way in which children and youngsters engage in creative practices emphasizing collective co-creation. Theoretically, the article is based on the concept of engaged scholarship (Van de Ven 2007), Practice as Research (Nelson 2013), and types of partnership (King 1998) all of which......The article is a case study of three different applied research projects analyzing and discussing the relationship between practice and research. The three projects are all arts projects occupied with participation in different forms: Theatre Talk is an audience development project conducted...... contribute to the analysis of the relationship, purpose, and outcomes of the relationship between practice and research....

A case-study of a socio-scientific issues curricular and pedagogical intervention in an undergraduate microbiology course: A focus on informal reasoning

Science.gov (United States)

Schalk, Kelly A.

The purpose of this investigation was to measure specific ways a student interest SSI-based curricular and pedagogical affects undergraduates' ability informally reason. The delimited components of informal reasoning measured were undergraduates' Nature of Science conceptualizations and ability to evaluate scientific information. The socio-scientific issues (SSI) theoretical framework used in this case-study has been advocated as a means for improving students' functional scientific literacy. This investigation focused on the laboratory component of an undergraduate microbiology course in spring 2008. There were 26 participants. The instruments used in this study included: (1) Individual and Group research projects, (2) journals, (3) laboratory write-ups, (4) a laboratory quiz, (5) anonymous evaluations, and (6) a pre/post article exercise. All instruments yielded qualitative data, which were coded using the qualitative software NVivo7. Data analyses were subjected to instrumental triangulation, inter-rater reliability, and member-checking. It was determined that undergraduates' epistemological knowledge of scientific discovery, processes, and justification matured in response to the intervention. Specifically, students realized: (1) differences between facts, theories, and opinions; (2) testable questions are not definitively proven; (3) there is no stepwise scientific process; and (4) lack of data weakens a claim. It was determined that this knowledge influenced participants' beliefs and ability to informally reason. For instance, students exhibited more critical evaluations of scientific information. It was also found that undergraduates' prior opinions had changed over the semester. Further, the student interest aspect of this framework engaged learners by offering participants several opportunities to influentially examine microbiology issues that affected their life. The investigation provided empirically based insights into the ways undergraduates' interest

Examining Preservice Teachers' Decision Behaviors and Individual Differences in Three Online Case-Based Approaches

Science.gov (United States)

Cevik, Yasemin Demiraslan; Andre, Thomas

2013-01-01

This study compared the impact of three types of case-based methods (case-based reasoning, worked example, and faded worked example) on preservice teachers' (n = 71) interaction with decision tasks and whether decision related measures (task difficulty, mental effort, decision making performance) were associated with the differences in student…

Astronomy Education Research Observations from the iSTAR international Study of Astronomical Reasoning Database

Science.gov (United States)

Tatge, C. B.; Slater, S. J.; Slater, T. F.; Schleigh, S.; McKinnon, D.

2016-12-01

Historically, an important part of the scientific research cycle is to situate any research project within the landscape of the existing scientific literature. In the field of discipline-based astronomy education research, grappling with the existing literature base has proven difficult because of the difficulty in obtaining research reports from around the world, particularly early ones. In order to better survey and efficiently utilize the wide and fractured range and domain of astronomy education research methods and results, the iSTAR international Study of Astronomical Reasoning database project was initiated. The project aims to host a living, online repository of dissertations, theses, journal articles, and grey literature resources to serve the world's discipline-based astronomy education research community. The first domain of research artifacts ingested into the iSTAR database were doctoral dissertations. To the authors' great surprise, nearly 300 astronomy education research dissertations were found from the last 100-years. Few, if any, of the literature reviews from recent astronomy education dissertations surveyed even come close to summarizing this many dissertations, most of which have not been published in traditional journals, as re-publishing one's dissertation research as a journal article was not a widespread custom in the education research community until recently. A survey of the iSTAR database dissertations reveals that the vast majority of work has been largely quantitative in nature until the last decade. We also observe that modern-era astronomy education research writings reaches as far back as 1923 and that the majority of dissertations come from the same eight institutions. Moreover, most of the astronomy education research work has been done covering learners' grasp of broad knowledge of astronomy rather than delving into specific learning targets, which has been more in vogue during the last two decades. The surprisingly wide breadth

The effect of short-term workshop on improving clinical reasoning skill of medical students.

Science.gov (United States)

Yousefichaijan, Parsa; Jafari, Farshad; Kahbazi, Manijeh; Rafiei, Mohammad; Pakniyat, AbdolGhader

2016-01-01

Clinical reasoning process leads clinician to get purposeful steps from signs and symptoms toward diagnosis and treatment. This research intends to investigate the effect of teaching clinical reasoning on problem-solving skills of medical students. This research is a semi-experimental study. Nineteen Medical student of the pediatric ward as case group participated in a two-day workshop for training clinical reasoning. Before the workshop, they filled out Diagnostic Thinking Inventory (DTI) questionnaires. Fifteen days after the workshop the DTI questionnaire completed and "key feature" (KF) test and "clinical reasoning problem" (CRP) test was held. 23 Medical student as the control group, without passing the clinical reasoning workshop DTI questionnaire completed, and KF test and CRP test was held. The average score of the DTI questionnaire in the control group was 162.04 and in the case group before the workshop was 153.26 and after the workshop was 181.68. Compare the average score of the DTI questionnaire before and after the workshop there is a significant difference. The difference between average KF test scores in the control and the case group was not significant but between average CRP test scores was significant. Clinical reasoning workshop is effectiveness in promoting problem-solving skills of students.

Undergraduate Students' Quantitative Reasoning in Economic Contexts

Science.gov (United States)

Mkhatshwa, Thembinkosi Peter; Doerr, Helen M.

2018-01-01

Contributing to a growing body of research on undergraduate students' quantitative reasoning, the study reported in this article used task-based interviews to investigate business calculus students' quantitative reasoning when solving two optimization tasks situated in the context of revenue and profit maximization. Analysis of verbal responses…

Probing student reasoning approaches through the lens of dual-process theories: A case study in buoyancy

Science.gov (United States)

Gette, Cody R.; Kryjevskaia, Mila; Stetzer, MacKenzie R.; Heron, Paula R. L.

2018-06-01

A growing body of scholarly work indicates that student performance on physics problems stems from many factors, including relevant conceptual understanding. However, in contexts in which significant conceptual difficulties have been documented via research, it can be difficult to pinpoint and isolate such factors because students' written and interview responses rarely reveal the full richness of their conscious and, perhaps more importantly, subconscious reasoning paths. In this investigation, informed by dual-process theories of reasoning and decision making as well as the theoretical construct of accessibility, we conducted a series of experiments in order to gain greater insight into the factors impacting student performance on the "five-block problem," which has been used in the literature to probe student thinking about buoyancy. In particular, we examined both the impact of problem design (including salient features and cueing) and the impact of targeted instruction focused on density-based arguments for sinking and floating and on neutral buoyancy. The investigation found that instructional modifications designed to remove the strong intuitive appeal of the first-available response led to significantly improved performance, without improving student conceptual understanding of the requisite buoyancy concepts. As such, our findings represent an important first step in identifying systematic strategies for using theories from cognitive science to guide the development and refinement of research-based instructional materials.

Probing student reasoning approaches through the lens of dual-process theories: A case study in buoyancy

Directory of Open Access Journals (Sweden)

Cody R. Gette

2018-03-01

Full Text Available A growing body of scholarly work indicates that student performance on physics problems stems from many factors, including relevant conceptual understanding. However, in contexts in which significant conceptual difficulties have been documented via research, it can be difficult to pinpoint and isolate such factors because students’ written and interview responses rarely reveal the full richness of their conscious and, perhaps more importantly, subconscious reasoning paths. In this investigation, informed by dual-process theories of reasoning and decision making as well as the theoretical construct of accessibility, we conducted a series of experiments in order to gain greater insight into the factors impacting student performance on the “five-block problem,” which has been used in the literature to probe student thinking about buoyancy. In particular, we examined both the impact of problem design (including salient features and cueing and the impact of targeted instruction focused on density-based arguments for sinking and floating and on neutral buoyancy. The investigation found that instructional modifications designed to remove the strong intuitive appeal of the first-available response led to significantly improved performance, without improving student conceptual understanding of the requisite buoyancy concepts. As such, our findings represent an important first step in identifying systematic strategies for using theories from cognitive science to guide the development and refinement of research-based instructional materials.

Using Interpretive Qualitative Case Studies for Exploratory Research in Doctoral Studies: A Case of Information Systems Research in Small and Medium Enterprises

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Shana R. Ponelis

2015-12-01

Full Text Available The use of the case study method has gained mainstream acceptance in both entrepreneurship and information systems research to develop conceptual and theoretical models that are novel, yet grounded in the literature. In spite of many texts on the case study method and the growing acceptance and use of thereof, there are relatively few examples that discuss how to apply the case study method. The purpose of this paper is to provide such an example by drawing upon the author’s research for her doctoral dissertation in the discipline of information systems and entrepreneurship research. First, the use of qualitative case studies as research method is motivated, then the importance of the research paradigm is discussed and the interpretivist research paradigm justified followed by a detailed discussion of the research design. The paper concludes with a discussion of lessons learned and recommendations based on the author’s experience with using the case study method. The practical yet theoretically founded approach of this paper may be useful to doctoral students who are considering or using the case study method. Equally, supervisors and others involved in research training may find this paper useful as an illustrative example of the case study method for their students.

Case-Based Fault Diagnostic System

International Nuclear Information System (INIS)

Mohamed, A.H.

2014-01-01

Nowadays, case-based fault diagnostic (CBFD) systems have become important and widely applied problem solving technologies. They are based on the assumption that “similar faults have similar diagnosis”. On the other hand, CBFD systems still suffer from some limitations. Common ones of them are: (1) failure of CBFD to have the needed diagnosis for the new faults that have no similar cases in the case library. (2) Limited memorization when increasing the number of stored cases in the library. The proposed research introduces incorporating the neural network into the case based system to enable the system to diagnose all the faults. Neural networks have proved their success in the classification and diagnosis problems. The suggested system uses the neural network to diagnose the new faults (cases) that cannot be diagnosed by the traditional CBR diagnostic system. Besides, the proposed system can use the another neural network to control adding and deleting the cases in the library to manage the size of the cases in the case library. However, the suggested system has improved the performance of the case based fault diagnostic system when applied for the motor rolling bearing as a case of study

Evidence-based policy-making in the NHS: exploring the interface between research and the commissioning process.

Science.gov (United States)

Harries, U; Elliott, H; Higgins, A

1999-03-01

The UK National Health Service (NHS) R&D strategy acknowledges the importance of developing an NHS where practice and policy is more evidence-based. This paper is based on a qualitative study which aimed to identify factors which facilitate or impede evidence-based policy-making at a local level in the NHS. The study involved a literature review and case studies of social research projects which were initiated by NHS health authority managers or general practitioner (GP) fundholders in one region of the NHS. Data were collected through in-depth interviews with lead policy-makers, GPs and researchers working on each of the case studies and analysis of project documentation. An over-arching theme from the analysis was that of the complexity of R&D in purchasing. The two worlds of research and health services management often sit uncomfortably together. For this reason it was not possible to describe a 'blueprint' for successful R&D, although several important issues emerged. These include sharing an appropriate model for research utilization, the importance of relationships in shaping R&D, the importance of influence and commitment in facilitating evidence-based change, and the resourcing of R&D in purchasing. These issues have important implications for the strategic development of R&D as well as for individual project application. Moving beyond the rhetoric of evidence-based policy-making is more likely if both policy-makers and researchers openly acknowledge this complexity and give due concern to the issues outlined.

OWL-based reasoning methods for validating archetypes.

Science.gov (United States)

Menárguez-Tortosa, Marcos; Fernández-Breis, Jesualdo Tomás

2013-04-01

Some modern Electronic Healthcare Record (EHR) architectures and standards are based on the dual model-based architecture, which defines two conceptual levels: reference model and archetype model. Such architectures represent EHR domain knowledge by means of archetypes, which are considered by many researchers to play a fundamental role for the achievement of semantic interoperability in healthcare. Consequently, formal methods for validating archetypes are necessary. In recent years, there has been an increasing interest in exploring how semantic web technologies in general, and ontologies in particular, can facilitate the representation and management of archetypes, including binding to terminologies, but no solution based on such technologies has been provided to date to validate archetypes. Our approach represents archetypes by means of OWL ontologies. This permits to combine the two levels of the dual model-based architecture in one modeling framework which can also integrate terminologies available in OWL format. The validation method consists of reasoning on those ontologies to find modeling errors in archetypes: incorrect restrictions over the reference model, non-conformant archetype specializations and inconsistent terminological bindings. The archetypes available in the repositories supported by the openEHR Foundation and the NHS Connecting for Health Program, which are the two largest publicly available ones, have been analyzed with our validation method. For such purpose, we have implemented a software tool called Archeck. Our results show that around 1/5 of archetype specializations contain modeling errors, the most common mistakes being related to coded terms and terminological bindings. The analysis of each repository reveals that different patterns of errors are found in both repositories. This result reinforces the need for making serious efforts in improving archetype design processes. Copyright © 2012 Elsevier Inc. All rights reserved.

Conceptualizing reasoning-and-proving opportunities in textbook expositions : Cases from secondary calculus

OpenAIRE

Bergwall, Andreas

2017-01-01

Several recent textbook studies focus on opportunities to learn reasoning-and-proving. They typically investigate the extent to which justifications are general proofs and what opportunities exist for learning important elements of mathematical reasoning. In this paper, I discuss how a particular analytical framework for this might be refined. Based on an in-depth analysis of certain textbook passages in upper secondary calculus textbooks, I make an account for analytical issues encountered d...

Navigating political minefields: partnerships in organizational case study research.

Science.gov (United States)

Moll, Sandra

2012-01-01

The purpose of this paper is to examine key challenges associated with conducting politically sensitive research within a workplace setting, and to highlight strategic partnerships that can be developed to address these challenges. The author's research on employee mental health issues within a large healthcare facility serves as the foundation for identification and description of "political minefields" that investigators may encounter when conducting organizational case study research. Key methodological principles from the literature on qualitative case study research will frame discussion of how to understand and address political sensitivities in the research process. The benefits of conducting organizational case study research will be outlined, followed by discussion of methodological challenges that can emerge in negotiating entry, collecting data (gatekeepers, researcher reflexivity, participant authenticity and non-maleficence), and communicating research findings. Courage, collaboration and clear communication with stakeholders at all levels of the organization are critical to the success of workplace based case study research.

