The Co-Emergence of Aggregate and Modelling Reasoning

Science.gov (United States)

Aridor, Keren; Ben-Zvi, Dani

2017-01-01

This article examines how two processes--reasoning with statistical modelling of a real phenomenon and aggregate reasoning--can co-emerge. We focus in this case study on the emergent reasoning of two fifth graders (aged 10) involved in statistical data analysis, informal inference, and modelling activities using TinkerPlots™. We describe nine…

Structured statistical models of inductive reasoning.

Science.gov (United States)

Kemp, Charles; Tenenbaum, Joshua B

2009-01-01

Everyday inductive inferences are often guided by rich background knowledge. Formal models of induction should aim to incorporate this knowledge and should explain how different kinds of knowledge lead to the distinctive patterns of reasoning found in different inductive contexts. This article presents a Bayesian framework that attempts to meet both goals and describes [corrected] 4 applications of the framework: a taxonomic model, a spatial model, a threshold model, and a causal model. Each model makes probabilistic inferences about the extensions of novel properties, but the priors for the 4 models are defined over different kinds of structures that capture different relationships between the categories in a domain. The framework therefore shows how statistical inference can operate over structured background knowledge, and the authors argue that this interaction between structure and statistics is critical for explaining the power and flexibility of human reasoning.

An integrated model of clinical reasoning: dual-process theory of cognition and metacognition.

Science.gov (United States)

Marcum, James A

2012-10-01

Clinical reasoning is an important component for providing quality medical care. The aim of the present paper is to develop a model of clinical reasoning that integrates both the non-analytic and analytic processes of cognition, along with metacognition. The dual-process theory of cognition (system 1 non-analytic and system 2 analytic processes) and the metacognition theory are used to develop an integrated model of clinical reasoning. In the proposed model, clinical reasoning begins with system 1 processes in which the clinician assesses a patient's presenting symptoms, as well as other clinical evidence, to arrive at a differential diagnosis. Additional clinical evidence, if necessary, is acquired and analysed utilizing system 2 processes to assess the differential diagnosis, until a clinical decision is made diagnosing the patient's illness and then how best to proceed therapeutically. Importantly, the outcome of these processes feeds back, in terms of metacognition's monitoring function, either to reinforce or to alter cognitive processes, which, in turn, enhances synergistically the clinician's ability to reason quickly and accurately in future consultations. The proposed integrated model has distinct advantages over other models proposed in the literature for explicating clinical reasoning. Moreover, it has important implications for addressing the paradoxical relationship between experience and expertise, as well as for designing a curriculum to teach clinical reasoning skills. © 2012 Blackwell Publishing Ltd.

Modelling Mathematical Reasoning in Physics Education

Science.gov (United States)

Uhden, Olaf; Karam, Ricardo; Pietrocola, Maurício; Pospiech, Gesche

2012-04-01

Many findings from research as well as reports from teachers describe students' problem solving strategies as manipulation of formulas by rote. The resulting dissatisfaction with quantitative physical textbook problems seems to influence the attitude towards the role of mathematics in physics education in general. Mathematics is often seen as a tool for calculation which hinders a conceptual understanding of physical principles. However, the role of mathematics cannot be reduced to this technical aspect. Hence, instead of putting mathematics away we delve into the nature of physical science to reveal the strong conceptual relationship between mathematics and physics. Moreover, we suggest that, for both prospective teaching and further research, a focus on deeply exploring such interdependency can significantly improve the understanding of physics. To provide a suitable basis, we develop a new model which can be used for analysing different levels of mathematical reasoning within physics. It is also a guideline for shifting the attention from technical to structural mathematical skills while teaching physics. We demonstrate its applicability for analysing physical-mathematical reasoning processes with an example.

Logical Reasoning versus Information Processing in the Dual-Strategy Model of Reasoning

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Markovits, Henry; Brisson, Janie; de Chantal, Pier-Luc

2017-01-01

One of the major debates concerning the nature of inferential reasoning is between counterexample-based strategies such as mental model theory and statistical strategies underlying probabilistic models. The dual-strategy model, proposed by Verschueren, Schaeken, & d'Ydewalle (2005a, 2005b), which suggests that people might have access to both…

Model-Based Reasoning in Humans Becomes Automatic with Training.

Directory of Open Access Journals (Sweden)

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.

The Probability Heuristics Model of Syllogistic Reasoning.

Science.gov (United States)

Chater, Nick; Oaksford, Mike

1999-01-01

Proposes a probability heuristic model for syllogistic reasoning and confirms the rationality of this heuristic by an analysis of the probabilistic validity of syllogistic reasoning that treats logical inference as a limiting case of probabilistic inference. Meta-analysis and two experiments involving 40 adult participants and using generalized…

New normative standards of conditional reasoning and the dual-source model.

Science.gov (United States)

Singmann, Henrik; Klauer, Karl Christoph; Over, David

2014-01-01

There has been a major shift in research on human reasoning toward Bayesian and probabilistic approaches, which has been called a new paradigm. The new paradigm sees most everyday and scientific reasoning as taking place in a context of uncertainty, and inference is from uncertain beliefs and not from arbitrary assumptions. In this manuscript we present an empirical test of normative standards in the new paradigm using a novel probabilized conditional reasoning task. Our results indicated that for everyday conditional with at least a weak causal connection between antecedent and consequent only the conditional probability of the consequent given antecedent contributes unique variance to predicting the probability of conditional, but not the probability of the conjunction, nor the probability of the material conditional. Regarding normative accounts of reasoning, we found significant evidence that participants' responses were confidence preserving (i.e., p-valid in the sense of Adams, 1998) for MP inferences, but not for MT inferences. Additionally, only for MP inferences and to a lesser degree for DA inferences did the rate of responses inside the coherence intervals defined by mental probability logic (Pfeifer and Kleiter, 2005, 2010) exceed chance levels. In contrast to the normative accounts, the dual-source model (Klauer et al., 2010) is a descriptive model. It posits that participants integrate their background knowledge (i.e., the type of information primary to the normative approaches) and their subjective probability that a conclusion is seen as warranted based on its logical form. Model fits showed that the dual-source model, which employed participants' responses to a deductive task with abstract contents to estimate the form-based component, provided as good an account of the data as a model that solely used data from the probabilized conditional reasoning task.

New Normative Standards of Conditional Reasoning and the Dual-Source Model

Directory of Open Access Journals (Sweden)

Henrik eSingmann

2014-04-01

Full Text Available There has been a major shift in research on human reasoning towards Bayesian and probabilistic approaches, which has been called a new paradigm. The new paradigm sees most everyday and scientific reasoning as taking place in a context of uncertainty, and inference is from uncertain beliefs and not from arbitrary assumptions. In this manuscript we present an empirical test of normative standards in the new paradigm using a novel probabilized conditional reasoning task. Our results indicated that for everyday conditional with at least a weak causal connection between antecedent and consequent only the conditional probability of the consequent given antecedent contributes unique variance to predicting the probability of conditional, but not the probability of the conjunction, nor the probability of the material conditional. Regarding normative accounts of reasoning, we found significant evidence that participants' responses were confidence preserving (i.e., p-valid in the sense of Adams, 1998 for MP inferences, but not for MT inferences. Additionally, only for MP inferences and to a lesser degree for DA inferences did the rate of responses inside the coherence intervals defined by mental probability logic (Pfeifer & Kleiter, 2005, 2010 exceed chance levels. In contrast to the normative accounts, the dual-source model (Klauer, Beller, & Hütter, 2010 is a descriptive model. It posits that participants integrate their background knowledge (i.e., the type of information primary to the normative approaches and their subjective probability that a conclusion is seen as warranted based on its logical form. Model fits showed that the dual-source model, which employed participants' responses to a deductive task with abstract contents to estimate the form-based component, provided as good an account of the data as a model that solely used data from the probabilized conditional reasoning task.

Exploring family physicians' reasons to continue or discontinue providing intrapartum care: Qualitative descriptive study.

Science.gov (United States)

Dove, Marion; Dogba, Maman Joyce; Rodríguez, Charo

2017-08-01

To examine the reasons why family physicians continue or discontinue providing intrapartum care in their clinical practice. Qualitative descriptive study. Two hospitals located in a multicultural area of Montreal, Que, in November 2011 to June 2012. Sixteen family physicians who were current or former providers of obstetric care. Data were collected using semistructured qualitative interviews. Thematic analysis was used to analyze the interview transcripts. Three overarching themes that help create understanding of why family doctors continue to provide obstetric care were identified: their attraction, often initiated by role models early in their careers, to practising complete continuity of care and accompanying patients in a special moment in their lives; the personal, family, and organizational pressures experienced while pursuing a family medicine career that includes obstetrics; and their ongoing reflection about continuing to practise obstetrics. The practice of obstetrics was very attractive to family physician participants whether they provided intrapartum care or decided to stop. More professional support and incentives might help keep family doctors practising obstetrics. Copyright© the College of Family Physicians of Canada.

Modeling mental spatial reasoning about cardinal directions.