Conceptual Knowledge Representation and Reasoning

DEFF Research Database (Denmark)

Oldager, Steen Nikolaj

2003-01-01

One of the main areas in knowledge representation and logic-based artificial intelligence concerns logical formalisms that can be used for representing and reasoning with concepts. For almost 30 years, since research in this area began, the issue of intensionality has had a special status...

Case Study Research Methodology in Nursing Research.

Science.gov (United States)

Cope, Diane G

2015-11-01

Through data collection methods using a holistic approach that focuses on variables in a natural setting, qualitative research methods seek to understand participants' perceptions and interpretations. Common qualitative research methods include ethnography, phenomenology, grounded theory, and historic research. Another type of methodology that has a similar qualitative approach is case study research, which seeks to understand a phenomenon or case from multiple perspectives within a given real-world context.

The Analysis of Geometrical Reasoning Ability Viewed from Self-Efficacy on Connected Mathematic Project (CMP Learning Etnomathematics-Based

Directory of Open Access Journals (Sweden)

Desi Dwi Damaryanti

2017-11-01

Full Text Available The purpose of this research was to know the geometrical reasoning ability of the students viewed from the self-efficacy through the learning of  Connected Mathematic Project (CMP ethnomathematic-based. The type of this research was qualitative which was descriptive. To obtained the validity of the qualitative data, the checking technique used in this research was sources triangulation, which had been done by comparing the suitability of the obtained data from the results of the interview and the test. Population of this research was the students of grade VIII at SMP Negeri 1 Sidoharjo and the sample was the students from VIII A Class. At the final, 12 research subjects were chosen to represent the group of level 1 self-efficacy, level 2 self-efficacy, level 3 self-efficacy, level 4 self efficacy, level 5 self-efficacy, and level 6 self-efficacy. In this research, there was a finding which shows us that the students with high self-efficacy had low ability to finish the geometrical reasoning ability test, while the students with low self-efficacy had the ability to finish the geometrical reasoning ability test. The factors which affected the finding were the motivations and the interest of learning mathematics which was affecting the attitude of the students in the classroom.

Reasoning about modular datatypes with Mendler induction

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Paolo Torrini

2015-09-01

Full Text Available In functional programming, datatypes a la carte provide a convenient modular representation of recursive datatypes, based on their initial algebra semantics. Unfortunately it is highly challenging to implement this technique in proof assistants that are based on type theory, like Coq. The reason is that it involves type definitions, such as those of type-level fixpoint operators, that are not strictly positive. The known work-around of impredicative encodings is problematic, insofar as it impedes conventional inductive reasoning. Weak induction principles can be used instead, but they considerably complicate proofs. This paper proposes a novel and simpler technique to reason inductively about impredicative encodings, based on Mendler-style induction. This technique involves dispensing with dependent induction, ensuring that datatypes can be lifted to predicates and relying on relational formulations. A case study on proving subject reduction for structural operational semantics illustrates that the approach enables modular proofs, and that these proofs are essentially similar to conventional ones.

Indicators that influence prospective mathematics teachers representational and reasoning abilities

Science.gov (United States)

Darta; Saputra, J.

2018-01-01

Representational and mathematical reasoning ability are very important ability as basic in mathematics learning process. The 2013 curriculum suggests that the use of a scientific approach emphasizes higher order thinking skills. Therefore, a scientific approach is required in mathematics learning to improve ability of representation and mathematical reasoning. The objectives of this research are: (1) to analyze representational and reasoning abilities, (2) to analyze indicators affecting the ability of representation and mathematical reasoning, (3) to analyze scientific approaches that can improve the ability of representation and mathematical reasoning. The subject of this research is the students of mathematics prospective teachers in the first semester at Private Higher Education of Bandung City. The research method of this research was descriptive analysis. The research data were collected using reasoning and representation tests on sixty-one students. Data processing was done by descriptive analysis specified based on the indicators of representation ability and mathematical reasoning that influenced it. The results of this first-year study showed that students still had many weaknesses in reasoning and mathematical representation that were influenced by the ability to understand the indicators of both capabilities. After observing the results of the first-year research, then in the second and third year, the development of teaching materials with a scientific approach in accordance with the needs of prospective students was planned.

Reasons for mother-infant bed-sharing: a systematic narrative synthesis of the literature and implications for future research.

Science.gov (United States)

Ward, Trina C Salm

2015-03-01

Mother-infant bed-sharing has been a common practice for centuries. Understanding the reasons parents choose to bed-share can help tailor safe sleep education. The purpose of this article was to systematically review the international literature on: (1) reasons parents bed-share, (2) the cultural context of bed-sharing, and (3) implications for interventions and future research. The search occurred August-September 2013 via PubMed, CINAHL, and Psyc INFO using the terms: "infant," "sleep," "bed shar*," "co sleep*," "sleep location," "sleep practices," and "sleep arrangements," alone or in combination. Google Scholar was searched using: "bed share," "bed sharing," "co sleep," and "co sleeping." Inclusion criteria were: (1) referenced bed-sharing with infants 12 months or younger; (2) provided reasons for bed-sharing; and (3) published between 1990 and 2013. Studies were excluded if they focused on disorders such as epilepsy, breathing disorders, or among multi-gestational infants. Narrative synthesis was used to summarize findings. Thirty-four studies met inclusion criteria. The main themes around bed-sharing based on this synthesis included: (1) breastfeeding, (2) comforting, (3) better/more sleep, (4) monitoring, (5) bonding/attachment, (6) environmental, (7) crying, (8) tradition, (9) disagree with danger, and (10) maternal instinct. Findings suggest that future research should examine parents' decision-making process on infant sleep location, including how they weigh personal reasons and sources of advice. Public health interventions should incorporate the particular reasons of the population they are targeting. Clinicians should discuss infant sleep environment with each family, along with their motivations for choosing this environment, and work within that framework to address the safety of the sleep environment.

Model Based Reasoning by Introductory Students When Analyzing Earth Systems and Societal Challenges

Science.gov (United States)

Holder, L. N.; Herbert, B. E.

2014-12-01

Understanding how students use their conceptual models to reason about societal challenges involving societal issues such as natural hazard risk assessment, environmental policy and management, and energy resources can improve instructional activity design that directly impacts student motivation and literacy. To address this question, we created four laboratory exercises for an introductory physical geology course at Texas A&M University that engages students in authentic scientific practices by using real world problems and issues that affect societies based on the theory of situated cognition. Our case-study design allows us to investigate the various ways that students utilize model based reasoning to identify and propose solutions to societally relevant issues. In each of the four interventions, approximately 60 students in three sections of introductory physical geology were expected to represent and evaluate scientific data, make evidence-based claims about the data trends, use those claims to express conceptual models, and use their models to analyze societal challenges. Throughout each step of the laboratory exercise students were asked to justify their claims, models, and data representations using evidence and through the use of argumentation with peers. Cognitive apprenticeship was the foundation for instruction used to scaffold students so that in the first exercise they are given a partially completed model and in the last exercise students are asked to generate a conceptual model on their own. Student artifacts, including representation of earth systems, representation of scientific data, verbal and written explanations of models and scientific arguments, and written solutions to specific societal issues or environmental problems surrounding earth systems, were analyzed through the use of a rubric that modeled authentic expertise and students were sorted into three categories. Written artifacts were examined to identify student argumentation and

Danish Majority Children’s Reasoning About Exclusion Based on Gender and Ethnicity

DEFF Research Database (Denmark)

Møller, Signe Juhl; Tenenbaum, Harriet R.

2011-01-01

This study investigated 282 eight- to twelve-year-old Danish majority children's judgments and justifications of exclusion based on gender and ethnicity (i.e., Danish majority children and ethnic-minority children of a Muslim background). Children's judgments and reasoning varied with the perpetr......This study investigated 282 eight- to twelve-year-old Danish majority children's judgments and justifications of exclusion based on gender and ethnicity (i.e., Danish majority children and ethnic-minority children of a Muslim background). Children's judgments and reasoning varied...... with the perpetrator of the exclusion and the social identity of the target. Children assessed exclusion based on ethnicity as less acceptable than exclusion based on gender and used more moral reasoning for the former than the latter. Children judged it less acceptable for a teacher than a child to exclude a child...

Undermining Reasonableness: Expert Testimony in a Case Involving a Battered Woman Who Kills

Science.gov (United States)

Terrance, Cheryl; Matheson, Kimberly

2003-01-01

Student participants (N = 316) viewed a videotaped simulated case involving a woman who had entered a self-defense plea in the shooting death of her abusive husband. As successful claims of self-defense rest on the portrayal of a defendant who has responded reasonably to his/her situation, the implications of various forms of expert testimony in…

Case Study Research Methodology

Directory of Open Access Journals (Sweden)

Mark Widdowson

2011-01-01

Full Text Available Commenting on the lack of case studies published in modern psychotherapy publications, the author reviews the strengths of case study methodology and responds to common criticisms, before providing a summary of types of case studies including clinical, experimental and naturalistic. Suggestions are included for developing systematic case studies and brief descriptions are given of a range of research resources relating to outcome and process measures. Examples of a pragmatic case study design and a hermeneutic single-case efficacy design are given and the paper concludes with some ethical considerations and an exhortation to the TA community to engage more widely in case study research.

Uses of Published Research: An Exploratory Case Study

Directory of Open Access Journals (Sweden)

Patrick J. Fahy

Full Text Available Academic publications are too often ignored by other researchers. There are various reasons: Researchers know that conclusions may eventually be proved wrong; publications are sometimes retracted; effects may decline when studied later; researchers occasionally don’t seem to know about papers they have allegedly authored; there are even accusations of fraud (Cohen, 2011. In this exploratory case study, 10 papers were examined to determine the various ways they were used by others, whether there were cases of reported effects declining, and whether, among those who referenced the papers, there were suggestions that anything in the papers ought to be retracted. Findings showed that all the papers had been referenced by others (337 user publications were found, containing a total of 868 references. Other findings include the following: Single references were far more common than multiple references; applications/replications were the least common type of usage (23 occurrences, followed by contrasts/elaborations (34, and quotations (65; unlike reports regarding publications in the sciences, whether the paper was solo- or co-authored did not affect usage; appearance in a non-prestige journal was actually associated with more usage of some kinds; and well over 80% of uses were in heavily scrutinized sources (journal articles or theses/dissertations. The paper concludes with recommendations to writers about how to avoid producing publications that are ignored.

GIS-based landscape design research: Stourhead landscape garden as a case study

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Steffen Nijhuis

2017-11-01

Full Text Available Landscape design research is important for cultivating spatial intelligence in landscape architecture. This study explores GIS (geographic information systems as a tool for landscape design research - investigating landscape designs to understand them as architectonic compositions (architectonic plan analysis. The concept ‘composition’ refers to a conceivable arrangement, an architectural expression of a mental construct that is legible and open to interpretation. Landscape architectonic compositions and their representations embody a great wealth of design knowledge as objects of our material culture and reflect the possible treatment of the ground, space, image and program as a characteristic coherence. By exploring landscape architectonic compositions with GIS, design researchers can acquire design knowledge that can be used in the creation and refinement of a design.  The research aims to identify and illustrate the potential role of GIS as a tool in landscape design research, so as to provide insight into the possibilities and limitations of using GIS in this capacity. The critical, information-oriented case of Stourhead landscape garden (Wiltshire, UK, an example of a designed landscape that covers the scope and remit of landscape architecture design, forms the heart of the study. The exploration of Stourhead by means of GIS can be understood as a plausibility probe. Here the case study is considered a form of ‘quasi-experiment’, testing the hypothesis and generating a learning process that constitutes a prerequisite for advanced understanding, while using an adjusted version of the framework for landscape design analysis by Steenbergen and Reh (2003. This is a theoretically informed analytical method based on the formal interpretation of the landscape architectonic composition addressing four landscape architectonic categories: the basic, the spatial, the symbolic and the programmatic form. This study includes new aspects to be

Architectural design thinking as a form of model-based reasoning

NARCIS (Netherlands)

Pauwels, P.; Bod, R.

2014-01-01

Model-based reasoning can be considered central in very diverse domains of practice. Recently considered domains of practice are political discourse, social intercourse, language learning, archaeology, collaboration and conversation, and so forth. In this paper, we explore features of model-based

Investigating Image-Based Perception and Reasoning in Geometry

Science.gov (United States)

Campbell, Stephen R.; Handscomb, Kerry; Zaparyniuk, Nicholas E.; Sha, Li; Cimen, O. Arda; Shipulina, Olga V.

2009-01-01

Geometry is required for many secondary school students, and is often learned, taught, and assessed more in a heuristic image-based manner, than as a formal axiomatic deductive system. Students are required to prove general theorems, but diagrams are usually used. It follows that understanding how students engage in perceiving and reasoning about…

Ten Reasons to Still Keep the Focus on Teen Childbearing. Research Brief, Publication #2009-10

Science.gov (United States)

Holcombe, Emily; Peterson, Kristen; Manlove, Jennifer; Scarupa, Harriet J., Ed.

2009-01-01

In 2002, Child Trends drew on statistics and research findings to produce a report called "Ten Reasons to Keep the Focus on Teen Childbearing." That report took note of the steady decline in the nation's teenage pregnancy and childbearing rates, beginning in 1991, while citing multiple reasons to continue to be concerned about teen childbearing.…

Effectual Reasoning and Causal Reasoning in Creating New Businesses: A Case Study

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Juan Miguel Rosa González

2011-10-01

Full Text Available This article focuses on the process of new business creation, considering the effectuation approach, which explains the phenomenon of entrepreneurship in a different perspective than the traditional causal approach. Beginning with a description of the effectual approach assumptions, a case study about the subject is presented in order to explore the logic of the business creation process. The case discusses a Brazilian organization created in 1980 to produce materials and services in steel industry. Through structured interview with the entrepreneur who idealized the business, the main events in the early stages of the project are described. The results show the relationship between entrepreneur’s means available at the time of the enterprise creation and the new business design. In addition, the entrepreneur preferred a strategy of drawing instead of a decision one, and gave priority to strategic partnerships as a substitute of formal market research. All these aspects are covered by the effectual approach.

A Tuned Value Chain Model for University Based Public Research Organisation. Case Lut Cst.