Science.gov (United States)

Schultheis, Holger; Bertel, Sven; Barkowsky, Thomas

2014-01-01

This article presents research into human mental spatial reasoning with orientation knowledge. In particular, we look at reasoning problems about cardinal directions that possess multiple valid solutions (i.e., are spatially underdetermined), at human preferences for some of these solutions, and at representational and procedural factors that lead to such preferences. The article presents, first, a discussion of existing, related conceptual and computational approaches; second, results of empirical research into the solution preferences that human reasoners actually have; and, third, a novel computational model that relies on a parsimonious and flexible spatio-analogical knowledge representation structure to robustly reproduce the behavior observed with human reasoners. Copyright © 2014 Cognitive Science Society, Inc.

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…

Models of clinical reasoning with a focus on general practice: A critical review.

Science.gov (United States)

Yazdani, Shahram; Hosseinzadeh, Mohammad; Hosseini, Fakhrolsadat

2017-10-01

Diagnosis lies at the heart of general practice. Every day general practitioners (GPs) visit patients with a wide variety of complaints and concerns, with often minor but sometimes serious symptoms. General practice has many features which differentiate it from specialty care setting, but during the last four decades little attention was paid to clinical reasoning in general practice. Therefore, we aimed to critically review the clinical reasoning models with a focus on the clinical reasoning in general practice or clinical reasoning of general practitioners to find out to what extent the existing models explain the clinical reasoning specially in primary care and also identity the gaps of the model for use in primary care settings. A systematic search to find models of clinical reasoning were performed. To have more precision, we excluded the studies that focused on neurobiological aspects of reasoning, reasoning in disciplines other than medicine decision making or decision analysis on treatment or management plan. All the articles and documents were first scanned to see whether they include important relevant contents or any models. The selected studies which described a model of clinical reasoning in general practitioners or with a focus on general practice were then reviewed and appraisal or critics of other authors on these models were included. The reviewed documents on the model were synthesized. Six models of clinical reasoning were identified including hypothetic-deductive model, pattern recognition, a dual process diagnostic reasoning model, pathway for clinical reasoning, an integrative model of clinical reasoning, and model of diagnostic reasoning strategies in primary care. Only one model had specifically focused on general practitioners reasoning. A Model of clinical reasoning that included specific features of general practice to better help the general practitioners with the difficulties of clinical reasoning in this setting is needed.

Models of clinical reasoning with a focus on general practice: a critical review

Directory of Open Access Journals (Sweden)

SHAHRAM YAZDANI

2017-10-01

Full Text Available Introduction: Diagnosis lies at the heart of general practice. Every day general practitioners (GPs visit patients with a wide variety of complaints and concerns, with often minor but sometimes serious symptoms. General practice has many features which differentiate it from specialty care setting, but during the last four decades little attention was paid to clinical reasoning in general practice. Therefore, we aimed to critically review the clinical reasoning models with a focus on the clinical reasoning in general practice or clinical reasoning of general practitioners to find out to what extent the existing models explain the clinical reasoning specially in primary care and also identity the gaps of the model for use in primary care settings Methods: A systematic search to find models of clinical reasoning were performed. To have more precision, we excluded the studies that focused on neurobiological aspects of reasoning, reasoning in disciplines other than medicine decision making or decision analysis on treatment or management plan. All the articles and documents were first scanned to see whether they include important relevant contents or any models. The selected studies which described a model of clinical reasoning in general practitioners or with a focus on general practice were then reviewed and appraisal or critics of other authors on these models were included. The reviewed documents on the model were synthesized Results: Six models of clinical reasoning were identified including hypothetic-deductive model, pattern recognition, a dual process diagnostic reasoning model, pathway for clinical reasoning, an integrative model of clinical reasoning, and model of diagnostic reasoning strategies in primary care. Only one model had specifically focused on general practitioners reasoning. Conclusion: A Model of clinical reasoning that included specific features of general practice to better help the general practitioners with the difficulties

Improving statistical reasoning theoretical models and practical implications

CERN Document Server

Sedlmeier, Peter

1999-01-01

This book focuses on how statistical reasoning works and on training programs that can exploit people''s natural cognitive capabilities to improve their statistical reasoning. Training programs that take into account findings from evolutionary psychology and instructional theory are shown to have substantially larger effects that are more stable over time than previous training regimens. The theoretical implications are traced in a neural network model of human performance on statistical reasoning problems. This book apppeals to judgment and decision making researchers and other cognitive scientists, as well as to teachers of statistics and probabilistic reasoning.

Modeling visual problem solving as analogical reasoning.

Science.gov (United States)

Lovett, Andrew; Forbus, Kenneth

2017-01-01

We present a computational model of visual problem solving, designed to solve problems from the Raven's Progressive Matrices intelligence test. The model builds on the claim that analogical reasoning lies at the heart of visual problem solving, and intelligence more broadly. Images are compared via structure mapping, aligning the common relational structure in 2 images to identify commonalities and differences. These commonalities or differences can themselves be reified and used as the input for future comparisons. When images fail to align, the model dynamically rerepresents them to facilitate the comparison. In our analysis, we find that the model matches adult human performance on the Standard Progressive Matrices test, and that problems which are difficult for the model are also difficult for people. Furthermore, we show that model operations involving abstraction and rerepresentation are particularly difficult for people, suggesting that these operations may be critical for performing visual problem solving, and reasoning more generally, at the highest level. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Improving practical reasoning and argumentation

OpenAIRE

Baumtrog, Michael David

2015-01-01

This thesis justifies the need for and develops a new integrated model of practical reasoning and argumentation. After framing the work in terms of what is reasonable rather than what is rational (chapter 1), I apply the model for practical argumentation analysis and evaluation provided by Fairclough and Fairclough (2012) to a paradigm case of unreasonable individual practical argumentation provided by mass murderer Anders Behring Breivik (chapter 2). The application shows that by following t...

A Hierarchal Risk Assessment Model Using the Evidential Reasoning Rule

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Xiaoxiao Ji

2017-02-01

Full Text Available This paper aims to develop a hierarchical risk assessment model using the newly-developed evidential reasoning (ER rule, which constitutes a generic conjunctive probabilistic reasoning process. In this paper, we first provide a brief introduction to the basics of the ER rule and emphasize the strengths for representing and aggregating uncertain information from multiple experts and sources. Further, we discuss the key steps of developing the hierarchical risk assessment framework systematically, including (1 formulation of risk assessment hierarchy; (2 representation of both qualitative and quantitative information; (3 elicitation of attribute weights and information reliabilities; (4 aggregation of assessment information using the ER rule and (5 quantification and ranking of risks using utility-based transformation. The proposed hierarchical risk assessment framework can potentially be implemented to various complex and uncertain systems. A case study on the fire/explosion risk assessment of marine vessels demonstrates the applicability of the proposed risk assessment model.

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

Health, Supportive Environments, and the Reasonable Person Model

Science.gov (United States)

Stephen Kaplan; Rachel Kaplan

2003-01-01

The Reasonable Person Model is a conceptual framework that links environmental factors with human behavior. People are more reasonable, cooperative, helpful, and satisfied when the environment supports their basic informational needs. The same environmental supports are important factors in enhancing human health. We use this framework to identify the informational...

Symbolic Processing Combined with Model-Based Reasoning

Science.gov (United States)

James, Mark

2009-01-01

A computer program for the detection of present and prediction of future discrete states of a complex, real-time engineering system utilizes a combination of symbolic processing and numerical model-based reasoning. One of the biggest weaknesses of a purely symbolic approach is that it enables prediction of only future discrete states while missing all unmodeled states or leading to incorrect identification of an unmodeled state as a modeled one. A purely numerical approach is based on a combination of statistical methods and mathematical models of the applicable physics and necessitates development of a complete model to the level of fidelity required for prediction. In addition, a purely numerical approach does not afford the ability to qualify its results without some form of symbolic processing. The present software implements numerical algorithms to detect unmodeled events and symbolic algorithms to predict expected behavior, correlate the expected behavior with the unmodeled events, and interpret the results in order to predict future discrete states. The approach embodied in this software differs from that of the BEAM methodology (aspects of which have been discussed in several prior NASA Tech Briefs articles), which provides for prediction of future measurements in the continuous-data domain.

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

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...

Structured Statistical Models of Inductive Reasoning

Science.gov (United States)

Kemp, Charles; Tenenbaum, Joshua B.

2009-01-01

Everyday inductive inferences are often guided by rich background knowledge. Formal models of induction should aim to incorporate this knowledge and should explain how different kinds of knowledge lead to the distinctive patterns of reasoning found in different inductive contexts. This article presents a Bayesian framework that attempts to meet…

Paraconsistency, Pluralistic Models and Reasoning in Climate Science

Directory of Open Access Journals (Sweden)

Bryson Brown

2018-05-01

Full Text Available Scientific inquiry is typically focused on particular questions about particular objects and properties.  This leads to a multiplicity of models which, even when they draw on a single, consistent body of concepts and principles, often employ different methods and assumptions to model different systems.  Pluralists have remarked on how scientists draw on different assumptions to model different systems, different aspects of systems and systems under different conditions and defended the value of distinct, incompatible models within science at any given time. (Cartwright, 1999; Chang, 2012 Paraconsistentists have proposed logical strategies to avoid trivialization when inconsistencies arise by a variety of means.(Batens, 2001; Brown, 1990; Brown, 2002  Here we examine how chunk and permeate, a simple approach to paraconsistent reasoning which avoids heterodox logic by confining commitments to separate contexts in which reasoning with them is taken to be reliable while allowing ‘permeation’ of some conclusions into other contexts, can help to systematize pluralistic reasoning across the boundaries of plural contexts, using regional climate models as an example.(Benham et al., 2014; Brown & Priest 2004, 2015  The result is a kind of unity for science—but a unity achieved by the constrained exchange of specified information between different contexts, rather than the closure of all commitments under some paraconsistent consequence relation. 

Theoretical frameworks for the learning of geometrical reasoning

OpenAIRE

Jones, Keith

1998-01-01

With the growth in interest in geometrical ideas it is important to be clear about the nature of geometrical reasoning and how it develops. This paper provides an overview of three theoretical frameworks for the learning of geometrical reasoning: the van Hiele model of thinking in geometry, Fischbein’s theory of figural concepts, and Duval’s cognitive model of geometrical reasoning. Each of these frameworks provides theoretical resources to support research into the development of geometrical...

Sampling, Probability Models and Statistical Reasoning Statistical

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 1; Issue 5. Sampling, Probability Models and Statistical Reasoning Statistical Inference. Mohan Delampady V R Padmawar. General Article Volume 1 Issue 5 May 1996 pp 49-58 ...

Reasoning with probabilistic and deterministic graphical models exact algorithms

CERN Document Server

Dechter, Rina

2013-01-01

Graphical models (e.g., Bayesian and constraint networks, influence diagrams, and Markov decision processes) have become a central paradigm for knowledge representation and reasoning in both artificial intelligence and computer science in general. These models are used to perform many reasoning tasks, such as scheduling, planning and learning, diagnosis and prediction, design, hardware and software verification, and bioinformatics. These problems can be stated as the formal tasks of constraint satisfaction and satisfiability, combinatorial optimization, and probabilistic inference. It is well

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.

Modelling Chemical Reasoning to Predict and Invent Reactions.

Science.gov (United States)

Segler, Marwin H S; Waller, Mark P

2017-05-02

The ability to reason beyond established knowledge allows organic chemists to solve synthetic problems and invent novel transformations. Herein, we propose a model that mimics chemical reasoning, and formalises reaction prediction as finding missing links in a knowledge graph. We have constructed a knowledge graph containing 14.4 million molecules and 8.2 million binary reactions, which represents the bulk of all chemical reactions ever published in the scientific literature. Our model outperforms a rule-based expert system in the reaction prediction task for 180 000 randomly selected binary reactions. The data-driven model generalises even beyond known reaction types, and is thus capable of effectively (re-)discovering novel transformations (even including transition metal-catalysed reactions). Our model enables computers to infer hypotheses about reactivity and reactions by only considering the intrinsic local structure of the graph and because each single reaction prediction is typically achieved in a sub-second time frame, the model can be used as a high-throughput generator of reaction hypotheses for reaction discovery. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Improving statistical reasoning: theoretical models and practical implications

National Research Council Canada - National Science Library

Sedlmeier, Peter

1999-01-01

... in Psychology? 206 References 216 Author Index 230 Subject Index 235 v PrefacePreface Statistical literacy, the art of drawing reasonable inferences from an abundance of numbers provided daily by...

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

CERN Document Server

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...

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.

Rational speech act models of pragmatic reasoning in reference games

OpenAIRE

Frank, Michael

2016-01-01

Human communication is almost always ambiguous, but it typically takes place in a context where this ambiguity can be resolved. A key part of this process of disambiguation comes from pragmatic reasoning about alternative messages that a speaker could have said in that context. Following previous work, we describe pragmatic inference as recursive reasoning – in which listeners reason about speakers and vice versa – using a “rational speech act” (RSA) model. We then systematically test the par...

Training propositional reasoning.

Science.gov (United States)

Klauer, K C; Meiser, T; Naumer, B

2000-08-01

Two experiments compared the effects of four training conditions on propositional reasoning. A syntactic training demonstrated formal derivations, in an abstract semantic training the standard truth-table definitions of logical connectives were explained, and a domain-specific semantic training provided thematic contexts for the premises of the reasoning task. In a control training, an inductive reasoning task was practised. In line with the account by mental models, both kinds of semantic training were significantly more effective than the control and the syntactic training, whereas there were no significant differences between the control and the syntactic training, nor between the two kinds of semantic training. Experiment 2 replicated this pattern of effects using a different set of syntactic and domain-specific training conditions.

The Coastal Zone: Man and Nature. An Application of the Socio-Scientific Reasoning Model.

Science.gov (United States)

Maul, June Paradise; And Others

The curriculum model described here has been designed by incorporating the socio-scientific reasoning model with a simulation design in an attempt to have students investigate the onshore impacts of Outer Continental Shelf (OCS) gas and oil development. The socio-scientific reasoning model incorporates a logical/physical reasoning component as…

Speed of reasoning and its relation to reasoning ability

NARCIS (Netherlands)

Goldhammer, F.; Klein Entink, R.H.

2011-01-01

The study investigates empirical properties of reasoning speed which is conceived as the fluency of solving reasoning problems. Responses and response times in reasoning tasks are modeled jointly to clarify the covariance structure of reasoning speed and reasoning ability. To determine underlying

Gambling and the Reasoned Action Model: Predicting Past Behavior, Intentions, and Future Behavior.

Science.gov (United States)

Dahl, Ethan; Tagler, Michael J; Hohman, Zachary P

2018-03-01

Gambling is a serious concern for society because it is highly addictive and is associated with a myriad of negative outcomes. The current study applied the Reasoned Action Model (RAM) to understand and predict gambling intentions and behavior. Although prior studies have taken a reasoned action approach to understand gambling, no prior study has fully applied the RAM or used the RAM to predict future gambling. Across two studies the RAM was used to predict intentions to gamble, past gambling behavior, and future gambling behavior. In study 1 the model significantly predicted intentions and past behavior in both a college student and Amazon Mechanical Turk sample. In study 2 the model predicted future gambling behavior, measured 2 weeks after initial measurement of the RAM constructs. This study stands as the first to show the utility of the RAM in predicting future gambling behavior. Across both studies, attitudes and perceived normative pressure were the strongest predictors of intentions to gamble. These findings provide increased understanding of gambling and inform the development of gambling interventions based on the RAM.

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).

Practical Application of the MFM Suite on a PWR System: Modelling and Reasoning on Causes and Consequences of Process Anomalies

DEFF Research Database (Denmark)

Zhang, Xinxin; Thunem, Harald P - J; Lind, Morten

2014-01-01

and linking the MFM model to its process components. The purpose of this report is to make a comprehensive demonstration of how to use the MFM Suite to develop MFM models and run causal reasoning for abnormal situations. This report will explain the capability of representing process and operational knowledge...... by using the MFM methodolog y, and demonstrate how the model combined with the MFM reasoning can be used to evaluate the plant state, identify the current situation and support operational decisions. The report will provide a detailed explanation of MFM concepts by modelling the prim ary side system...... systems. Two of the modelling examples can be found in HWR - 990 and HWR - 1059. The inherent causal reasoning capability enabled the developed MFM models to be used for diagnostic and prognostic analysis. These MFM models h ave been used to develop the basis for implementing operator support tools...

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.

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

Measurement Model of Reasoning Skills among Science Students Based on Socio Scientific Issues (SSI

Directory of Open Access Journals (Sweden)

MOHD AFIFI BAHURUDIN SETAMBAH

2018-05-01

Full Text Available The lack of reasoning skills has been recognized as one of the contributing factors to the declined achievement in the Trends in Mathematics and Science Studies (TIMSS and Programme for International Student Assessment (PISA assessments in Malaysia. The use of socio-scientific issues (SSI as a learning strategy offers the potential of improving the level of students' reasoning skills and consequently improves students’ achievement in science subjects. This study examined the development of a measurement model of reasoning skills among science students based on SSI using the analysis of moment structure (AMOS approach before going to second level to full structured equation modelling (SEM. A total of 450 respondents were selected using a stratified random sampling. Results showed a modified measurement model of reasoning skills consisting of the View Knowledge (VK was as a main construct. The items that measure the level of pre-reflection of students fulfilled the elements of unidimensionality, validity, and reliability. Although the level of student reasoning skills was still low but this development of measurement model could be identified and proposed teaching methods that could be adopted to improve students’ reasoning skills.

Anthropic Reasoning about Fine-Tuning, and Neoclassical Cosmology: Providence, Omnipresence, and Observation Selection Theory

Science.gov (United States)

Walker, Theodore, Jr.