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Vesa Karvonen

2012-12-01

Full Text Available The Porter´s value chain model was introduced for strategic business purposes. During the last decades also Universities and University based institutes have started to use actions similar to private business concepts. A University based institute is not independent actor like company but there are interest groups who are expecting them to act like they would be. This article discusses about the possibility of utilize tuned value chain to public research organizations (PRO. Also the interactions of tuned value chain model to existing industrial network are discussed. The case study object is the Centre for Separation Technology (CST at Lappeenranta University of Technology (LUT in Finland.

Semantics-based plausible reasoning to extend the knowledge coverage of medical knowledge bases for improved clinical decision support.

Science.gov (United States)

Mohammadhassanzadeh, Hossein; Van Woensel, William; Abidi, Samina Raza; Abidi, Syed Sibte Raza

2017-01-01

Capturing complete medical knowledge is challenging-often due to incomplete patient Electronic Health Records (EHR), but also because of valuable, tacit medical knowledge hidden away in physicians' experiences. To extend the coverage of incomplete medical knowledge-based systems beyond their deductive closure, and thus enhance their decision-support capabilities, we argue that innovative, multi-strategy reasoning approaches should be applied. In particular, plausible reasoning mechanisms apply patterns from human thought processes, such as generalization, similarity and interpolation, based on attributional, hierarchical, and relational knowledge. Plausible reasoning mechanisms include inductive reasoning , which generalizes the commonalities among the data to induce new rules, and analogical reasoning , which is guided by data similarities to infer new facts. By further leveraging rich, biomedical Semantic Web ontologies to represent medical knowledge, both known and tentative, we increase the accuracy and expressivity of plausible reasoning, and cope with issues such as data heterogeneity, inconsistency and interoperability. In this paper, we present a Semantic Web-based, multi-strategy reasoning approach, which integrates deductive and plausible reasoning and exploits Semantic Web technology to solve complex clinical decision support queries. We evaluated our system using a real-world medical dataset of patients with hepatitis, from which we randomly removed different percentages of data (5%, 10%, 15%, and 20%) to reflect scenarios with increasing amounts of incomplete medical knowledge. To increase the reliability of the results, we generated 5 independent datasets for each percentage of missing values, which resulted in 20 experimental datasets (in addition to the original dataset). The results show that plausibly inferred knowledge extends the coverage of the knowledge base by, on average, 2%, 7%, 12%, and 16% for datasets with, respectively, 5%, 10%, 15

Fuzzy Reasoning as a Base for Collision Avoidance Decision Support System

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tanja brcko

2013-12-01

Full Text Available Despite the generally high qualifications of seafarers, many maritime accidents are caused by human error; such accidents include capsizing, collision, and fire, and often result in pollution. Enough concern has been generated that researchers around the world have developed the study of the human factor into an independent scientific discipline. A great deal of progress has been made, particularly in the area of artificial intelligence. But since total autonomy is not yet expedient, the decision support systems based on soft computing are proposed to support human navigators and VTS operators in times of crisis as well as during the execution of everyday tasks as a means of reducing risk levels.This paper considers a decision support system based on fuzzy logic integrated into an existing bridge collision avoidance system. The main goal is to determine the appropriate course of avoidance, using fuzzy reasoning.

Bringing explicit insight into cognitive psychology features during clinical reasoning seminars: a prospective, controlled study.

Science.gov (United States)

Nendaz, Mathieu R; Gut, Anne M; Louis-Simonet, Martine; Perrier, Arnaud; Vu, Nu V

2011-04-01

Facets of reasoning competence influenced by an explicit insight into cognitive psychology features during clinical reasoning seminars have not been specifically explored. This prospective, controlled study, conducted at the University of Geneva Faculty of Medicine, Switzerland, assessed the impact on sixth-year medical students' patient work-up of case-based reasoning seminars, bringing them explicit insight into cognitive aspects of their reasoning. Volunteer students registered for our three-month Internal Medicine elective were assigned to one of two training conditions: standard (control) or modified (intervention) case-based reasoning seminars. These seminars start with the patient's presenting complaint and the students must ask the tutor for additional clinical information to progress through case resolution. For this intervention, the tutors made each step explicit to students and encouraged self-reflection on their reasoning processes. At the end of their elective, students' performances were assessed through encounters with two standardized patients and chart write-ups. Twenty-nine students participated, providing a total of 58 encounters. The overall differences in accuracy of the final diagnosis given to the patient at the end of the encounter (control 63% vs intervention 74%, p = 0.53) and of the final diagnosis mentioned in the patient chart (61% vs 70%, p = 0.58) were not statistically significant. The students in the intervention group significantly more often listed the correct diagnosis among the differential diagnoses in their charts (75% vs 97%, p = 0.02). This case-based clinical reasoning seminar intervention, designed to bring students insight into cognitive features of their reasoning, improved aspects of diagnostic competence.

Hurrah for the Reasonable Woman.

Science.gov (United States)

Leland, Dorothy

1994-01-01

Recent court cases on sexual harassment, and the outcomes, were reviewed in terms of how the court viewed a "reasonable" woman. Rulings in such cases can vary because of different interpretations of the "reasonable" concept. Also discusses how recent rulings will affect sexual harassment policymakers in the workplace and educational institutions.…

Features of calculation of reasonable time of the trial in civil cases in the context of the practice of the European court of human rights

Directory of Open Access Journals (Sweden)

Т. Цувіна

2015-11-01

Full Text Available Problem setting. European Convention of Human Rights (ECHR guarantees right to a fair trial within a reasonable time for everyone (par. 1 art. 6 ECHR. Reasonable time of the trial is an element of the right to a fair trial. One of the main directions for development of civil procedure in Ukraine is the implementation of international standards of fair trial, in particular standards of reasonable time of the trial. Recent research and publications analyses. Foreign and Ukrainian scientists such as Komarov V. V., Neshataeva T. M., Sakara N. U. and others in their works paid attention to different aspects of problems connected with the right to a fair trial within a reasonable time, but a comprehensive study devoted to a features of calculation of reasonable time of the trial taking into account the practice of the ECHR on this issue wasn’t conducted. Paper objective. Main objective of the article is to study decisions of the ECHR concerning the interpretation of Par. 1, Art. 6 ECHR and analyze features of calculation of reasonable time of the trial to make recommendations on implementation of such national level. Paper main body. As a rule, according to a practice of ECHR reasonable time of civil proceedings begins on the date on which the case is referred to a judicial authority. Thus ECHR can take as the starting point the date of a preliminary application to an administrative authority, especially when this is a prerequisite for commencement of proceedings. The end of reasonable time of the trial connected with the moment when the court decision become final or its execution. Conclusions of the research. Calculation of reasonable time of the trial in civil cases in circumstances when an application to the court was preceded by a seeking for protection from the authorities and public servants of executive power has features. In such situations a calculation of reasonable time of the trial doesn’t begin from the moment of seeking for

Evaluating moral reasoning in nursing education.

Science.gov (United States)

McLeod-Sordjan, Renee

2014-06-01

Evidence-based practice suggests the best approach to improving professionalism in practice is ethics curricula. However, recent research has demonstrated that millennium graduates do not advocate for patients or assert themselves during moral conflicts. The aim of this article is the exploration of evaluation techniques to evaluate one measurable outcome of ethics curricula: moral reasoning. A review of literature, published between 1995 and 2013, demonstrated that the moral orientations of care and justice as conceptualized by Gilligan and Kohlberg are utilized by nursing students to solve ethical dilemmas. Data obtained by means of reflective journaling, Ethics of Care Interview (ECI) and Defining Issues Test (DIT), would objectively measure the interrelated pathways of care-based and justice-based moral reasoning. In conclusion, educators have an ethical responsibility to foster students' ability to exercise sound clinical judgment, and support their professional development. It is recommended that educators design authentic assessments to demonstrate student's improvement of moral reasoning. © The Author(s) 2013.

Reasons of conscience and termination of employment

International Nuclear Information System (INIS)

Anon.

1990-01-01

The plaintiff was head of a research team in a German subsidiary company of a British pharmaceutical company. The research team was to carry out tests with volounteers for medical acceptance of a newly developed agent against nausea (preliminary product name BRL 43694-5-HT receptor antagonist). The goal was to prove the agent's efficacy for prevention or treatment of acute radiation sickness due to radiotherapy, or in the event of a nuclear war. The plaintiff refused for reasons of conscience to take part in this work. As the firm could not give him other tasks to do, notice of routine dismissal was sent after several warnings, against which he brought an action in court. The Federal Labour Court's decision headnotes state among other reasons: If serious reasons of conscience (para. 315 I BGB) do not allow an employer to assign a particular job to an employee, the reason for dismissal lies with the personality of the employee, if the firm cannot offer any other job. The personal conscience of the employee may not restrict the employer's freedom to determine their activities and product range. The employee in this case is not able to perform his duty in accordance with para. 297 BGB. (orig./HP) [de

Improving product development practice: An action-research based approach

DEFF Research Database (Denmark)

Harmsen, Hanne

In studies of new product development it has often been concluded that to a large extent new product suc-cess is tunder the influence of companies and long lists of direct norma-tive guide-lines have been formulated. Nevertheless descriptive studi that deve-lopment practice is still far from...... the widely published normative advice. While there may be several reasons for discrepancies between research results and prac-tice this paper focuses on problems of implementation of the identified success factors. Within the research area of NPD-management there has been numerous surveys as well as case...

Connecting mathematics learning through spatial reasoning

Science.gov (United States)

Mulligan, Joanne; Woolcott, Geoffrey; Mitchelmore, Michael; Davis, Brent

2018-03-01

Spatial reasoning, an emerging transdisciplinary area of interest to mathematics education research, is proving integral to all human learning. It is particularly critical to science, technology, engineering and mathematics (STEM) fields. This project will create an innovative knowledge framework based on spatial reasoning that identifies new pathways for mathematics learning, pedagogy and curriculum. Novel analytical tools will map the unknown complex systems linking spatial and mathematical concepts. It will involve the design, implementation and evaluation of a Spatial Reasoning Mathematics Program (SRMP) in Grades 3 to 5. Benefits will be seen through development of critical spatial skills for students, increased teacher capability and informed policy and curriculum across STEM education.

Online Open Circuit Fault Diagnosis for Rail Transit Traction Converter Based on Object-Oriented Colored Petri Net Topology Reasoning

Directory of Open Access Journals (Sweden)

Lei Wang

2016-01-01

Full Text Available For online open circuit fault diagnosis of the traction converter in rail transit vehicles, conventional approaches depend heavily on component parameters and circuit layouts. For better universality and less parameter sensitivity during the diagnosis, this paper proposes a novel topology analysis approach to diagnose switching device open circuit failures. During the diagnosis, the topology is analyzed with fault reasoning mechanism, which is based on object-oriented Petri net (OOCPN. The OOCPN model takes in digitalized current inputs as fault signatures, and dynamical transitions between discrete switching states of a circuit with broken device are symbolized with the dynamical transitions of colored tokens in OOCPN. Such transitions simulate natural reasoning process of an expert’s brain during diagnosis. The dependence on component parameters and on circuit layouts is finally eliminated by such circuit topology reasoning process. In the last part, the proposed online reasoning and diagnosis process is exemplified with the case of a certain switching device failure in the power circuit of traction converter.

Kohlberg's theory of moral development: insights into rights reasoning.

Science.gov (United States)

Peens, B J; Louw, D A

2000-01-01

Kohlberg's theory of moral development was based on extensive research done on the reactions of people of all ages to specific moral situational dilemmas. Kohlberg was specifically interested in reasoning processes involved in decision-making. The way in which children perceive their rights is also based on reasoning processes that are inextricably linked to their level of development and more specifically to their level of moral development since the area of human rights can be considered essentially moral. Since Kohlberg's theory is primarily concerned with development, a great deal of insight can be gained into the developmental shift that occurs in children's reasoning about the rights to which they feel they should be entitled. This article focuses on Kohlberg's six-stage theory, specifically as it pertains to reasoning processes similar to those that would be used in rights reasoning. At each stage the authors propose a potential view of how children at each developmental stage might perceive their rights based on the description Kohlberg gives of the developmental trends associated with each stage. A critical assessment of Kohlberg's work is also given in order to highlight certain considerations about the limitations of this theory that need to be considered for future research.

Towards sustained Innovation in Education using Design-Based-Research - A new Approach to Teaching Electricity

CERN Multimedia

CERN. Geneva

2018-01-01

The influence of Physics Education Research (PER) on teaching in schools is often rather limited. Design-Based-Research tries to overcome this often-criticised research-practice gap by developing and evaluating new approaches to teaching physics. Using a variety of qualitative and quantitative research methods and working closely with schools, design research strives to find evidence-based solutions to pressing educational problems. One such problem in physics education is that most students fail to correctly analyse electric circuits even after instruction as they tend to reason exclusively with current and resistance. Effective reasoning about electric circuits, however, requires a solid understanding of voltage and potential. At the example of the development and evaluation of an innovative curriculum to teach electricity based on the electron gas model, the presentation will give an introduction to Design-Based-Research in PER.

Reliability Assessment of Cloud Computing Platform Based on Semiquantitative Information and Evidential Reasoning

Directory of Open Access Journals (Sweden)

Hang Wei

2016-01-01

Full Text Available A reliability assessment method based on evidential reasoning (ER rule and semiquantitative information is proposed in this paper, where a new reliability assessment architecture including four aspects with both quantitative data and qualitative knowledge is established. The assessment architecture is more objective in describing complex dynamic cloud computing environment than that in traditional method. In addition, the ER rule which has good performance for multiple attribute decision making problem is employed to integrate different types of the attributes in assessment architecture, which can obtain more accurate assessment results. The assessment results of the case study in an actual cloud computing platform verify the effectiveness and the advantage of the proposed method.