2011-10-01

Anthropic reasoning about observation selection effects upon the appearance of cosmic providential fine-tuning (fine-tuning that provides for life) is often motivated by a desire to avoid theological implications (implications favoring the idea of a divine cosmic provider) without appealing to sheer lucky-for-us-cosmic-jackpot happenstance and coincidence. Cosmic coincidence can be rendered less incredible by appealing to a multiverse context. Cosmic providence can be rendered non-theological by appealing to an agent-less providential purpose, or by appealing to less-than-omnipresent/local providers, such as alien intelligences creating life- providing baby universes. Instead of choosing either cosmic coincidence or cosmic providence, as though they were mutually exclusive; it is better to accept both. Neoclassical thought accepts coincidence and providence, plus many local providers and one omnipresent provider. Moreover, fundamental observation selection theory should distinguish the many local observers of some events from the one omnipresent observer of all events. Accepting both coincidence and providence avoids classical theology (providence without coincidence) and classical atheism (coincidence without providence), but not neoclassical theology (providence with coincidence). Cosmology cannot avoid the idea of an all-inclusive omnipresent providential dice-throwing living-creative whole of reality, an idea essential to neoclassical theology, and to neoclassical cosmology.

Eye movements provide insight into individual differences in children's analogical reasoning strategies.

Science.gov (United States)

Starr, Ariel; Vendetti, Michael S; Bunge, Silvia A

2018-05-01

Analogical reasoning is considered a key driver of cognitive development and is a strong predictor of academic achievement. However, it is difficult for young children, who are prone to focusing on perceptual and semantic similarities among items rather than relational commonalities. For example, in a classic A:B::C:? propositional analogy task, children must inhibit attention towards items that are visually or semantically similar to C, and instead focus on finding a relational match to the A:B pair. Competing theories of reasoning development attribute improvements in children's performance to gains in either executive functioning or semantic knowledge. Here, we sought to identify key drivers of the development of analogical reasoning ability by using eye gaze patterns to infer problem-solving strategies used by six-year-old children and adults. Children had a greater tendency than adults to focus on the immediate task goal and constrain their search based on the C item. However, large individual differences existed within children, and more successful reasoners were able to maintain the broader goal in mind and constrain their search by initially focusing on the A:B pair before turning to C and the response choices. When children adopted this strategy, their attention was drawn more readily to the correct response option. Individual differences in children's reasoning ability were also related to rule-guided behavior but not to semantic knowledge. These findings suggest that both developmental improvements and individual differences in performance are driven by the use of more efficient reasoning strategies regarding which information is prioritized from the start, rather than the ability to disengage from attractive lure items. Copyright © 2018 Elsevier B.V. All rights reserved.

Electronic cigarette use among patients with cancer: Reasons for use, beliefs, and patient-provider communication.

Science.gov (United States)

Correa, John B; Brandon, Karen O; Meltzer, Lauren R; Hoehn, Hannah J; Piñeiro, Bárbara; Brandon, Thomas H; Simmons, Vani N

2018-04-19

Smoking tobacco cigarettes after a cancer diagnosis increases risk for several serious adverse outcomes. Thus, patients can significantly benefit from quitting smoking. Electronic cigarettes are an increasingly popular cessation method. Providers routinely ask about combustible cigarette use, yet little is known about use and communication surrounding e-cigarettes among patients with cancer. This study aims to describe patterns, beliefs, and communication with oncology providers about e-cigarette use of patients with cancer. Patients with cancer (N = 121) who currently used e-cigarettes were surveyed in a cross-sectional study about their patterns and reasons for use, beliefs, and perceptions of risk for e-cigarettes, combustible cigarettes, and nicotine replacement therapies. Patient perspectives on provider communication regarding e-cigarettes were also assessed. Most participants identified smoking cessation as the reason for initiating (81%) and continuing (60%) e-cigarette use. However, 51% of patients reported current dual use of combustible cigarettes and e-cigarettes, and most patients reported never having discussed their use of e-cigarettes with their oncology provider (72%). Patients characterized e-cigarettes as less addictive, less expensive, less stigmatizing, and less likely to impact cancer treatment than combustible cigarettes (Ps < .05), and more satisfying, more useful for quitting smoking, and more effective at reducing cancer-related stress than nicotine replacement therapies (Ps < .05). Patients with cancer who use e-cigarettes have positive attitudes toward these devices and use them to aid in smoking cessation. This study also highlights the need for improved patient-provider communication on the safety and efficacy of e-cigarettes for smoking cessation. Copyright © 2018 John Wiley & Sons, Ltd.

CAD Parts-Based Assembly Modeling by Probabilistic Reasoning

KAUST Repository

Zhang, Kai-Ke

2016-04-11

Nowadays, increasing amount of parts and sub-assemblies are publicly available, which can be used directly for product development instead of creating from scratch. In this paper, we propose an interactive design framework for efficient and smart assembly modeling, in order to improve the design efficiency. Our approach is based on a probabilistic reasoning. Given a collection of industrial assemblies, we learn a probabilistic graphical model from the relationships between the parts of assemblies. Then in the modeling stage, this probabilistic model is used to suggest the most likely used parts compatible with the current assembly. Finally, the parts are assembled under certain geometric constraints. We demonstrate the effectiveness of our framework through a variety of assembly models produced by our prototype system. © 2015 IEEE.

CAD Parts-Based Assembly Modeling by Probabilistic Reasoning

KAUST Repository

Zhang, Kai-Ke; Hu, Kai-Mo; Yin, Li-Cheng; Yan, Dongming; Wang, Bin

2016-01-01

Nowadays, increasing amount of parts and sub-assemblies are publicly available, which can be used directly for product development instead of creating from scratch. In this paper, we propose an interactive design framework for efficient and smart assembly modeling, in order to improve the design efficiency. Our approach is based on a probabilistic reasoning. Given a collection of industrial assemblies, we learn a probabilistic graphical model from the relationships between the parts of assemblies. Then in the modeling stage, this probabilistic model is used to suggest the most likely used parts compatible with the current assembly. Finally, the parts are assembled under certain geometric constraints. We demonstrate the effectiveness of our framework through a variety of assembly models produced by our prototype system. © 2015 IEEE.

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.

All Roads Lead to Fault Diagnosis : Model-Based Reasoning with LYDIA

NARCIS (Netherlands)

Feldman, A.B.; Pietersma, J.; Van Gemund, A.J.C.

2006-01-01

Model-Based Reasoning (MBR) over qualitative models of complex, real-world systems has proven succesful for automated fault diagnosis, control, and repair. Expressing a system under diagnosis in a formal model and infering a diagnosis given observations are both challenging problems. In this paper

Models of Human Information Requirements: "When Reasonable Aiding Systems Disagree"

Science.gov (United States)

Corker, Kevin; Pisanich, Gregory; Shafto, Michael (Technical Monitor)

1994-01-01

Aircraft flight management and Air Traffic Control (ATC) automation are under development to maximize the economy of flight and to increase the capacity of the terminal area airspace while maintaining levels of flight safety equal to or better than current system performance. These goals are being realized by the introduction of flight management automation aiding and operations support systems on the flight deck and by new developments of ATC aiding systems that seek to optimize scheduling of aircraft while potentially reducing required separation and accounting for weather and wake vortex turbulence. Aiding systems on both the flight deck and the ground operate through algorithmic functions on models of the aircraft and of the airspace. These models may differ from each other as a result of variations in their models of the immediate environment. The resultant flight operations or ATC commands may differ in their response requirements (e.g. different preferred descent speeds or descent initiation points). The human operators in the system must then interact with the automation to reconcile differences and resolve conflicts. We have developed a model of human performance including cognitive functions (decision-making, rule-based reasoning, procedural interruption recovery and forgetting) that supports analysis of the information requirements for resolution of flight aiding and ATC conflicts. The model represents multiple individuals in the flight crew and in ATC. The model is supported in simulation on a Silicon Graphics' workstation using Allegro Lisp. Design guidelines for aviation automation aiding systems have been developed using the model's specification of information and team procedural requirements. Empirical data on flight deck operations from full-mission flight simulation are provided to support the model's predictions. The paper describes the model, its development and implementation, the simulation test of the model predictions, and the empirical

Developing Computer Model-Based Assessment of Chemical Reasoning: A Feasibility Study

Science.gov (United States)

Liu, Xiufeng; Waight, Noemi; Gregorius, Roberto; Smith, Erica; Park, Mihwa

2012-01-01

This paper reports a feasibility study on developing computer model-based assessments of chemical reasoning at the high school level. Computer models are flash and NetLogo environments to make simultaneously available three domains in chemistry: macroscopic, submicroscopic, and symbolic. Students interact with computer models to answer assessment…

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.

The heuristic-analytic theory of reasoning: extension and evaluation.

Science.gov (United States)

Evans, Jonathan St B T

2006-06-01

An extensively revised heuristic-analytic theory of reasoning is presented incorporating three principles of hypothetical thinking. The theory assumes that reasoning and judgment are facilitated by the formation of epistemic mental models that are generated one at a time (singularity principle) by preconscious heuristic processes that contextualize problems in such a way as to maximize relevance to current goals (relevance principle). Analytic processes evaluate these models but tend to accept them unless there is good reason to reject them (satisficing principle). At a minimum, analytic processing of models is required so as to generate inferences or judgments relevant to the task instructions, but more active intervention may result in modification or replacement of default models generated by the heuristic system. Evidence for this theory is provided by a review of a wide range of literature on thinking and 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

Do Different Mental Models Influence Cybersecurity Behavior? Evaluations via Statistical Reasoning Performance.