Using case-based reasoning for the reconstitution and manipulation of voxelized phantoms; Utilisation du raisonnement a partir de cas pour la reconstitution et la manipulation de fantomes voxelises

Energy Technology Data Exchange (ETDEWEB)

Henriet, J.; Fontaine, E.; Bopp, M.; Makovicka, L. [IRMAIENISYSI Institut FEMTO - UMR CNRS 6174, Pole Universitaire des Portes du Jura, 4 Place Tharradin - BP 71427, 25211 - Montbeliard (France); Farah, J.; Broggio, D.; Franck, D. [CEA Fontenay-aux-Roses, LEDIISDIIDPRH, IRSN, 92 (France); Chebel-Morello, B. [COSMI/AS2M/Institut FEMTO - UMR CNRS 6174, 24 Rue Alain Savary, 25000 - Besaneon (France)

2010-07-01

The authors reports the development of the EquiVox platform, the aim of which is to allow a radioprotection expert (physician, biologist or other) to work with a phantom which will be the closest possible to the examined person in order to make an as precise as possible dosimetric assessment. The objective is to help to select the best phantom among those the expert knows depending on the assessment type he wants to make. First, they present the general principles of the case-based reasoning, and then the EquiVox platform which proposes all the steps: formalization, elaboration, comparison, and so on. Based on typical numerical values associated with different morphological characteristics, they present and discuss graphical results obtained by the platform. They also discuss their validity and reliability

Restoration of noncarious tooth defects by dentists in The Dental Practice-Based Research Network

DEFF Research Database (Denmark)

Nascimento, Marcelle M; Gordan, Valeria V; Qvist, Vibeke

2011-01-01

The authors conducted a study to quantify the reasons for restoring noncarious tooth defects (NCTDs) by dentists in The Dental Practice-Based Research Network (DPBRN) and to assess the tooth, patient and dentist characteristics associated with those reasons....

Diagnostic reasoning using qualitative causal models

International Nuclear Information System (INIS)

Sudduth, A.L.

1992-01-01

The application of expert systems to reasoning problems involving real-time data from plant measurements has been a topic of much research, but few practical systems have been deployed. One obstacle to wider use of expert systems in applications involving real-time data is the lack of adequate knowledge representation methodologies for dynamic processes. Knowledge bases composed mainly of rules have disadvantages when applied to dynamic processes and real-time data. This paper describes a methodology for the development of qualitative causal models that can be used as knowledge bases for reasoning about process dynamic behavior. These models provide a systematic method for knowledge base construction, considerably reducing the engineering effort required. They also offer much better opportunities for verification and validation of the knowledge base, thus increasing the possibility of the application of expert systems to reasoning about mission critical systems. Starting with the Signed Directed Graph (SDG) method that has been successfully applied to describe the behavior of diverse dynamic processes, the paper shows how certain non-physical behaviors that result from abstraction may be eliminated by applying causal constraint to the models. The resulting Extended Signed Directed Graph (ESDG) may then be compiled to produce a model for use in process fault diagnosis. This model based reasoning methodology is used in the MOBIAS system being developed by Duke Power Company under EPRI sponsorship. 15 refs., 4 figs

Case Reports, Case Series - From Clinical Practice to Evidence-Based Medicine in Graduate Medical Education.

Science.gov (United States)

Sayre, Jerry W; Toklu, Hale Z; Ye, Fan; Mazza, Joseph; Yale, Steven

2017-08-07

Case reports and case series or case study research are descriptive studies that are prepared for illustrating novel, unusual, or atypical features identified in patients in medical practice, and they potentially generate new research questions. They are empirical inquiries or investigations of a patient or a group of patients in a natural, real-world clinical setting. Case study research is a method that focuses on the contextual analysis of a number of events or conditions and their relationships. There is disagreement among physicians on the value of case studies in the medical literature, particularly for educators focused on teaching evidence-based medicine (EBM) for student learners in graduate medical education. Despite their limitations, case study research is a beneficial tool and learning experience in graduate medical education and among novice researchers. The preparation and presentation of case studies can help students and graduate medical education programs evaluate and apply the six American College of Graduate Medical Education (ACGME) competencies in the areas of medical knowledge, patient care, practice-based learning, professionalism, systems-based practice, and communication. A goal in graduate medical education should be to assist residents to expand their critical thinking, problem-solving, and decision-making skills. These attributes are required in the teaching and practice of EBM. In this aspect, case studies provide a platform for developing clinical skills and problem-based learning methods. Hence, graduate medical education programs should encourage, assist, and support residents in the publication of clinical case studies; and clinical teachers should encourage graduate students to publish case reports during their graduate medical education.

Reasonable Accommodation Information Tracking System

Data.gov (United States)

U.S. Environmental Protection Agency — The Reasonable Accommodation Information Tracking System (RAITS) is a case management system that allows the National Reasonable Accommodation Coordinator (NRAC) and...

Reasons for Implementing Movement in Kinetic Architecture

Science.gov (United States)

Cudzik, Jan; Nyka, Lucyna

2017-10-01

The paper gives insights into different forms of movement in contemporary architecture and examines them based on the reasons for their implementation. The main objective of the paper is to determine: the degree to which the complexity of kinematic architecture results from functional and spatial needs and what other motivations there are. The method adopted to investigate these questions involves theoretical studies and comparative analyses of architectural objects with different forms of movement imbedded in their structure. Using both methods allowed delving into reasons that lie behind the implementation of movement in contemporary kinetic architecture. As research shows, there is a constantly growing range of applications with kinematic solutions inserted in buildings’ structures. The reasons for their implementation are manifold and encompass pursuits of functional qualities, environmental performance, spatial effects, social interactions and new aesthetics. In those early projects based on simple mechanisms, the main motives were focused on functional values and in later experiments - on improving buildings’ environmental performance. Additionally, in recent proposals, a significant quest could be detected toward kinematic solutions that are focused on factors related to alternative aesthetics and innovative spatial effects. Research reveals that the more complicated form of movement, the more often the reason for its implementation goes beyond the traditionally understood “function”. However, research also shows that the effects resulting from investigations on spatial qualities of architecture and new aesthetics often appear to provide creative insights into new functionalities in architecture.

Visualizing complex processes using a cognitive-mapping tool to support the learning of clinical reasoning.

Science.gov (United States)

Wu, Bian; Wang, Minhong; Grotzer, Tina A; Liu, Jun; Johnson, Janice M

2016-08-22

Practical experience with clinical cases has played an important role in supporting the learning of clinical reasoning. However, learning through practical experience involves complex processes difficult to be captured by students. This study aimed to examine the effects of a computer-based cognitive-mapping approach that helps students to externalize the reasoning process and the knowledge underlying the reasoning process when they work with clinical cases. A comparison between the cognitive-mapping approach and the verbal-text approach was made by analyzing their effects on learning outcomes. Fifty-two third-year or higher students from two medical schools participated in the study. Students in the experimental group used the computer-base cognitive-mapping approach, while the control group used the verbal-text approach, to make sense of their thinking and actions when they worked with four simulated cases over 4 weeks. For each case, students in both groups reported their reasoning process (involving data capture, hypotheses formulation, and reasoning with justifications) and the underlying knowledge (involving identified concepts and the relationships between the concepts) using the given approach. The learning products (cognitive maps or verbal text) revealed that students in the cognitive-mapping group outperformed those in the verbal-text group in the reasoning process, but not in making sense of the knowledge underlying the reasoning process. No significant differences were found in a knowledge posttest between the two groups. The computer-based cognitive-mapping approach has shown a promising advantage over the verbal-text approach in improving students' reasoning performance. Further studies are needed to examine the effects of the cognitive-mapping approach in improving the construction of subject-matter knowledge on the basis of practical experience.

Structuring students’ analogical reasoning in solving algebra problem

Science.gov (United States)

Lailiyah, S.; Nusantara, T.; Sa'dijah, C.; Irawan, E. B.; Kusaeri; Asyhar, A. H.

2018-01-01

The average achievement of Indonesian students’ mathematics skills according to Benchmark International Trends in Mathematics and Science Study (TIMSS) is ranked at the 38th out of 42 countries and according to the survey result in Program for International Student Assessment (PISA) is ranked at the 64th out of 65 countries. The low mathematics skill of Indonesian student has become an important reason to research more deeply about reasoning and algebra in mathematics. Analogical reasoning is a very important component in mathematics because it is the key to creativity and it can make the learning process in the classroom become effective. The major part of the analogical reasoning is about structuring including the processes of inferencing and decision-making happens. Those processes involve base domain and target domain. Methodologically, the subjects of this research were 42 students from class XII. The sources of data were derived from the results of thinks aloud, the transcribed interviews, and the videos taken while the subject working on the instruments and interviews. The collected data were analyzed using qualitative techniques. The result of this study described the structuring characteristics of students’ analogical reasoning in solving algebra problems from all the research subjects.

Reasons for receiving or not receiving HPV vaccination in primary schoolgirls in Tanzania: a case control study.

Science.gov (United States)

Watson-Jones, Deborah; Tomlin, Keith; Remes, Pieter; Baisley, Kathy; Ponsiano, Riziki; Soteli, Selephina; de Sanjosé, Silvia; Changalucha, John; Kapiga, Saidi; Hayes, Richard J

2012-01-01

There are few data on factors influencing human papillomavirus (HPV) vaccination uptake in sub-Saharan Africa. We examined the characteristics of receivers and non-receivers of HPV vaccination in Tanzania and identified reasons for not receiving the vaccine. We conducted a case control study of HPV vaccine receivers and non-receivers within a phase IV cluster-randomised trial of HPV vaccination in 134 primary schools in Tanzania. Girls who failed to receive vaccine (pupil cases) and their parents/guardians (adult cases) and girls who received dose 1 (pupil controls) of the quadrivalent vaccine (Gardasil™) and their parents/guardians (adult controls) were enrolled from 39 schools in a 1∶1 ratio and interviewed about cervical cancer, HPV vaccine knowledge and reasons why they might have received or not received the vaccine. Conditional logistic regression was used to determine factors independently associated with not receiving HPV vaccine. We interviewed 159 pupil/adult cases and 245 pupil/adult controls. Adult-factors independently associated with a daughter being a case were older age, owning fewer household items, not attending a school meeting about HPV vaccine, and not knowing anyone with cancer. Pupil-factors for being a case included having a non-positive opinion about the school de-worming programme, poor knowledge about the location of the cervix, and not knowing that a vaccine could prevent cervical cancer. Reasons for actively refusing vaccination included concerns about side effects and infertility. Most adult and pupil cases reported that they would accept the HPV vaccine if it were offered again (97% and 93% respectively). Sensitisation messages, especially targeted at older and poorer parents, knowledge retention and parent meetings are critical for vaccine acceptance in Tanzania. Vaccine side effects and fertility concerns should be addressed prior to a national vaccination program. Parents and pupils who initially decline vaccination should be

Approaching Ethical Reasoning in Nursing Research through a Communitarian Perspective.

Science.gov (United States)

Dresden, Elissa; McElmurry, Beverly J.; McCreary, Linda L.

2003-01-01

Case studies depict dilemmas in nursing research involving protection of community rights and community informed consent. Outlines research guidelines derived from communitarian ethical frameworks that consider beneficence, justice, and respect for autonomy in the context of community. (Contains 58 references.) (SK)

A reasonable Semantic Web

NARCIS (Netherlands)

Hitzler, Pascal; Van Harmelen, Frank

2010-01-01

The realization of Semantic Web reasoning is central to substantiating the Semantic Web vision. However, current mainstream research on this topic faces serious challenges, which forces us to question established lines of research and to rethink the underlying approaches. We argue that reasoning for

Emotional reasoning and parent-based reasoning in normal children

NARCIS (Netherlands)

Morren, M.; Muris, P.; Kindt, M.

2004-01-01

A previous study by Muris, Merckelbach, and Van Spauwen demonstrated that children display emotional reasoning irrespective of their anxiety levels. That is, when estimating whether a situation is dangerous, children not only rely on objective danger information but also on their own

Case Study Research in Software Engineering Guidelines and Examples

CERN Document Server

Runeson, Per; Rainer, Austen; Regnell, Bjorn

2012-01-01

Based on their own experiences of in-depth case studies of software projects in international corporations, in this book the authors present detailed practical guidelines on the preparation, conduct, design and reporting of case studies of software engineering.  This is the first software engineering specific book on the case study research method.

Strengthening moral reasoning through dedicated ethics training in dietetic preparatory programs.

Science.gov (United States)

Hewko, Sarah J; Cooper, Sarah L; Cummings, Greta G

2015-01-01

Moral reasoning skills, associated with the ability to make ethical decisions effectively, must be purposively fostered. Among health professionals, enhanced moral reasoning is linked to superior clinical performance. Research demonstrates that moral reasoning is enhanced through dedicated, discussion-based ethics education offered over a period of 3-12 weeks. Current dietetic students and practicing dietitians seeking to strengthen their moral reasoning skills can undertake elective ethics education. Further research within dietetic preparatory programs is warranted to better inform the development and implementation of ethics courses. Copyright © 2015 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Working memory, reasoning, and expertise in medicine-insights into their relationship using functional neuroimaging.

Science.gov (United States)

Hruska, Pam; Krigolson, Olav; Coderre, Sylvain; McLaughlin, Kevin; Cortese, Filomeno; Doig, Christopher; Beran, Tanya; Wright, Bruce; Hecker, Kent G

2016-12-01

Clinical reasoning is dependent upon working memory (WM). More precisely, during the clinical reasoning process stored information within long-term memory is brought into WM to facilitate the internal deliberation that affords a clinician the ability to reason through a case. In the present study, we examined the relationship between clinical reasoning and WM while participants read clinical cases with functional magnetic resonance imaging (fMRI). More specifically, we examined the impact of clinical case difficulty (easy, hard) and clinician level of expertise (2nd year medical students, senior gastroenterologists) on neural activity within regions of cortex associated with WM (i.e., the prefrontal cortex) during the reasoning process. fMRI was used to scan ten second-year medical students and ten practicing gastroenterologists while they reasoned through sixteen clinical cases [eight straight forward (easy) and eight complex (hard)] during a single 1-h scanning session. Within-group analyses contrasted the easy and hard cases which were then subsequently utilized for a between-group analysis to examine effects of expertise (novice > expert, expert > novice). Reading clinical cases evoked multiple neural activations in occipital, prefrontal, parietal, and temporal cortical regions in both groups. Importantly, increased activation in the prefrontal cortex in novices for both easy and hard clinical cases suggests novices utilize WM more so than experts during clinical reasoning. We found that clinician level of expertise elicited differential activation of regions of the human prefrontal cortex associated with WM during clinical reasoning. This suggests there is an important relationship between clinical reasoning and human WM. As such, we suggest future models of clinical reasoning take into account that the use of WM is not consistent throughout all clinical reasoning tasks, and that memory structure may be utilized differently based on level of expertise.

Language-Based Reasoning in Primary Science

Science.gov (United States)

Hackling, Mark; Sherriff, Barbara

2015-01-01

Language is critical in the mediation of scientific reasoning, higher-order thinking and the development of scientific literacy. This study investigated how an exemplary primary science teacher scaffolds and supports students' reasoning during a Year 4 materials unit. Lessons captured on video, teacher and student interviews and micro-ethnographic…

Diversity-based reasoning in children.