Science.gov (United States)

Brase, Gary L; Vasserman, Eugene Y; Hsu, William

2017-01-01

Cybersecurity research often describes people as understanding internet security in terms of metaphorical mental models (e.g., disease risk, physical security risk, or criminal behavior risk). However, little research has directly evaluated if this is an accurate or productive framework. To assess this question, two experiments asked participants to respond to a statistical reasoning task framed in one of four different contexts (cybersecurity, plus the above alternative models). Each context was also presented using either percentages or natural frequencies, and these tasks were followed by a behavioral likelihood rating. As in previous research, consistent use of natural frequencies promoted correct Bayesian reasoning. There was little indication, however, that any of the alternative mental models generated consistently better understanding or reasoning over the actual cybersecurity context. There was some evidence that different models had some effects on patterns of responses, including the behavioral likelihood ratings, but these effects were small, as compared to the effect of the numerical format manipulation. This points to a need to improve the content of actual internet security warnings, rather than working to change the models users have of warnings.

Do Different Mental Models Influence Cybersecurity Behavior? Evaluations via Statistical Reasoning Performance

Directory of Open Access Journals (Sweden)

Gary L. Brase

2017-11-01

Full Text Available Cybersecurity research often describes people as understanding internet security in terms of metaphorical mental models (e.g., disease risk, physical security risk, or criminal behavior risk. However, little research has directly evaluated if this is an accurate or productive framework. To assess this question, two experiments asked participants to respond to a statistical reasoning task framed in one of four different contexts (cybersecurity, plus the above alternative models. Each context was also presented using either percentages or natural frequencies, and these tasks were followed by a behavioral likelihood rating. As in previous research, consistent use of natural frequencies promoted correct Bayesian reasoning. There was little indication, however, that any of the alternative mental models generated consistently better understanding or reasoning over the actual cybersecurity context. There was some evidence that different models had some effects on patterns of responses, including the behavioral likelihood ratings, but these effects were small, as compared to the effect of the numerical format manipulation. This points to a need to improve the content of actual internet security warnings, rather than working to change the models users have of warnings.

A qualitative reasoning model of algal bloom in the Danube Delta Biosphere Reserve (DDBR)

NARCIS (Netherlands)

Cioaca, E.; Linnebank, F.E.; Bredeweg, B.; Salles, P.

2009-01-01

This paper presents a Qualitative Reasoning model of the algal bloom phenomenon and its effects in the Danube Delta Biosphere Reserve (DDBR) in Romania. Qualitative Reasoning models represent processes and their cause-effect relationships in a flexible and conceptually rich manner and as such can be

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...

Non-monotonic reasoning in conceptual modeling and ontology design: A proposal

CSIR Research Space (South Africa)

Casini, G

2013-06-01

Full Text Available -1 2nd International Workshop on Ontologies and Conceptual Modeling (Onto.Com 2013), Valencia, Spain, 17-21 June 2013 Non-monotonic reasoning in conceptual modeling and ontology design: A proposal Giovanni Casini1 and Alessandro Mosca2 1...

A Chemistry Concept Reasoning Test

Science.gov (United States)

Cloonan, Carrie A.; Hutchinson, John S.

2011-01-01

A Chemistry Concept Reasoning Test was created and validated providing an easy-to-use tool for measuring conceptual understanding and critical scientific thinking of general chemistry models and theories. The test is designed to measure concept understanding comparable to that found in free-response questions requiring explanations over…

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.

Clinical Reasoning in Athletic Training Education: Modeling Expert Thinking

Science.gov (United States)

Geisler, Paul R.; Lazenby, Todd W.

2009-01-01

Objective: To address the need for a more definitive approach to critical thinking during athletic training educational experiences by introducing the clinical reasoning model for critical thinking. Background: Educators are aware of the need to teach students how to think critically. The multiple domains of athletic training are comprehensive and…

High-school students' reasoning while constructing plant growth models in a computer-supported educational environment

Science.gov (United States)

Ergazaki, Marida; Komis, Vassilis; Zogza, Vassiliki

2005-08-01

This paper highlights specific aspects of high-school students’ reasoning while coping with a modeling task of plant growth in a computer-supported educational environment. It is particularly concerned with the modeling levels (‘macro-phenomenological’ and ‘micro-conceptual’ level) activated by peers while exploring plant growth and with their ability to shift between or within these levels. The focus is on the types of reasoning developed in the modeling process, as well as on the reasoning coherence around the central concept of plant growth. The findings of the study show that a significant proportion of the 18 participating dyads perform modeling on both levels, while their ability to shift between them as well as between the various elements of the ‘micro-conceptual’ level is rather constrained. Furthermore, the reasoning types identified in peers’ modeling process are ‘convergent’, ‘serial’, ‘linked’ and ‘convergent attached’, with the first type being the most frequent. Finally, a significant part of the participating dyads display a satisfactory degree of reasoning ‘coherence’, performing their task committed to the main objective of exploring plant growth. Teaching implications of the findings are also discussed.

Clinical cognition and diagnostic error: applications of a dual process model of reasoning.

Science.gov (United States)

Croskerry, Pat

2009-09-01

Both systemic and individual factors contribute to missed or delayed diagnoses. Among the multiple factors that impact clinical performance of the individual, the caliber of cognition is perhaps the most relevant and deserves our attention and understanding. In the last few decades, cognitive psychologists have gained substantial insights into the processes that underlie cognition, and a new, universal model of reasoning and decision making has emerged, Dual Process Theory. The theory has immediate application to medical decision making and provides an overall schema for understanding the variety of theoretical approaches that have been taken in the past. The model has important practical applications for decision making across the multiple domains of healthcare, and may be used as a template for teaching decision theory, as well as a platform for future research. Importantly, specific operating characteristics of the model explain how diagnostic failure occurs.

Learning clinical reasoning.

Science.gov (United States)

Pinnock, Ralph; Welch, Paul

2014-04-01

Errors in clinical reasoning continue to account for significant morbidity and mortality, despite evidence-based guidelines and improved technology. Experts in clinical reasoning often use unconscious cognitive processes that they are not aware of unless they explain how they are thinking. Understanding the intuitive and analytical thinking processes provides a guide for instruction. How knowledge is stored is critical to expertise in clinical reasoning. Curricula should be designed so that trainees store knowledge in a way that is clinically relevant. Competence in clinical reasoning is acquired by supervised practice with effective feedback. Clinicians must recognise the common errors in clinical reasoning and how to avoid them. Trainees can learn clinical reasoning effectively in everyday practice if teachers provide guidance on the cognitive processes involved in making diagnostic decisions. © 2013 The Authors. Journal of Paediatrics and Child Health © 2013 Paediatrics and Child Health Division (Royal Australasian College of Physicians).

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

Directory of Open Access Journals (Sweden)

Phillips Paddy A

2006-05-01

Full Text Available Abstract Background 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. Discussion 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

Quantitative Reasoning Learning Progressions for Environmental Science: Developing a Framework

Directory of Open Access Journals (Sweden)

Robert L. Mayes

2013-01-01

Full Text Available Quantitative reasoning is a complex concept with many definitions and a diverse account in the literature. The purpose of this article is to establish a working definition of quantitative reasoning within the context of science, construct a quantitative reasoning framework, and summarize research on key components in that framework. Context underlies all quantitative reasoning; for this review, environmental science serves as the context.In the framework, we identify four components of quantitative reasoning: the quantification act, quantitative literacy, quantitative interpretation of a model, and quantitative modeling. Within each of these components, the framework provides elements that comprise the four components. The quantification act includes the elements of variable identification, communication, context, and variation. Quantitative literacy includes the elements of numeracy, measurement, proportional reasoning, and basic probability/statistics. Quantitative interpretation includes the elements of representations, science diagrams, statistics and probability, and logarithmic scales. Quantitative modeling includes the elements of logic, problem solving, modeling, and inference. A brief comparison of the quantitative reasoning framework with the AAC&U Quantitative Literacy VALUE rubric is presented, demonstrating a mapping of the components and illustrating differences in structure. The framework serves as a precursor for a quantitative reasoning learning progression which is currently under development.

The Cognitive-Miser Response Model: Testing for Intuitive and Deliberate Reasoning

Science.gov (United States)

Bockenholt, Ulf

2012-01-01

In a number of psychological studies, answers to reasoning vignettes have been shown to result from both intuitive and deliberate response processes. This paper utilizes a psychometric model to separate these two response tendencies. An experimental application shows that the proposed model facilitates the analysis of dual-process item responses…

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.

Nurses' intention to leave: critically analyse the theory of reasoned action and organizational commitment model.