Science.gov (United States)

Heit, E; Hahn, U

2001-12-01

One of the hallmarks of inductive reasoning by adults is the diversity effect, namely that people draw stronger inferences from a diverse set of evidence than from a more homogenous set of evidence. However, past developmental work has not found consistent diversity effects with children age 9 and younger. We report robust sensitivity to diversity in children as young as 5, using everyday stimuli such as pictures of objects with people. Experiment 1 showed the basic diversity effect in 5- to 9-year-olds. Experiment 2 showed that, like adults, children restrict their use of diversity information when making inferences about remote categories. Experiment 3 used other stimulus sets to overcome an alternate explanation in terms of sample size rather than diversity effects. Finally, Experiment 4 showed that children more readily draw on diversity when reasoning about objects and their relations with people than when reasoning about objects' internal, hidden properties, thus partially explaining the negative findings of previous work. Relations to cross-cultural work and models of induction are discussed. Copyright 2001 Academic Press.

From qualitative reasoning models to Bayesian-based learner modeling

NARCIS (Netherlands)

Milošević, U.; Bredeweg, B.; de Kleer, J.; Forbus, K.D.

2010-01-01

Assessing the knowledge of a student is a fundamental part of intelligent learning environments. We present a Bayesian network based approach to dealing with uncertainty when estimating a learner’s state of knowledge in the context of Qualitative Reasoning (QR). A proposal for a global architecture

Expert system reasoning techniques applicable to the electric power industry

International Nuclear Information System (INIS)

Touchton, R.A.

1987-01-01

This paper describes the applicability of three problem solving paradigms adopted from the artificial intelligence discipline of computer sciences, which have been used in developing nuclear plant expert systems. Each technique is briefly defined and an example is presented that shows how that technique was used in developing an expert system application prototype. The three paradigms and their associated example systems are: (1) rule-based reasoning: reactor emergency action level monitor (REALM) for the Electric Power Research Institute, (2) object-oriented programming: accident diagnosis and prognosis aid for the US Department of Energy, and (3) model-based reasoning: knowledge-based monitoring and control system for the Electric Power Research Institute

Understanding of emotions based on counterfactual reasoning in children with autism spectrum disorders.

Science.gov (United States)

Begeer, Sander; De Rosnay, Marc; Lunenburg, Patty; Stegge, Hedy; Terwogt, Mark Meerum

2014-04-01

The understanding of emotions based on counterfactual reasoning was studied in children with high-functioning autism spectrum disorders (n = 71) and in typically developing children (n = 71), aged 6-12 years. Children were presented with eight stories about two protagonists who experienced the same positive or negative outcome, either due to their own action or by default. Relative to the comparison group, children with high-functioning autism spectrum disorder were poor at explaining emotions based on downward counterfactual reasoning (i.e. contentment and relief). There were no group differences in upward counterfactual reasoning (i.e. disappointment and regret). In the comparison group, second-order false-belief reasoning was related to children's understanding of second-order counterfactual emotions (i.e. regret and relief), while children in the high-functioning autism spectrum disorder group relied more on their general intellectual skills. Results are discussed in terms of the different functions of counterfactual reasoning about emotion and the cognitive style of children with high-functioning autism spectrum disorder.

Emotional reasoning and parent-based reasoning in normal children.

NARCIS (Netherlands)

Morren, M.; Muris, P.; Kindt, M.

2004-01-01

A previous study by Muris, Merckelbach, and Van Spauwen demonstrated that children display emotional reasoning irrepective of their anxiety levels. That is when estimating whether a situation is dangerous, childen not only rely on objective danger information but also on their own anciety-response.

An Exploratory Investigation on Modularity Adoption in Design and Production Through a Case-Based Research in a Brazilian Automaker

DEFF Research Database (Denmark)

Cauchick Miguel, Paulo Augusto; Hsuan, Juliana

2010-01-01

to what extent the adoption of modularity varies according to such tradeoffs. Case-based research is employed as the methodological approach. The unit of analysis is a business unit of an international leading manufacturer of trucks and buses, being the latter within the scope of the present investigation....... Potential gaps in the literature are also proposed for further research....

Implementation of a Clinical Reasoning Course in the Internal Medicine trimester of the final year of undergraduate medical training and its effect on students' case presentation and differential diagnostic skills.

Science.gov (United States)

Harendza, Sigrid; Krenz, Ingo; Klinge, Andreas; Wendt, Ulrike; Janneck, Matthias

2017-01-01

Background: Clinical reasoning, comprising the processes of clinical thinking, which form the basis of medical decisions, constitutes a central competence in the clinical routine on which diagnostic and therapeutic steps are based. In medical curricula in Germany, clinical reasoning is currently taught explicitly only to a small extend. Therefore, the aim of this project was to develop and implement a clinical reasoning course in the final year of undergraduate medical training. Project description: A clinical reasoning course with six learning units and 18 learning objectives was developed, which was taught by two to four instructors on the basis of 32 paper cases from the clinical practice of the instructors. In the years 2011 to 2013, the course of eight weeks with two hours per week was taught seven times. Before the first and after the last seminar, the participating students filled out a self-assessment questionnaire with a 6-point Likert scale regarding eight different clinical reasoning skills. At the same times, they received a patient case with the assignment to prepare a case presentation and differential diagnoses. Results: From 128 participating students altogether, 42 complete data sets were available. After the course, participants assessed themselves significantly better than before the course in all eight clinical reasoning skills, for example in "Summarizing and presentation of a paper case" or in the "Skill to enumerate differential diagnoses" (ppresentation of the paper case was significantly more focused after the course (p=0.011). A significant increase in the number of gathered differential diagnoses was not detected after the course. Conclusion: The newly developed and established Clinical Reasoning Course leads to a gain in the desired skills from the students' self-assessment perspective and to a more structured case presentation. To establish better options to exercise clinical reasoning, a longitudinal implementation in the medical

The Effects of Successful versus Failure-Based Cases on Argumentation while Solving Decision-Making Problems

Science.gov (United States)

Tawfik, Andrew; Jonassen, David

2013-01-01

Solving complex, ill-structured problems may be effectively supported by case-based reasoning through case libraries that provide just-in-time domain-specific principles in the form of stories. The cases not only articulate previous experiences of practitioners, but also serve as problem-solving narratives from which learners can acquire meaning.…

Global polar geospatial information service retrieval based on search engine and ontology reasoning

Science.gov (United States)

Chen, Nengcheng; E, Dongcheng; Di, Liping; Gong, Jianya; Chen, Zeqiang

2007-01-01

In order to improve the access precision of polar geospatial information service on web, a new methodology for retrieving global spatial information services based on geospatial service search and ontology reasoning is proposed, the geospatial service search is implemented to find the coarse service from web, the ontology reasoning is designed to find the refined service from the coarse service. The proposed framework includes standardized distributed geospatial web services, a geospatial service search engine, an extended UDDI registry, and a multi-protocol geospatial information service client. Some key technologies addressed include service discovery based on search engine and service ontology modeling and reasoning in the Antarctic geospatial context. Finally, an Antarctica multi protocol OWS portal prototype based on the proposed methodology is introduced.

Diagnostic reasoning strategies and diagnostic success.

Science.gov (United States)

Coderre, S; Mandin, H; Harasym, P H; Fick, G H

2003-08-01

Cognitive psychology research supports the notion that experts use mental frameworks or "schemes", both to organize knowledge in memory and to solve clinical problems. The central purpose of this study was to determine the relationship between problem-solving strategies and the likelihood of diagnostic success. Think-aloud protocols were collected to determine the diagnostic reasoning used by experts and non-experts when attempting to diagnose clinical presentations in gastroenterology. Using logistic regression analysis, the study found that there is a relationship between diagnostic reasoning strategy and the likelihood of diagnostic success. Compared to hypothetico-deductive reasoning, the odds of diagnostic success were significantly greater when subjects used the diagnostic strategies of pattern recognition and scheme-inductive reasoning. Two other factors emerged as independent determinants of diagnostic success: expertise and clinical presentation. Not surprisingly, experts outperformed novices, while the content area of the clinical cases in each of the four clinical presentations demonstrated varying degrees of difficulty and thus diagnostic success. These findings have significant implications for medical educators. It supports the introduction of "schemes" as a means of enhancing memory organization and improving diagnostic success.

Priming analogical reasoning with false memories.

Science.gov (United States)

Howe, Mark L; Garner, Sarah R; Threadgold, Emma; Ball, Linden J

2015-08-01

Like true memories, false memories are capable of priming answers to insight-based problems. Recent research has attempted to extend this paradigm to more advanced problem-solving tasks, including those involving verbal analogical reasoning. However, these experiments are constrained inasmuch as problem solutions could be generated via spreading activation mechanisms (much like false memories themselves) rather than using complex reasoning processes. In three experiments we examined false memory priming of complex analogical reasoning tasks in the absence of simple semantic associations. In Experiment 1, we demonstrated the robustness of false memory priming in analogical reasoning when backward associative strength among the problem terms was eliminated. In Experiments 2a and 2b, we extended these findings by demonstrating priming on newly created homonym analogies that can only be solved by inhibiting semantic associations within the analogy. Overall, the findings of the present experiments provide evidence that the efficacy of false memory priming extends to complex analogical reasoning problems.

Improving of prospective elementary teachers' reasoning: Learning geometry through mathematical investigation

Science.gov (United States)

Sumarna, Nana; Sentryo, Izlan

2017-08-01

This research applies mathematical investigation approach in teaching geometry to improve mathematical reasoning abilities of prospective elementary teachers. Mathematical investigation in this study involved non-routine tasks through a mathematical investigation process, namely through a series of activities as an attribute of mathematical investigation. Developing the ability of mathematical reasoning of research subjects obtained through capability of research subjects in the analysis, generalization, synthesis, justify, and resolve non-routine, which is operationally constructed as an indicator of research and is used as a criterion for measuring the ability of mathematical reasoning. Research design using Quasi-Experimental design. Based on this type, the researchers apply a pre-and posttest design, which is divided into two study groups: control group and the treatment group. The number of research subjects were 111 students consisting of 56 students in the experimental group and 55 students in the control group. The conclusion of this study stated that (1) Investigation of mathematics as an approach to learning is able to give a positive response to the increasing ability of mathematical reasoning, and (2) There is no interaction effect of the factors of learning and prior knowledge of mathematics to the increased ability of mathematical reasoning.

INTERSECTION DETECTION BASED ON QUALITATIVE SPATIAL REASONING ON STOPPING POINT CLUSTERS

Directory of Open Access Journals (Sweden)

S. Zourlidou

2016-06-01

Full Text Available The purpose of this research is to propose and test a method for detecting intersections by analysing collectively acquired trajectories of moving vehicles. Instead of solely relying on the geometric features of the trajectories, such as heading changes, which may indicate turning points and consequently intersections, we extract semantic features of the trajectories in form of sequences of stops and moves. Under this spatiotemporal prism, the extracted semantic information which indicates where vehicles stop can reveal important locations, such as junctions. The advantage of the proposed approach in comparison with existing turning-points oriented approaches is that it can detect intersections even when not all the crossing road segments are sampled and therefore no turning points are observed in the trajectories. The challenge with this approach is that first of all, not all vehicles stop at the same location – thus, the stop-location is blurred along the direction of the road; this, secondly, leads to the effect that nearby junctions can induce similar stop-locations. As a first step, a density-based clustering is applied on the layer of stop observations and clusters of stop events are found. Representative points of the clusters are determined (one per cluster and in a last step the existence of an intersection is clarified based on spatial relational cluster reasoning, with which less informative geospatial clusters, in terms of whether a junction exists and where its centre lies, are transformed in more informative ones. Relational reasoning criteria, based on the relative orientation of the clusters with their adjacent ones are discussed for making sense of the relation that connects them, and finally for forming groups of stop events that belong to the same junction.

Watch what happens: using a web-based multimedia platform to enhance intraoperative learning and development of clinical reasoning.

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Fingeret, Abbey L; Martinez, Rebecca H; Hsieh, Christine; Downey, Peter; Nowygrod, Roman

2016-02-01

We aim to determine whether observed operations or internet-based video review predict improved performance in the surgery clerkship. A retrospective review of students' usage of surgical videos, observed operations, evaluations, and examination scores were used to construct an exploratory principal component analysis. Multivariate regression was used to determine factors predictive of clerkship performance. Case log data for 231 students revealed a median of 25 observed cases. Students accessed the web-based video platform a median of 15 times. Principal component analysis yielded 4 factors contributing 74% of the variability with a Kaiser-Meyer-Olkin coefficient of .83. Multivariate regression predicted shelf score (P < .0001), internal clinical skills examination score (P < .0001), subjective evaluations (P < .001), and video website utilization (P < .001) but not observed cases to be significantly associated with overall performance. Utilization of a web-based operative video platform during a surgical clerkship is an independently associated with improved clinical reasoning, fund of knowledge, and overall evaluation. Thus, this modality can serve as a useful adjunct to live observation. Copyright © 2016 Elsevier Inc. All rights reserved.

Clinical reasoning of junior doctors in emergency medicine: a grounded theory study.

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Adams, E; Goyder, C; Heneghan, C; Brand, L; Ajjawi, R

2017-02-01

Emergency medicine (EM) has a high case turnover and acuity making it a demanding clinical reasoning domain especially for junior doctors who lack experience. We aimed to better understand their clinical reasoning using dual cognition as a guiding theory. EM junior doctors were recruited from six hospitals in the south of England to participate in semi-structured interviews (n=20) and focus groups (n=17) based on recall of two recent cases. Transcripts were analysed using a grounded theory approach to identify themes and to develop a model of junior doctors' clinical reasoning in EM. Within cases, clinical reasoning occurred in three phases. In phase 1 (case framing), initial case cues and first impressions were predominantly intuitive, but checked by analytical thought and determined the urgency of clinical assessment. In phase 2 (evolving reasoning), non-analytical single cue and pattern recognitions were common which were subsequently validated by specific analytical strategies such as use of red flags. In phase 3 (ongoing uncertainty) analytical self-monitoring and reassurance strategies were used to precipitate a decision regarding discharge. We found a constant dialectic between intuitive and analytical cognition throughout the reasoning process. Our model of clinical reasoning by EM junior doctors illustrates the specific contextual manifestations of the dual cognition theory. Distinct diagnostic strategies are identified and together these give EM learners and educators a framework and vocabulary for discussion and learning about clinical reasoning. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Understanding clinical reasoning in osteopathy: a qualitative research approach

OpenAIRE

Grace, Sandra; Orrock, Paul; Vaughan, Brett; Blaich, Raymond; Coutts, Rosanne

2016-01-01

Background Clinical reasoning has been described as a process that draws heavily on the knowledge, skills and attributes that are particular to each health profession. However, the clinical reasoning processes of practitioners of different disciplines demonstrate many similarities, including hypothesis generation and reflective practice. The aim of this study was to understand clinical reasoning in osteopathy from the perspective of osteopathic clinical educators and the extent to which it wa...

Clinical reasoning: concept analysis.

Science.gov (United States)

Simmons, Barbara

2010-05-01

This paper is a report of a concept analysis of clinical reasoning in nursing. Clinical reasoning is an ambiguous term that is often used synonymously with decision-making and clinical judgment. Clinical reasoning has not been clearly defined in the literature. Healthcare settings are increasingly filled with uncertainty, risk and complexity due to increased patient acuity, multiple comorbidities, and enhanced use of technology, all of which require clinical reasoning. Data sources. Literature for this concept analysis was retrieved from several databases, including CINAHL, PubMed, PsycINFO, ERIC and OvidMEDLINE, for the years 1980 to 2008. Rodgers's evolutionary method of concept analysis was used because of its applicability to concepts that are still evolving. Multiple terms have been used synonymously to describe the thinking skills that nurses use. Research in the past 20 years has elucidated differences among these terms and identified the cognitive processes that precede judgment and decision-making. Our concept analysis defines one of these terms, 'clinical reasoning,' as a complex process that uses cognition, metacognition, and discipline-specific knowledge to gather and analyse patient information, evaluate its significance, and weigh alternative actions. This concept analysis provides a middle-range descriptive theory of clinical reasoning in nursing that helps clarify meaning and gives direction for future research. Appropriate instruments to operationalize the concept need to be developed. Research is needed to identify additional variables that have an impact on clinical reasoning and what are the consequences of clinical reasoning in specific situations.

Semantical Markov Logic Network for Distributed Reasoning in Cyber-Physical Systems

Directory of Open Access Journals (Sweden)

Abdul-Wahid Mohammed

2017-01-01

Full Text Available The challenges associated with developing accurate models for cyber-physical systems are attributable to the intrinsic concurrent and heterogeneous computations of these systems. Even though reasoning based on interconnected domain specific ontologies shows promise in enhancing modularity and joint functionality modelling, it has become necessary to build interoperable cyber-physical systems due to the growing pervasiveness of these systems. In this paper, we propose a semantically oriented distributed reasoning architecture for cyber-physical systems. This model accomplishes reasoning through a combination of heterogeneous models of computation. Using the flexibility of semantic agents as a formal representation for heterogeneous computational platforms, we define autonomous and intelligent agent-based reasoning procedure for distributed cyber-physical systems. Sensor networks underpin the semantic capabilities of this architecture, and semantic reasoning based on Markov logic networks is adopted to address uncertainty in modelling. To illustrate feasibility of this approach, we present a Markov logic based semantic event model for cyber-physical systems and discuss a case study of event handling and processing in a smart home.

Emotional Reasoning and Parent-Based Reasoning in Normal Children

Science.gov (United States)

Morren, Mattijn; Muris, Peter; Kindt, Merel

2004-01-01

A previous study by Muris, Merckelbach, and Van Spauwen [1] demonstrated that children display emotional reasoning irrespective of their anxiety levels. That is, when estimating whether a situation is dangerous, children not only rely on objective danger information but also on their "own" anxiety-response. The present study further examined…

Prayer Healing: A Case Study Research Protocol.

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Kruijthoff, Dirk J; van der Kooi, Cornelis; Glas, Gerrit; Abma, Tineke A

2017-01-01

Context • Prayer healing is a common practice in many religious communities around the world. Even in the highly secularized Dutch society, cases of prayer healing are occasionally reported in the media, often generating public attention. There is an ongoing debate regarding whether such miraculous cures do actually occur and how to interpret them. Objective • The aim of the article was to present a research protocol for the investigation of reported cases of remarkable and/or unexplained healing after prayer. Design • The research team developed a method to perform a retrospective, case-based study of prayer healing. Reported prayer healings can be investigated systematically in accordance with a step-by-step methodology. The focus is on understanding the healing by studying it from multiple perspectives, using both medical judgment and patients' narratives collected by qualitative methods Setting • The study occurred at Vrije Universiteit (VU) and VU Medical Center (Amsterdam, Netherlands) as well as the general medical practice of the first author. Participants • Potential participants could be any individuals in the Netherlands or neighboring countries who claim to have been healed through prayer. The reports of healing came from multiple sources, including the research team's medical practices and their direct vicinities, newspaper articles, prayer healers, and medical colleagues. Outcome Measures • Medical data were obtained before and after prayer. Subsequently, a member of a research team and of a medical assessment committee made a standardized judgment that evaluated whether a cure was clinically remarkable or scientifically unexplained. The participants' experiences and insider perspectives were studied, using in-depth interviews in accordance with a qualitative research methodology, to gain insight into the perceptions and explanations of the cures that were offered by participants and by the members of the medical assessment committee. The

Reasoning in Design: Idea Generation Condition Effects on Reasoning Processes and Evaluation of Ideas

DEFF Research Database (Denmark)

Cramer-Petersen, Claus Lundgaard; Ahmed-Kristensen, Saeema

2015-01-01

to investigate idea generation sessions of two industry cases. Reasoning was found to appear in sequences of alternating reasoning types where the initiating reasoning type was decisive. The study found that abductive reasoning led to more radical ideas, whereas deductive reasoning led to ideas being for project...... requirements, but having a higher proportion being rejected as not valuable. The study sheds light on the conditions that promote these reasoning types. The study is one of the first of its kind and advances an understanding of reasoning in design by empirical means and suggests a relationship between......Reasoning is at the core of design activity and thinking. Thus, understanding and explaining reasoning in design is fundamental to understand and support design practice. This paper investigates reasoning in design and its relationship to varying foci at the stage of idea generation and subsequent...

Implementing accountability for reasonableness--the case of pharmaceutical reimbursement in Sweden.

Science.gov (United States)

Jansson, Sandra

2007-04-01

This paper aims to describe the priority-setting procedure for new original pharmaceuticals practiced by the Swedish Pharmaceutical Benefits Board (LFN), to analyse the outcome of the procedure in terms of decisions and the relative importance of ethical principles, and to examine the reactions of stakeholders. All the 'principally important' decisions made by the LFN during its first 33 months of operation were analysed. The study is theoretically anchored in the theory of fair and legitimate priority-setting procedures by Daniels and Sabin, and is based on public documents, media articles, and semi-structured interviews. Only nine cases resulted in a rejection of a subsidy by the LFN and 15 in a limited or conditional subsidy. Total rejections rather than limitations gave rise to actions by stakeholders. Primarily, the principle of cost-effectiveness was used when limiting/conditioning or totally rejecting a subsidy. This study suggests that implementing a priority-setting process that fulfils the conditions of accountability for reasonableness can result in a priority-setting process which is generally perceived as fair and legitimate by the major stakeholders and may increase social learning in terms of accepting the necessity of priority setting in health care. The principle of cost-effectiveness increased in importance when the demand for openness and transparency increased.

How People Reason: A Grounded Theory Study of Scientific Reasoning about Global Climate Change

Science.gov (United States)

Liu, Shiyu

Scientific reasoning is crucial in both scientific inquiry and everyday life. While the majority of researchers have studied "how people reason" by focusing on their cognitive processes, factors related to the underpinnings of scientific reasoning are still under-researched. The present study aimed to develop a grounded theory that captures not only the cognitive processes during reasoning but also their underpinnings. In particular, the grounded theory and phenomenographic methodologies were integrated to explore how undergraduate students reason about competing theories and evidence on global climate change. Twenty-six undergraduate students were recruited through theoretical sampling. Constant comparative analysis of responses from interviews and written assessments revealed that participants were mostly drawn to the surface features when reasoning about evidence. While prior knowledge might not directly contribute to participants' performance on evidence evaluation, it affected their level of engagement when reading and evaluating competing arguments on climate issues. More importantly, even though all participants acknowledged the relative correctness of multiple perspectives, they predominantly favored arguments that supported their own beliefs with weak scientific reasoning about the opposing arguments. Additionally, factors such as personal interests, religious beliefs, and reading capacity were also found to have bearings on the way participants evaluated evidence and arguments. In all, this work contributes to the current endeavors in exploring the nature of scientific reasoning. Taking a holistic perspective, it provides an in-depth discussion of factors that may affect or relate to scientific reasoning processes. Furthermore, in comparison with traditional methods used in the literature, the methodological approach employed in this work brought an innovative insight into the investigation of scientific reasoning. Last but not least, this research may

Synthesis Reasoning and Its Application in Chinese Calligraphy Generation

Institute of Scientific and Technical Information of China (English)

XUSong-Hua; PANYun-He; ZHUANGYue-Ting; FRANCISC.M.Lau

2005-01-01

In this paper, we address the demanding task of developing intelligent systems equipped with machine creativity that can perform design tasks automatically. The main challenge is how to model human beings' creativity mathematically and mimic such creativity computationally. We propose a “synthesis reasoning model” as the underlying mechanism to simulate human beings’ creative thinking when they are handling design tasks. We present the theory of the synthesis reasoning model, and the detailed procedure of designing an intelligent system based on the model.We offer a case study of an intelligent Chinese calligraphy generation system which we have developed.Based on implementation experiences of the calligraphy generation system as well as a few other systems for solving real-world problems, we suggest a generic methodology for constructing intelligent systems using the synthesis reasoning model.

Adult Gesture in Collaborative Mathematics Reasoning in Different Ages

Science.gov (United States)

Noto, M. S.; Harisman, Y.; Harun, L.; Amam, A.; Maarif, S.

2017-09-01

This article describes the case study on postgraduate students by using descriptive method. A problem is designed to facilitate the reasoning in the topic of Chi-Square test. The problem was given to two male students with different ages to investigate the gesture pattern and it will be related to their reasoning process. The indicators in reasoning problem can obtain the conclusion of analogy and generalization, and arrange the conjectures. This study refers to some questions—whether unique gesture is for every individual or to identify the pattern of the gesture used by the students with different ages. Reasoning problem was employed to collect the data. Two students were asked to collaborate to reason the problem. The discussion process recorded in using video tape to observe the gestures. The video recorded are explained clearly in this writing. Prosodic cues such as time, conversation text, gesture that appears, might help in understanding the gesture. The purpose of this study is to investigate whether different ages influences the maturity in collaboration observed from gesture perspective. The finding of this study shows that age is not a primary factor that influences the gesture in that reasoning process. In this case, adult gesture or gesture performed by order student does not show that he achieves, maintains, and focuses on the problem earlier on. Adult gesture also does not strengthen and expand the meaning if the student’s words or the language used in reasoning is not familiar for younger student. Adult gesture also does not affect cognitive uncertainty in mathematics reasoning. The future research is suggested to take more samples to find the consistency from that statement.

Measurement Models for Reasoned Action Theory.

Science.gov (United States)

Hennessy, Michael; Bleakley, Amy; Fishbein, Martin

2012-03-01

Quantitative researchers distinguish between causal and effect indicators. What are the analytic problems when both types of measures are present in a quantitative reasoned action analysis? To answer this question, we use data from a longitudinal study to estimate the association between two constructs central to reasoned action theory: behavioral beliefs and attitudes toward the behavior. The belief items are causal indicators that define a latent variable index while the attitude items are effect indicators that reflect the operation of a latent variable scale. We identify the issues when effect and causal indicators are present in a single analysis and conclude that both types of indicators can be incorporated in the analysis of data based on the reasoned action approach.

Lack of consent for mediation between companies and its reasons

OpenAIRE

Karpińska-Królikowska, Iwona

2011-01-01

This article discusses commercial mediation, presenting its principles and procedure. It shows the reason why I became interested in the topic of companies’ lack of willingness to solve problems through mediation. It presents empirical statistics from mediation in commercial cases, including those on lack of consents or settlements. The figures are shown against the background of court statistics. On the basis of research conducted in the form of case studies, it presents...

Case Study Observational Research: A Framework for Conducting Case Study Research Where Observation Data Are the Focus.

Science.gov (United States)

Morgan, Sonya J; Pullon, Susan R H; Macdonald, Lindsay M; McKinlay, Eileen M; Gray, Ben V

2017-06-01

Case study research is a comprehensive method that incorporates multiple sources of data to provide detailed accounts of complex research phenomena in real-life contexts. However, current models of case study research do not particularly distinguish the unique contribution observation data can make. Observation methods have the potential to reach beyond other methods that rely largely or solely on self-report. This article describes the distinctive characteristics of case study observational research, a modified form of Yin's 2014 model of case study research the authors used in a study exploring interprofessional collaboration in primary care. In this approach, observation data are positioned as the central component of the research design. Case study observational research offers a promising approach for researchers in a wide range of health care settings seeking more complete understandings of complex topics, where contextual influences are of primary concern. Future research is needed to refine and evaluate the approach.

Turkish Preservice Science Teachers' Informal Reasoning Regarding Socioscientific Issues and the Factors Influencing Their Informal Reasoning

Science.gov (United States)

Topçu, Mustafa Sami; Yılmaz-Tüzün, Özgül; Sadler, Troy D.

2011-06-01

The purpose of the study is to explore Turkish preservice science teachers' informal reasoning regarding socioscientific issues and the factors influencing their informal reasoning. The researchers engaged 39 preservice science teachers in informal reasoning interview and moral decision-making interview protocols. Of the seven socioscientific issues, three issues were related to gene therapy, another three were related to human cloning, and one was related to global warming. The data were analyzed using an interpretive qualitative research approach. The characteristic of informal reasoning was determined as multidimensional, and the patterns of informal reasoning emerged as rationalistic, emotive, and intuitive reasoning. The factors influencing informal reasoning were: personal experiences, social considerations, moral-ethical considerations, and technological concerns.

Reasons for receiving or not receiving HPV vaccination in primary schoolgirls in Tanzania: a case control study.