Science.gov (United States)

Liou, Shwu-Ru

2009-01-01

To systematically analyse the Organizational Commitment model and Theory of Reasoned Action and determine concepts that can better explain nurses' intention to leave their job. The Organizational Commitment model and Theory of Reasoned Action have been proposed and applied to understand intention to leave and turnover behaviour, which are major contributors to nursing shortage. However, the appropriateness of applying these two models in nursing was not analysed. Three main criteria of a useful model were used for the analysis: consistency in the use of concepts, testability and predictability. Both theories use concepts consistently. Concepts in the Theory of Reasoned Action are defined broadly whereas they are operationally defined in the Organizational Commitment model. Predictability of the Theory of Reasoned Action is questionable whereas the Organizational Commitment model can be applied to predict intention to leave. A model was proposed based on this analysis. Organizational commitment, intention to leave, work experiences, job characteristics and personal characteristics can be concepts for predicting nurses' intention to leave. Nursing managers may consider nurses' personal characteristics and experiences to increase their organizational commitment and enhance their intention to stay. Empirical studies are needed to test and cross-validate the re-synthesized model for nurses' intention to leave their job.

What variables can influence clinical reasoning?

Directory of Open Access Journals (Sweden)

Vahid Ashoorion

2012-01-01

Full Text Available Background: Clinical reasoning is one of the most important competencies that a physician should achieve. Many medical schools and licensing bodies try to predict it based on some general measures such as critical thinking, personality, and emotional intelligence. This study aimed at providing a model to design the relationship between the constructs. Materials and Methods: Sixty-nine medical students participated in this study. A battery test devised that consist four parts: Clinical reasoning measures, personality NEO inventory, Bar-On EQ inventory, and California critical thinking questionnaire. All participants completed the tests. Correlation and multiple regression analysis consumed for data analysis. Results: There is low to moderate correlations between clinical reasoning and other variables. Emotional intelligence is the only variable that contributes clinical reasoning construct (r=0.17-0.34 (R 2 chnage = 0.46, P Value = 0.000. Conclusion: Although, clinical reasoning can be considered as a kind of thinking, no significant correlation detected between it and other constructs. Emotional intelligence (and its subscales is the only variable that can be used for clinical reasoning prediction.

What variables can influence clinical reasoning?

Science.gov (United States)

Ashoorion, Vahid; Liaghatdar, Mohammad Javad; Adibi, Peyman

2012-12-01

Clinical reasoning is one of the most important competencies that a physician should achieve. Many medical schools and licensing bodies try to predict it based on some general measures such as critical thinking, personality, and emotional intelligence. This study aimed at providing a model to design the relationship between the constructs. Sixty-nine medical students participated in this study. A battery test devised that consist four parts: Clinical reasoning measures, personality NEO inventory, Bar-On EQ inventory, and California critical thinking questionnaire. All participants completed the tests. Correlation and multiple regression analysis consumed for data analysis. There is low to moderate correlations between clinical reasoning and other variables. Emotional intelligence is the only variable that contributes clinical reasoning construct (r=0.17-0.34) (R(2) chnage = 0.46, P Value = 0.000). Although, clinical reasoning can be considered as a kind of thinking, no significant correlation detected between it and other constructs. Emotional intelligence (and its subscales) is the only variable that can be used for clinical reasoning prediction.

A neural model of rule generation in inductive reasoning.

Science.gov (United States)

Rasmussen, Daniel; Eliasmith, Chris

2011-01-01

Inductive reasoning is a fundamental and complex aspect of human intelligence. In particular, how do subjects, given a set of particular examples, generate general descriptions of the rules governing that set? We present a biologically plausible method for accomplishing this task and implement it in a spiking neuron model. We demonstrate the success of this model by applying it to the problem domain of Raven's Progressive Matrices, a widely used tool in the field of intelligence testing. The model is able to generate the rules necessary to correctly solve Raven's items, as well as recreate many of the experimental effects observed in human subjects. Copyright © 2011 Cognitive Science Society, Inc.

Reasoning robots the art and science of programming robotic agents

CERN Document Server

Thielscher, Michael

2005-01-01

The book provides an in-depth and uniform treatment of a mathematical model for reasoning robotic agents. The book also contains an introduction to a programming method and system based on this model. The mathematical model, known as the "Fluent Calculus,'' describes how to use classical first-order logic to set up symbolic models of dynamic worlds and to represent knowledge of actions and their effects. Robotic agents use this knowledge and their reasoning facilities to make decisions when following high-level, long-term strategies. The book covers the issues of reasoning about sensor input, acting under incomplete knowledge and uncertainty, planning, intelligent troubleshooting, and many other topics. The mathematical model is supplemented by a programming method which allows readers to design their own reasoning robotic agents. The usage of this method, called "FLUX,'' is illustrated by many example programs. The book includes the details of an implementation of FLUX using the standard programming language...

Diagnostic causal reasoning with verbal information.

Science.gov (United States)

Meder, Björn; Mayrhofer, Ralf

2017-08-01

In diagnostic causal reasoning, the goal is to infer the probability of causes from one or multiple observed effects. Typically, studies investigating such tasks provide subjects with precise quantitative information regarding the strength of the relations between causes and effects or sample data from which the relevant quantities can be learned. By contrast, we sought to examine people's inferences when causal information is communicated through qualitative, rather vague verbal expressions (e.g., "X occasionally causes A"). We conducted three experiments using a sequential diagnostic inference task, where multiple pieces of evidence were obtained one after the other. Quantitative predictions of different probabilistic models were derived using the numerical equivalents of the verbal terms, taken from an unrelated study with different subjects. We present a novel Bayesian model that allows for incorporating the temporal weighting of information in sequential diagnostic reasoning, which can be used to model both primacy and recency effects. On the basis of 19,848 judgments from 292 subjects, we found a remarkably close correspondence between the diagnostic inferences made by subjects who received only verbal information and those of a matched control group to whom information was presented numerically. Whether information was conveyed through verbal terms or numerical estimates, diagnostic judgments closely resembled the posterior probabilities entailed by the causes' prior probabilities and the effects' likelihoods. We observed interindividual differences regarding the temporal weighting of evidence in sequential diagnostic reasoning. Our work provides pathways for investigating judgment and decision making with verbal information within a computational modeling framework. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

Causal reasoning and models of cognitive tasks for naval nuclear power plant operators; Raisonnement causal et modelisation de l`activite cognitive d`operateurs de chaufferie nucleaire navale

Energy Technology Data Exchange (ETDEWEB)

Salazar-Ferrer, P

1995-06-01

In complex industrial process control, causal reasoning appears as a major component in operators` cognitive tasks. It is tightly linked to diagnosis, prediction of normal and failure states, and explanation. This work provides a detailed review of literature in causal reasoning. A synthesis is proposed as a model of causal reasoning in process control. This model integrates distinct approaches in Cognitive Science: especially qualitative physics, Bayesian networks, knowledge-based systems, and cognitive psychology. Our model defines a framework for the analysis of causal human errors in simulated naval nuclear power plant fault management. Through the methodological framework of critical incident analysis we define a classification of errors and difficulties linked to causal reasoning. This classification is based on shallow characteristics of causal reasoning. As an origin of these errors, more elementary component activities in causal reasoning are identified. The applications cover the field of functional specification for man-machine interfaces, operators support systems design as well as nuclear safety. In addition of this study, we integrate the model of causal reasoning in a model of cognitive task in process control. (authors). 106 refs., 49 figs., 8 tabs.

Semantic Interaction for Sensemaking: Inferring Analytical Reasoning for Model Steering.

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Endert, A; Fiaux, P; North, C

2012-12-01

Visual analytic tools aim to support the cognitively demanding task of sensemaking. Their success often depends on the ability to leverage capabilities of mathematical models, visualization, and human intuition through flexible, usable, and expressive interactions. Spatially clustering data is one effective metaphor for users to explore similarity and relationships between information, adjusting the weighting of dimensions or characteristics of the dataset to observe the change in the spatial layout. Semantic interaction is an approach to user interaction in such spatializations that couples these parametric modifications of the clustering model with users' analytic operations on the data (e.g., direct document movement in the spatialization, highlighting text, search, etc.). In this paper, we present results of a user study exploring the ability of semantic interaction in a visual analytic prototype, ForceSPIRE, to support sensemaking. We found that semantic interaction captures the analytical reasoning of the user through keyword weighting, and aids the user in co-creating a spatialization based on the user's reasoning and intuition.

Modeling the Effects of Argument Length and Validity on Inductive and Deductive Reasoning

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Rotello, Caren M.; Heit, Evan

2009-01-01

In an effort to assess models of inductive reasoning and deductive reasoning, the authors, in 3 experiments, examined the effects of argument length and logical validity on evaluation of arguments. In Experiments 1a and 1b, participants were given either induction or deduction instructions for a common set of stimuli. Two distinct effects were…

Stereotypical Reasoning: Logical Properties

OpenAIRE

Lehmann, Daniel

2002-01-01

Stereotypical reasoning assumes that the situation at hand is one of a kind and that it enjoys the properties generally associated with that kind of situation. It is one of the most basic forms of nonmonotonic reasoning. A formal model for stereotypical reasoning is proposed and the logical properties of this form of reasoning are studied. Stereotypical reasoning is shown to be cumulative under weak assumptions.

The enhancement of mathematical analogical reasoning ability of university students through concept attainment model

Science.gov (United States)

Angraini, L. M.; Kusumah, Y. S.; Dahlan, J. A.