Directory of Open Access Journals (Sweden)

Deborah Watson-Jones

Full Text Available There are few data on factors influencing human papillomavirus (HPV vaccination uptake in sub-Saharan Africa. We examined the characteristics of receivers and non-receivers of HPV vaccination in Tanzania and identified reasons for not receiving the vaccine.We conducted a case control study of HPV vaccine receivers and non-receivers within a phase IV cluster-randomised trial of HPV vaccination in 134 primary schools in Tanzania. Girls who failed to receive vaccine (pupil cases and their parents/guardians (adult cases and girls who received dose 1 (pupil controls of the quadrivalent vaccine (Gardasil™ and their parents/guardians (adult controls were enrolled from 39 schools in a 1∶1 ratio and interviewed about cervical cancer, HPV vaccine knowledge and reasons why they might have received or not received the vaccine. Conditional logistic regression was used to determine factors independently associated with not receiving HPV vaccine.We interviewed 159 pupil/adult cases and 245 pupil/adult controls. Adult-factors independently associated with a daughter being a case were older age, owning fewer household items, not attending a school meeting about HPV vaccine, and not knowing anyone with cancer. Pupil-factors for being a case included having a non-positive opinion about the school de-worming programme, poor knowledge about the location of the cervix, and not knowing that a vaccine could prevent cervical cancer. Reasons for actively refusing vaccination included concerns about side effects and infertility. Most adult and pupil cases reported that they would accept the HPV vaccine if it were offered again (97% and 93% respectively.Sensitisation messages, especially targeted at older and poorer parents, knowledge retention and parent meetings are critical for vaccine acceptance in Tanzania. Vaccine side effects and fertility concerns should be addressed prior to a national vaccination program. Parents and pupils who initially decline vaccination

A Reasoning And Hypothesis-Generation Framework Based On Scalable Graph Analytics

Energy Technology Data Exchange (ETDEWEB)

Sukumar, Sreenivas Rangan [ORNL

2016-01-01

Finding actionable insights from data has always been difficult. As the scale and forms of data increase tremendously, the task of finding value becomes even more challenging. Data scientists at Oak Ridge National Laboratory are leveraging unique leadership infrastructure (e.g. Urika-XA and Urika-GD appliances) to develop scalable algorithms for semantic, logical and statistical reasoning with unstructured Big Data. We present the deployment of such a framework called ORiGAMI (Oak Ridge Graph Analytics for Medical Innovations) on the National Library of Medicine s SEMANTIC Medline (archive of medical knowledge since 1994). Medline contains over 70 million knowledge nuggets published in 23.5 million papers in medical literature with thousands more added daily. ORiGAMI is available as an open-science medical hypothesis generation tool - both as a web-service and an application programming interface (API) at http://hypothesis.ornl.gov . Since becoming an online service, ORIGAMI has enabled clinical subject-matter experts to: (i) discover the relationship between beta-blocker treatment and diabetic retinopathy; (ii) hypothesize that xylene is an environmental cancer-causing carcinogen and (iii) aid doctors with diagnosis of challenging cases when rare diseases manifest with common symptoms. In 2015, ORiGAMI was featured in the Historical Clinical Pathological Conference in Baltimore as a demonstration of artificial intelligence to medicine, IEEE/ACM Supercomputing and recognized as a Centennial Showcase Exhibit at the Radiological Society of North America (RSNA) Conference in Chicago. The final paper will describe the workflow built for the Cray Urika-XA and Urika-GD appliances that is able to reason with the knowledge of every published medical paper every time a clinical researcher uses the tool.

Probabilistic reasoning for assembly-based 3D modeling

KAUST Repository

Chaudhuri, Siddhartha

2011-01-01

Assembly-based modeling is a promising approach to broadening the accessibility of 3D modeling. In assembly-based modeling, new models are assembled from shape components extracted from a database. A key challenge in assembly-based modeling is the identification of relevant components to be presented to the user. In this paper, we introduce a probabilistic reasoning approach to this problem. Given a repository of shapes, our approach learns a probabilistic graphical model that encodes semantic and geometric relationships among shape components. The probabilistic model is used to present components that are semantically and stylistically compatible with the 3D model that is being assembled. Our experiments indicate that the probabilistic model increases the relevance of presented components. © 2011 ACM.

iCBLS: An interactive case-based learning system for medical education.

Science.gov (United States)

Ali, Maqbool; Han, Soyeon Caren; Bilal, Hafiz Syed Muhammad; Lee, Sungyoung; Kang, Matthew Jee Yun; Kang, Byeong Ho; Razzaq, Muhammad Asif; Amin, Muhammad Bilal

2018-01-01

Medical students should be able to actively apply clinical reasoning skills to further their interpretative, diagnostic, and treatment skills in a non-obtrusive and scalable way. Case-Based Learning (CBL) approach has been receiving attention in medical education as it is a student-centered teaching methodology that exposes students to real-world scenarios that need to be solved using their reasoning skills and existing theoretical knowledge. In this paper, we propose an interactive CBL System, called iCBLS, which supports the development of collaborative clinical reasoning skills for medical students in an online environment. The iCBLS consists of three modules: (i) system administration (SA), (ii) clinical case creation (CCC) with an innovative semi-automatic approach, and (iii) case formulation (CF) through intervention of medical students' and teachers' knowledge. Two evaluations under the umbrella of the context/input/process/product (CIPP) model have been performed with a Glycemia study. The first focused on the system satisfaction, evaluated by 54 students. The latter aimed to evaluate the system effectiveness, simulated by 155 students. The results show a high success rate of 70% for students' interaction, 76.4% for group learning, 72.8% for solo learning, and 74.6% for improved clinical skills. Copyright © 2017 Elsevier B.V. All rights reserved.

Fathers' Perceived Reasons for Their Underrepresentation in Child Health Research and Strategies to Increase Their Involvement.

Science.gov (United States)

Davison, Kirsten K; Charles, Jo N; Khandpur, Neha; Nelson, Timothy J

2017-02-01

Purpose Examine fathers' perceived reasons for their lack of inclusion in pediatric research and strategies to increase their participation. Description We conducted expert interviews with researchers and practitioners (N = 13) working with fathers to inform the development of an online survey. The survey-which measured fathers' perceived reasons for their underrepresentation in pediatric research, recommended recruitment venues, and research personnel and study characteristics valued by fathers-was distributed online and in-person to fathers. Assessment Respondents included 303 fathers. Over 80 % of respondents reported that fathers are underrepresented in pediatric research because they have not been asked to participate. Frequently recommended recruitment venues included community sports events (52 %), social service programs (48 %) and the internet (60 %). Compared with white fathers, more non-white fathers recommended public transit (19 % vs. 10 %, p = .02), playgrounds (16 % vs. 6 %, p = .007) and barber shops (34 % vs. 14 %, p research may increase if researchers explicitly invite father to participate, target father-focused recruitment venues, clearly communicate the benefits of the research for fathers and their families and adopt streamlined study procedures.

REASON-GIVING IN COURT PRACTICE: THE EXAMPLE OF FRENCH IMMIGRATION LITIGATION

Directory of Open Access Journals (Sweden)

Mathilde Cohen, Columbia Law School-School of Law, Estados Unidos

2012-10-01

Full Text Available Abstract: This Article examines the thesis according to which the practice of giving reasons for decisions is a central element of liberal democracies. In this view, public institutions’ practice—and sometimes duty—to give reasons is required so that each individual may view the state as reasonable and therefore, according to deliberative democratic theory, legitimate. Does the giving of reasons in actual court practice achieve these goals?  Drawing on empirical research carried out in a French administrative court, this Article argues that, in practice, reason-giving often falls either short of democracy or beyond democracy. Reasons fall short of democracy in the first case because they are transformed from a device designed to “protect” citizens from arbitrariness into a professional norm intended to “protect” the judges themselves and perhaps further their career goals. In the second case, reasons go beyond democracy because judges’ ambitions are much greater than to merely provide petitioners with a ground for understanding and criticizing the decision: they aim at positively—and paternalistically in some instances—guiding people’s conduct.  The discussion proceeds by drawing attention to social aspects that are often neglected in theoretical discussions on reason-giving. A skeptical conclusion is suggested: one can rarely guarantee that any predetermined value will be achieved by the giving of reasons. The degree to which individuals are empowered by the reasons given to them is dependent on the way in which decision-givers envision their reason-giving activity, and this representation is itself conditioned by the social setting of the court. Keywords: Arbitrariness. Reason-giving. Judges.

Research on Standard and Automatic Judgment of Press-fit Curve of Locomotive Wheel-set Based on AAR Standard

Science.gov (United States)

Lu, Jun; Xiao, Jun; Gao, Dong Jun; Zong, Shu Yu; Li, Zhu

2018-03-01

In the production of the Association of American Railroads (AAR) locomotive wheel-set, the press-fit curve is the most important basis for the reliability of wheel-set assembly. In the past, Most of production enterprises mainly use artificial detection methods to determine the quality of assembly. There are cases of miscarriage of justice appear. For this reason, the research on the standard is carried out. And the automatic judgment of press-fit curve is analysed and designed, so as to provide guidance for the locomotive wheel-set production based on AAR standard.

Reasoning and dyslexia: is visual memory a compensatory resource?

Science.gov (United States)

Bacon, Alison M; Handley, Simon J

2014-11-01

Effective reasoning is fundamental to problem solving and achievement in education and employment. Protocol studies have previously suggested that people with dyslexia use reasoning strategies based on visual mental representations, whereas non-dyslexics use abstract verbal strategies. This research presents converging evidence from experimental and individual differences perspectives. In Experiment 1, dyslexic and non-dyslexic participants were similarly accurate on reasoning problems, but scores on a measure of visual memory ability only predicted reasoning accuracy for dyslexics. In Experiment 2, a secondary task loaded visual memory resources during concurrent reasoning. Dyslexics were significantly less accurate when reasoning under conditions of high memory load and showed reduced ability to subsequently recall the visual stimuli, suggesting that the memory and reasoning tasks were competing for the same visual cognitive resource. The results are consistent with an explanation based on limitations in the verbal and executive components of working memory in dyslexia and the use of compensatory visual strategies for reasoning. There are implications for cognitive activities that do not readily support visual thinking, whether in education, employment or less formal everyday settings. Copyright © 2014 John Wiley & Sons, Ltd.

Single-Case Design Research: Building the Evidence-Base in the Field of Education of Deaf and Hard of Hearing Students.

Science.gov (United States)

Cannon, Joanna E; Guardino, Caroline; Antia, Shirin D; Luckner, John L

2016-01-01

The field of education of deaf and hard of hearing (DHH) students has a paucity of evidence-based practices (EBPs) to guide instruction. The authors discussed how the research methodology of single-case design (SCD) can be used to build EBPs through direct and systematic replication of studies. An overview of SCD research methods is presented, including an explanation of how internal and external validity issues are addressed, and why SCD is appropriate for intervention research with DHH children. The authors then examine the SCD research in the field according to quality indicators (QIs; at the individual level and as a body of evidence) to determine the existing evidence base. Finally, future replication areas are recommended to fill the gaps in SCD research with students who are DHH in order to add to the evidence base in the field.

Virtual patients design and its effect on clinical reasoning and student experience: a protocol for a randomised factorial multi-centre study

Directory of Open Access Journals (Sweden)

Bateman James

2012-08-01

Full Text Available Abstract Background Virtual Patients (VPs are web-based representations of realistic clinical cases. They are proposed as being an optimal method for teaching clinical reasoning skills. International standards exist which define precisely what constitutes a VP. There are multiple design possibilities for VPs, however there is little formal evidence to support individual design features. The purpose of this trial is to explore the effect of two different potentially important design features on clinical reasoning skills and the student experience. These are the branching case pathways (present or absent and structured clinical reasoning feedback (present or absent. Methods/Design This is a multi-centre randomised 2x2 factorial design study evaluating two independent variables of VP design, branching (present or absent, and structured clinical reasoning feedback (present or absent.The study will be carried out in medical student volunteers in one year group from three university medical schools in the United Kingdom, Warwick, Keele and Birmingham. There are four core musculoskeletal topics. Each case can be designed in four different ways, equating to 16 VPs required for the research. Students will be randomised to four groups, completing the four VP topics in the same order, but with each group exposed to a different VP design sequentially. All students will be exposed to the four designs. Primary outcomes are performance for each case design in a standardized fifteen item clinical reasoning assessment, integrated into each VP, which is identical for each topic. Additionally a 15-item self-reported evaluation is completed for each VP, based on a widely used EViP tool. Student patterns of use of the VPs will be recorded. In one centre, formative clinical and examination performance will be recorded, along with a self reported pre and post-intervention reasoning score, the DTI. Our power calculations indicate a sample size of 112 is required for

Case-Based Multi-Sensor Intrusion Detection

Science.gov (United States)

Schwartz, Daniel G.; Long, Jidong

2009-08-01

Multi-sensor intrusion detection systems (IDSs) combine the alerts raised by individual IDSs and possibly other kinds of devices such as firewalls and antivirus software. A critical issue in building a multi-sensor IDS is alert-correlation, i.e., determining which alerts are caused by the same attack. This paper explores a novel approach to alert correlation using case-based reasoning (CBR). Each case in the CBR system's library contains a pattern of alerts raised by some known attack type, together with the identity of the attack. Then during run time, the alert streams gleaned from the sensors are compared with the patterns in the cases, and a match indicates that the attack described by that case has occurred. For this purpose the design of a fast and accurate matching algorithm is imperative. Two such algorithms were explored: (i) the well-known Hungarian algorithm, and (ii) an order-preserving matching of our own device. Tests were conducted using the DARPA Grand Challenge Problem attack simulator. These showed that the both matching algorithms are effective in detecting attacks; but the Hungarian algorithm is inefficient; whereas the order-preserving one is very efficient, in fact runs in linear time.

The legal reasoning skills. Theoretical considerations

Directory of Open Access Journals (Sweden)

Lisett D. Páez Cuba

2014-06-01

Full Text Available This research analyzes the legal reasoning as essential skills to the teaching - learning process of law. This approach is based on a theoretical systematization of the Theory of Legal Argumentation (TLA that allows the conception of law as an argumentative act itself. It also determines, as a new element, the inclusion of legal argumentation as the final phase of the law cycle, which has particular impact on the teaching of this science. In this regard, the proposal of three skills of legal reasoning is made: interpreting the law, enforce the rule of law and legally argue the legal decision.

Brain Imaging, Forward Inference, and Theories of Reasoning

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Heit, Evan

2015-01-01

This review focuses on the issue of how neuroimaging studies address theoretical accounts of reasoning, through the lens of the method of forward inference (Henson, 2005, 2006). After theories of deductive and inductive reasoning are briefly presented, the method of forward inference for distinguishing between psychological theories based on brain imaging evidence is critically reviewed. Brain imaging studies of reasoning, comparing deductive and inductive arguments, comparing meaningful versus non-meaningful material, investigating hemispheric localization, and comparing conditional and relational arguments, are assessed in light of the method of forward inference. Finally, conclusions are drawn with regard to future research opportunities. PMID:25620926

Brain imaging, forward inference, and theories of reasoning.