2018-05-01

This study aims to see the enhancement of mathematical analogical reasoning ability of the university students through concept attainment model learning based on overall and Prior Mathematical Knowledge (PMK) and interaction of both. Quasi experiments with the design of this experimental-controlled equivalent group involved 54 of second semester students at the one of State Islamic University. The instrument used is pretest-postest. Kolmogorov-Smirnov test, Levene test, t test, two-way ANOVA test were used to analyse the data. The result of this study includes: (1) The enhancement of the mathematical analogical reasoning ability of the students who gets the learning of concept attainment model is better than the enhancement of the mathematical analogical reasoning ability of the students who gets the conventional learning as a whole and based on PMK; (2) There is no interaction between the learning that is used and PMK on enhancing mathematical analogical reasoning ability.

Belief–logic conflict resolution in syllogistic reasoning: Inspection-time evidence for a parallel process model

OpenAIRE

Stupple, Edward J.N; Ball, Linden

2008-01-01

An experiment is reported examining dual-process models of belief bias in syllogistic reasoning using a problem complexity manipulation and an inspection-time method to monitor processing latencies for premises and conclusions. Endorsement rates indicated increased belief bias on complex problems, a finding that runs counter to the “belief-first” selective scrutiny model, but which is consistent with other theories, including “reasoning-first” and “parallel-process” models. Inspection-time da...

Improving Students’ Scientific Reasoning and Problem-Solving Skills by The 5E Learning Model

Directory of Open Access Journals (Sweden)

Sri Mulyani Endang Susilowati

2017-12-01

Full Text Available Biology learning in MA (Madrasah Aliyah Khas Kempek was still dominated by teacher with low students’ involvement. This study would analyze the effectiveness of the 5E (Engagement, Exploration, Explanation, Elaboration, Evaluation learning model in improving scientific knowledge and problems solving. It also explained the relationship between students’ scientific reasoning with their problem-solving abilities. This was a pre-experimental research with one group pre-test post-test. Sixty students of MA Khas Kempek from XI MIA 3 and XI MIA 4 involved in this study. The learning outcome of the students was collected by the test of reasoning and problem-solving. The results showed that the rises of students’ scientific reasoning ability were 69.77% for XI MIA 3 and 66.27% for XI MIA 4, in the medium category. The problem-solving skills were 63.40% for XI MIA 3, 61.67% for XI MIA 4, and classified in the moderate category. The simple regression test found a linear correlation between students’ scientific reasoning and problem-solving ability. This study affirms that reasoning ability is needed in problem-solving. It is found that application of 5E learning model was effective to improve scientific reasoning and problem-solving ability of students.

Measurement Models for Reasoned Action Theory

OpenAIRE

Hennessy, Michael; Bleakley, Amy; Fishbein, Martin

2012-01-01

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 ...

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

The reasoned/reactive model: A new approach to examining eating decisions among female college dieters and nondieters.

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Ruhl, Holly; Holub, Shayla C; Dolan, Elaine A

2016-12-01

Female college students are prone to unhealthy eating patterns that can impact long-term health. This study examined female students' healthy and unhealthy eating behaviors with three decision-making models. Specifically, the theory of reasoned action, prototype/willingness model, and new reasoned/reactive model were compared to determine how reasoned (logical) and reactive (impulsive) factors relate to dietary decisions. Females (N=583, M age =20.89years) completed measures on reasoned cognitions about foods (attitudes, subjective norms, nutrition knowledge, intentions to eat foods), reactive cognitions about foods (prototypes, affect, willingness to eat foods), dieting, and food consumption. Structural equation modeling (SEM) revealed the new reasoned/reactive model to be the preeminent model for examining eating behaviors. This model showed that attitudes were related to intentions and willingness to eat healthy and unhealthy foods. Affect was related to willingness to eat healthy and unhealthy foods, whereas nutrition knowledge was related to intentions and willingness to eat healthy foods only. Intentions and willingness were related to healthy and unhealthy food consumption. Dieting status played a moderating role in the model and revealed mean-level differences between dieters and nondieters. This study highlights the importance of specific factors in relation to female students' eating decisions and unveils a comprehensive model for examining health behaviors. Copyright © 2016 Elsevier Ltd. All rights reserved.

Promoting the self-regulation of clinical reasoning skills in nursing students.

Science.gov (United States)

Kuiper, R; Pesut, D; Kautz, D

2009-10-02

The purpose of this paper is to describe the research surrounding the theories and models the authors united to describe the essential components of clinical reasoning in nursing practice education. The research was conducted with nursing students in health care settings through the application of teaching and learning strategies with the Self-Regulated Learning Model (SRL) and the Outcome-Present-State-Test (OPT) Model of Reflective Clinical Reasoning. Standardized nursing languages provided the content and clinical vocabulary for the clinical reasoning task. This descriptive study described the application of the OPT model of clinical reasoning, use of nursing language content, and reflective journals based on the SRL model with 66 undergraduate nursing students over an 8 month period of time. The study tested the idea that self-regulation of clinical reasoning skills can be developed using self-regulation theory and the OPT model. This research supports a framework for effective teaching and learning methods to promote and document learner progress in mastering clinical reasoning skills. Self-regulated Learning strategies coupled with the OPT model suggest benefits of self-observation and self-monitoring during clinical reasoning activities, and pinpoints where guidance is needed for the development of cognitive and metacognitive awareness. Thinking and reasoning about the complexities of patient care needs requires attention to the content, processes and outcomes that make a nursing care difference. These principles and concepts are valuable to clinical decision making for nurses globally as they deal with local, regional, national and international health care issues.

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.

Probabilistic representation in syllogistic reasoning: A theory to integrate mental models and heuristics.

Science.gov (United States)

Hattori, Masasi

2016-12-01

This paper presents a new theory of syllogistic reasoning. The proposed model assumes there are probabilistic representations of given signature situations. Instead of conducting an exhaustive search, the model constructs an individual-based "logical" mental representation that expresses the most probable state of affairs, and derives a necessary conclusion that is not inconsistent with the model using heuristics based on informativeness. The model is a unification of previous influential models. Its descriptive validity has been evaluated against existing empirical data and two new experiments, and by qualitative analyses based on previous empirical findings, all of which supported the theory. The model's behavior is also consistent with findings in other areas, including working memory capacity. The results indicate that people assume the probabilities of all target events mentioned in a syllogism to be almost equal, which suggests links between syllogistic reasoning and other areas of cognition. Copyright © 2016 The Author(s). Published by Elsevier B.V. All rights reserved.

Therapeutic reasoning: from hiatus to hypothetical model

NARCIS (Netherlands)

Bissessur, S.; Geijteman, E.C.T.; Al-Dulaimy, M.; Teunissen, P.W.; Richir, M.C.; Arnold, A.E.R.; Vries, de T.P.G.M.

2009-01-01

Rationale Extensive research has been conducted on clinical reasoning to gain better understanding of this process. Clinical reasoning has been defined as the process of thinking critically about the diagnosis and patient management. However, most research has focused on the process of diagnostic

Predicting substance-abuse treatment providers' communication with clients about medication assisted treatment: a test of the theories of reasoned action and planned behavior.

Science.gov (United States)

Roberto, Anthony J; Shafer, Michael S; Marmo, Jennifer

2014-01-01

The purpose of this investigation is to determine if the theory of reasoned action (TRA) and theory of planned behavior (TPB) can retrospectively predict whether substance-abuse treatment providers encourage their clients to use medicated-assisted treatment (MAT) as part of their treatment plan. Two-hundred and ten substance-abuse treatment providers completed a survey measuring attitudes, subjective norms, perceived behavioral control, intentions, and behavior. Results indicate that substance-abuse treatment providers have very positive attitudes, neutral subjective norms, somewhat positive perceived behavioral control, somewhat positive intentions toward recommending MAT as part of their clients' treatment plan, and were somewhat likely to engage in the actual behavior. Further, the data fit both the TRA and TPB, but with the TPB model having better fit and predictive power for this target audience and behavior. The theoretical and practical implications for the developing messages for substance-abuse treatment providers and other health-care professionals who provide treatment to patients with substance use disorders are discussed. Copyright © 2014 Elsevier Inc. All rights reserved.

Reasoning about Grover's Quantum Search Algorithm using Probabilistic wp

NARCIS (Netherlands)

Butler, M.J.; Hartel, Pieter H.

Grover's search algorithm is designed to be executed on a quantum mechanical computer. In this paper, the probabilistic wp-calculus is used to model and reason about Grover's algorithm. It is demonstrated that the calculus provides a rigorous programming notation for modelling this and other quantum

Reasoning with Previous Decisions: Beyond the Doctrine of Precedent

DEFF Research Database (Denmark)

Komárek, Jan

2013-01-01

in different jurisdictions use previous judicial decisions in their argument, we need to move beyond the concept of precedent to a wider notion, which would embrace practices and theories in legal systems outside the Common law tradition. This article presents the concept of ‘reasoning with previous decisions...... law method’, but they are no less rational and intellectually sophisticated. The reason for the rather conceited attitude of some comparatists is in the dominance of the common law paradigm of precedent and the accompanying ‘case law method’. If we want to understand how courts and lawyers......’ as such an alternative and develops its basic models. The article first points out several shortcomings inherent in limiting the inquiry into reasoning with previous decisions by the common law paradigm (1). On the basis of numerous examples provided in section (1), I will present two basic models of reasoning...