Science.gov (United States)

Heit, Evan

2014-01-01

This review focuses on the issue of how neuroimaging studies address theoretical accounts of reasoning, through the lens of the method of forward inference (Henson, 2005, 2006). After theories of deductive and inductive reasoning are briefly presented, the method of forward inference for distinguishing between psychological theories based on brain imaging evidence is critically reviewed. Brain imaging studies of reasoning, comparing deductive and inductive arguments, comparing meaningful versus non-meaningful material, investigating hemispheric localization, and comparing conditional and relational arguments, are assessed in light of the method of forward inference. Finally, conclusions are drawn with regard to future research opportunities.

Using a Recommendation System to Support Problem Solving and Case-Based Reasoning Retrieval

Science.gov (United States)

Tawfik, Andrew A.; Alhoori, Hamed; Keene, Charles Wayne; Bailey, Christian; Hogan, Maureen

2018-01-01

In case library learning environments, learners are presented with an array of narratives that can be used to guide their problem solving. However, according to theorists, learners struggle to identify and retrieve the optimal case to solve a new problem. Given the challenges novice face during case retrieval, recommender systems can be embedded…

Structure induction in diagnostic causal reasoning.

Science.gov (United States)

Meder, Björn; Mayrhofer, Ralf; Waldmann, Michael R

2014-07-01

Our research examines the normative and descriptive adequacy of alternative computational models of diagnostic reasoning from single effects to single causes. Many theories of diagnostic reasoning are based on the normative assumption that inferences from an effect to its cause should reflect solely the empirically observed conditional probability of cause given effect. We argue against this assumption, as it neglects alternative causal structures that may have generated the sample data. Our structure induction model of diagnostic reasoning takes into account the uncertainty regarding the underlying causal structure. A key prediction of the model is that diagnostic judgments should not only reflect the empirical probability of cause given effect but should also depend on the reasoner's beliefs about the existence and strength of the link between cause and effect. We confirmed this prediction in 2 studies and showed that our theory better accounts for human judgments than alternative theories of diagnostic reasoning. Overall, our findings support the view that in diagnostic reasoning people go "beyond the information given" and use the available data to make inferences on the (unobserved) causal rather than on the (observed) data level. (c) 2014 APA, all rights reserved.

Faith-based perspectives on the use of chimeric organisms for medical research.

Science.gov (United States)

Degeling, Chris; Irvine, Rob; Kerridge, Ian

2014-04-01

Efforts to advance our understanding of neurodegenerative diseases involve the creation chimeric organisms from human neural stem cells and primate embryos--known as prenatal chimeras. The existence of potential mentally complex beings with human and non-human neural apparatus raises fundamental questions as to the ethical permissibility of chimeric research and the moral status of the creatures it creates. Even as bioethicists find fewer reasons to be troubled by most types of chimeric organisms, social attitudes towards the non-human world are often influenced by religious beliefs. In this paper scholars representing eight major religious traditions provide a brief commentary on a hypothetical case concerning the development and use of prenatal human-animal chimeric primates in medical research. These commentaries reflect the plurality and complexity within and between religious discourses of our relationships with other species. Views on the moral status and permissibility of research on neural human animal chimeras vary. The authors provide an introduction to those who seek a better understanding of how faith-based perspectives might enter into biomedical ethics and public discourse towards forms of biomedical research that involves chimeric organisms.

INTERNET BANKING ACCEPTANCE IN MALAYSIA BASED ON THE THEORY OF REASONED ACTION

Directory of Open Access Journals (Sweden)

J Michael Pearson

2008-09-01

Full Text Available ABSTRACT The theory of reasoned action originally introduced in the field of Social Psychology has been widely used to explain individuals’ behaviour. The theory postulates that individuals’ behaviour is influenced by their attitude and subjective norm. The purpose of this study was to determine factors that influence an individual’s intention to use a technology based on the theory of reasoned action. We used Internet banking as the target technology and Malaysian subjects as the sampling frame. A principal component analysis was used to validate the constructs and multiple regressions were used to analyze the data. As expected, the results supported the theory’s proposition as that an individuals’ behavioural intention to use Internet banking is influenced by their attitude and subjective norm. Based on the findings, theoretical and practical implications were offered. Keywords: theory of reasoned action, Internet banking, technology acceptance

Participatory scenario planning in place-based social-ecological research: insights and experiences from 23 case studies

Directory of Open Access Journals (Sweden)

Elisa Oteros-Rozas

2015-12-01

Full Text Available Participatory scenario planning (PSP is an increasingly popular tool in place-based environmental research for evaluating alternative futures of social-ecological systems. Although a range of guidelines on PSP methods are available in the scientific and grey literature, there is a need to reflect on existing practices and their appropriate application for different objectives and contexts at the local scale, as well as on their potential perceived outcomes. We contribute to theoretical and empirical frameworks by analyzing how and why researchers assess social-ecological systems using place-based PSP, hence facilitating the appropriate uptake of such scenario tools in the future. We analyzed 23 PSP case studies conducted by the authors in a wide range of social-ecological settings by exploring seven aspects: (1 the context; (2 the original motivations and objectives; (3 the methodological approach; (4 the process; (5 the content of the scenarios; (6 the outputs of the research; and (7 the monitoring and evaluation of the PSP process. This was complemented by a reflection on strengths and weaknesses of using PSP for the place-based social-ecological research. We conclude that the application of PSP, particularly when tailored to shared objectives between local people and researchers, has enriched environmental management and scientific research through building common understanding and fostering learning about future planning of social-ecological systems. However, PSP still requires greater systematic monitoring and evaluation to assess its impact on the promotion of collective action for transitions to sustainability and the adaptation to global environmental change and its challenges.

Archivists Killed for Political Reasons

NARCIS (Netherlands)

de Baets, Antoon

2015-01-01

This essay, Archivists Killed for Political Reasons, offers an overview of archivists who were killed for political reasons through the ages. After determining the criteria for inclusion, sixteen such political murders of archivists are briefly discussed. These cases were distributed over six

Generic project definitions for improvement of health care delivery: A case-base approach

NARCIS (Netherlands)

Niemeijer, G.C.; Does, R.J.M.M.; de Mast, J.; Trip, A.; van den Heuvel, J.

2011-01-01

Background: The purpose of this article is to create actionable knowledge, making the definition of process improvement projects in health care delivery more effective. Methods: This study is a retrospective analysis of process improvement projects in hospitals, facilitating a case-based reasoning

Implementation science: a role for parallel dual processing models of reasoning?

Science.gov (United States)

Sladek, Ruth M; Phillips, Paddy A; Bond, Malcolm J

2006-05-25

A better theoretical base for understanding professional behaviour change is needed to support evidence-based changes in medical practice. Traditionally strategies to encourage changes in clinical practices have been guided empirically, without explicit consideration of underlying theoretical rationales for such strategies. This paper considers a theoretical framework for reasoning from within psychology for identifying individual differences in cognitive processing between doctors that could moderate the decision to incorporate new evidence into their clinical decision-making. Parallel dual processing models of reasoning posit two cognitive modes of information processing that are in constant operation as humans reason. One mode has been described as experiential, fast and heuristic; the other as rational, conscious and rule based. Within such models, the uptake of new research evidence can be represented by the latter mode; it is reflective, explicit and intentional. On the other hand, well practiced clinical judgments can be positioned in the experiential mode, being automatic, reflexive and swift. Research suggests that individual differences between people in both cognitive capacity (e.g., intelligence) and cognitive processing (e.g., thinking styles) influence how both reasoning modes interact. This being so, it is proposed that these same differences between doctors may moderate the uptake of new research evidence. Such dispositional characteristics have largely been ignored in research investigating effective strategies in implementing research evidence. Whilst medical decision-making occurs in a complex social environment with multiple influences and decision makers, it remains true that an individual doctor's judgment still retains a key position in terms of diagnostic and treatment decisions for individual patients. This paper argues therefore, that individual differences between doctors in terms of reasoning are important considerations in any

Key-feature questions for assessment of clinical reasoning: a literature review.

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Hrynchak, Patricia; Takahashi, Susan Glover; Nayer, Marla

2014-09-01

Key-feature questions (KFQs) have been developed to assess clinical reasoning skills. The purpose of this paper is to review the published evidence on the reliability and validity of KFQs to assess clinical reasoning. A literature review was conducted by searching MEDLINE (1946-2012) and EMBASE (1980-2012) via OVID and ERIC. The following search terms were used: key feature; question or test or tests or testing or tested or exam; assess or evaluation, and case-based or case-specific. Articles not in English were eliminated. The literature search resulted in 560 articles. Duplicates were eliminated, as were articles that were not relevant; nine articles that contained reliability or validity data remained. A review of the references and of citations of these articles resulted in an additional 12 articles to give a total of 21 for this review. Format, language and scoring of KFQ examinations have been studied and modified to maximise reliability. Internal consistency reliability has been reported as being between 0.49 and 0.95. Face and content validity have been shown to be moderate to high. Construct validity has been shown to be good using vector thinking processes and novice versus expert paradigms, and to discriminate between teaching methods. The very modest correlations between KFQ examinations and more general knowledge-based examinations point to differing roles for each. Importantly, the results of KFQ examinations have been shown to successfully predict future physician performance, including patient outcomes. Although it is inaccurate to conclude that any testing format is universally reliable or valid, published research supports the use of examinations using KFQs to assess clinical reasoning. The review identifies areas of further study, including all categories of evidence. Investigation into how examinations using KFQs integrate with other methods in a system of assessment is needed. © 2014 John Wiley & Sons Ltd.

Formalization and Analysis of Reasoning by Assumption

NARCIS (Netherlands)

Bosse, T.; Jonker, C.M.; Treur, J.

2006-01-01

This article introduces a novel approach for the analysis of the dynamics of reasoning processes and explores its applicability for the reasoning pattern called reasoning by assumption. More specifically, for a case study in the domain of a Master Mind game, it is shown how empirical human reasoning

Principles for designing mathematical tasks that enhance imitative and creative reasoning

OpenAIRE

Lithner, Johan

2017-01-01

The design research programme Learning by Imitative and Creative Reasoning (LICR) studies whether, how and why tasks and teaching that enhance creative reasoning lead to a more productive struggle and more efficient learning than the common but inefficient task designs based on imitating given solution procedures. The purpose of this paper is to synthesise the research outcomes determined to date by providing the following: a conceptual framework for key concepts and relationships among teach...

Evidence-based policy learning: the case of the research excellence indicat

Energy Technology Data Exchange (ETDEWEB)

Hardeman, S.; Vertesy, D.

2016-07-01

Excellence is arguably the single most important concept in academia today, especially when it comes to science policy making. At the same time, however, excellence leads to a great amount of discomfort, leading some to plea for an overall rejection of the concept. The discomfort with excellence reaches its heights whenever proposals are made for measuring it. Yet, especially given the period of professionalization science policy making finds itself in, these same metrics are frequently called upon to legitimate policy interventions. Excellence and its measurement, it seems therefore, is something we can neither life with nor without. This paper offers some middle ground in the debate on excellence and its measurement for science policy purposes. Using the case of the European Commission’s Research Excellence Indicator as an example, we show how the development and use of indicators offers an opportunity for learning in science policy making. Ultimately, therefore, we show how and in what ways measuring excellence can contribute to evidence-based science policy learning in practice. (Author)

[Research and development of medical case database: a novel medical case information system integrating with biospecimen management].

Science.gov (United States)

Pan, Shiyang; Mu, Yuan; Wang, Hong; Wang, Tong; Huang, Peijun; Ma, Jianfeng; Jiang, Li; Zhang, Jie; Gu, Bing; Yi, Lujiang

2010-04-01

To meet the needs of management of medical case information and biospecimen simultaneously, we developed a novel medical case information system integrating with biospecimen management. The database established by MS SQL Server 2000 covered, basic information, clinical diagnosis, imaging diagnosis, pathological diagnosis and clinical treatment of patient; physicochemical property, inventory management and laboratory analysis of biospecimen; users log and data maintenance. The client application developed by Visual C++ 6.0 was used to implement medical case and biospecimen management, which was based on Client/Server model. This system can perform input, browse, inquest, summary of case and related biospecimen information, and can automatically synthesize case-records based on the database. Management of not only a long-term follow-up on individual, but also of grouped cases organized according to the aim of research can be achieved by the system. This system can improve the efficiency and quality of clinical researches while biospecimens are used coordinately. It realizes synthesized and dynamic management of medical case and biospecimen, which may be considered as a new management platform.

How novice, skilled and advanced clinical researchers include variables in a case report form for clinical research: a qualitative study.

Science.gov (United States)

Chu, Hongling; Zeng, Lin; Fetters, Micheal D; Li, Nan; Tao, Liyuan; Shi, Yanyan; Zhang, Hua; Wang, Xiaoxiao; Li, Fengwei; Zhao, Yiming

2017-09-18

Despite varying degrees in research training, most academic clinicians are expected to conduct clinical research. The objective of this research was to understand how clinical researchers of different skill levels include variables in a case report form for their clinical research. The setting for this research was a major academic institution in Beijing, China. The target population was clinical researchers with three levels of experience, namely, limited clinical research experience, clinicians with rich clinical research experience and clinical research experts. Using a qualitative approach, we conducted 13 individual interviews (face to face) and one group interview (n=4) with clinical researchers from June to September 2016. Based on maximum variation sampling to identify researchers with three levels of research experience: eight clinicians with limited clinical research experience, five clinicians with rich clinical research experience and four clinical research experts. These 17 researchers had diverse hospital-based medical specialties and or specialisation in clinical research. Our analysis yields a typology of three processes developing a case report form that varies according to research experience level. Novice clinician researchers often have an incomplete protocol or none at all, and conduct data collection and publication based on a general framework. Experienced clinician researchers include variables in the case report form based on previous experience with attention to including domains or items at risk for omission and by eliminating unnecessary variables. Expert researchers consider comprehensively in advance data collection and implementation needs and plan accordingly. These results illustrate increasing levels of sophistication in research planning that increase sophistication in selection for variables in the case report form. These findings suggest that novice and intermediate-level researchers could benefit by emulating the comprehensive