Towards a structured approach to building qualitative reasoning models and simulations

NARCIS (Netherlands)

Bredeweg, B.; Salles, P.; Bouwer, A.; Liem, J.; Nuttle, T.; Cioca, E.; Nakova, E.; Noble, R.; Caldas, A.L.R.; Uzunov, Y.; Varadinova, E.; Zitek, A.

2008-01-01

Successful transfer and uptake of qualitative reasoning technology for modelling and simulation in a variety of domains has been hampered by the lack of a structured methodology to support formalisation of ideas. We present a framework that structures and supports the capture of conceptual knowledge

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

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

What every teacher needs to know about clinical reasoning.

Science.gov (United States)

Eva, Kevin W

2005-01-01

One of the core tasks assigned to clinical teachers is to enable students to sort through a cluster of features presented by a patient and accurately assign a diagnostic label, with the development of an appropriate treatment strategy being the end goal. Over the last 30 years there has been considerable debate within the health sciences education literature regarding the model that best describes how expert clinicians generate diagnostic decisions. The purpose of this essay is to provide a review of the research literature on clinical reasoning for frontline clinical teachers. The strengths and weaknesses of different approaches to clinical reasoning will be examined using one of the core divides between various models (that of analytic (i.e. conscious/controlled) versus non-analytic (i.e. unconscious/automatic) reasoning strategies) as an orienting framework. Recent work suggests that clinical teachers should stress the importance of both forms of reasoning, thereby enabling students to marshal reasoning processes in a flexible and context-specific manner. Specific implications are drawn from this overview for clinical teachers.

The Effectiveness of MURDER Cooperative Model towards Students' Mathematics Reasoning Ability and Self Concept of Ten Grade

Directory of Open Access Journals (Sweden)

Sofan Tri Prasetiyo

2017-08-01

Full Text Available The purpose of this research was to know the effectiveness of MURDER cooperative model towards students’ mathematics reasoning ability and self concept of ten grade. Population of this research were students of MIA ten grade Senior High School 1 Kebumen in the academic year 2016/1017. Sampling technique using simple random sampling technique. The data collected by the method of documentation, test methods, observation methods, and questionnaire methods. The analyzed of data are used completeness test and average different test. The results showed that: (1 mathematics reasoning ability of students that following MURDER cooperative model have completed individual and classical study completeness; (2 mathematics reasoning ability of students that following MURDER cooperative model better than mathematics reasoning ability of students that following ekspository learning; (3 self concept of students that following MURDER cooperative model better than self concept of students that following ekspository learning.

Irrelevance Reasoning in Knowledge Based Systems

Science.gov (United States)

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.

"Model-Based Reasoning is Not a Simple Thing": Investigating Enactment of Modeling in Five High School Biology Classrooms

Science.gov (United States)

Gaytan, Candice Renee

Modeling is an important scientific practice through which scientists generate, evaluate, and revise scientific knowledge, and it can be translated into science classrooms as a means for engaging students in authentic scientific practice. Much of the research investigating modeling in classrooms focuses on student learning, leaving a gap in understanding how teachers enact this important practice. This dissertation draws on data collected through a model-based curricular project to uncover instructional moves teachers made to enact modeling, to describe factors influencing enactment, and to discuss a framework for designing and enacting modeling lessons. I framed my analysis and interpretation of data within the varying perceptions of modeling found in the science studies and science education literature. Largely, modeling is described to varying degrees as a means to engage students in sense-making or as a means to deliver content to students. This frame revealed how the instructional moves teachers used to enact modeling may have influenced its portrayal as a reasoning practice. I found that teachers' responses to their students' ideas or questions may have important consequences for students' engagement in modeling, and thus, sense-making. To investigate factors influencing the portrayal of modeling, I analyzed teacher interviews and writings for what they perceived affected instruction. My findings illustrate alignments and misalignments between what teachers perceive modeling to be and what they do through instruction. In particular, teachers valued providing their students with time to collaborate and to share their ideas, but when time was perceived as a constraint, instruction shifted towards delivering content. Additionally, teachers' perceptions of students' capacity to engage in modeling is also related to if and how they provided opportunities for students to make sense of phenomena. The dissertation closes with a discussion of a framework for designing

AORTA: Adding Organizational Reasoning to Agents

DEFF Research Database (Denmark)

Jensen, Andreas Schmidt; Dignum, Virginia

2014-01-01

the expected behavior of the agents. Agents need to be able to reason about the regulations, so that they can act within the expected boundaries and work towards the objectives of the organization. This extended abstract introduces AORTA, a component that can be integrated into agents’ reasoning mechanism......, allowing them to reason about (and act upon) regulations specified by an organizational model using simple reasoning rules. The added value is that the organizational model is independent of that of the agents, and that the approach is not tied to a specific organizational model....

Information Uncertainty to Compare Qualitative Reasoning Security Risk Assessment Results

Energy Technology Data Exchange (ETDEWEB)

Chavez, Gregory M [Los Alamos National Laboratory; Key, Brian P [Los Alamos National Laboratory; Zerkle, David K [Los Alamos National Laboratory; Shevitz, Daniel W [Los Alamos National Laboratory

2009-01-01

The security risk associated with malevolent acts such as those of terrorism are often void of the historical data required for a traditional PRA. Most information available to conduct security risk assessments for these malevolent acts is obtained from subject matter experts as subjective judgements. Qualitative reasoning approaches such as approximate reasoning and evidential reasoning are useful for modeling the predicted risk from information provided by subject matter experts. Absent from these approaches is a consistent means to compare the security risk assessment results. Associated with each predicted risk reasoning result is a quantifiable amount of information uncertainty which can be measured and used to compare the results. This paper explores using entropy measures to quantify the information uncertainty associated with conflict and non-specificity in the predicted reasoning results. The measured quantities of conflict and non-specificity can ultimately be used to compare qualitative reasoning results which are important in triage studies and ultimately resource allocation. Straight forward extensions of previous entropy measures are presented here to quantify the non-specificity and conflict associated with security risk assessment results obtained from qualitative reasoning models.

Geometric Modeling and Reasoning of Human-Centered Freeform Products

CERN Document Server

Wang, Charlie C L

2013-01-01

The recent trend in user-customized product design requires the shape of products to be automatically adjusted according to the human body’s shape, so that people will feel more comfortable when wearing these products.  Geometric approaches can be used to design the freeform shape of products worn by people, which can greatly improve the efficiency of design processes in various industries involving customized products (e.g., garment design, toy design, jewel design, shoe design, and design of medical devices, etc.). These products are usually composed of very complex geometric shapes (represented by free-form surfaces), and are not driven by a parameter table but a digital human model with free-form shapes or part of human bodies (e.g., wrist, foot, and head models).   Geometric Modeling and Reasoning of Human-Centered Freeform Products introduces the algorithms of human body reconstruction, freeform product modeling, constraining and reconstructing freeform products, and shape optimization for improving...

A set for relational reasoning: Facilitation of algebraic modeling by a fraction task.

Science.gov (United States)

DeWolf, Melissa; Bassok, Miriam; Holyoak, Keith J

2016-12-01

Recent work has identified correlations between early mastery of fractions and later math achievement, especially in algebra. However, causal connections between aspects of reasoning with fractions and improved algebra performance have yet to be established. The current study investigated whether relational reasoning with fractions facilitates subsequent algebraic reasoning using both pre-algebra students and adult college students. Participants were first given either a relational reasoning fractions task or a fraction algebra procedures control task. Then, all participants solved word problems and constructed algebraic equations in either multiplication or division format. The word problems and the equation construction tasks involved simple multiplicative comparison statements such as "There are 4 times as many students as teachers in a classroom." Performance on the algebraic equation construction task was enhanced for participants who had previously completed the relational fractions task compared with those who completed the fraction algebra procedures task. This finding suggests that relational reasoning with fractions can establish a relational set that promotes students' tendency to model relations using algebraic expressions. Copyright © 2016 Elsevier Inc. All rights reserved.

A neurocomputational model of analogical reasoning and its breakdown in frontotemporal lobar degeneration.

Science.gov (United States)

Morrison, Robert G; Krawczyk, Daniel C; Holyoak, Keith J; Hummel, John E; Chow, Tiffany W; Miller, Bruce L; Knowlton, Barbara J

2004-03-01

Analogy is important for learning and discovery and is considered a core component of intelligence. We present a computational account of analogical reasoning that is compatible with data we have collected from patients with cortical degeneration of either their frontal or anterior temporal cortices due to frontotemporal lobar degeneration (FTLD). These two patient groups showed different deficits in picture and verbal analogies: frontal lobe FTLD patients tended to make errors due to impairments in working memory and inhibitory abilities, whereas temporal lobe FTLD patients tended to make errors due to semantic memory loss. Using the "Learning and Inference with Schemas and Analogies" model, we provide a specific account of how such deficits may arise within neural networks supporting analogical problem solving.

Health belief model and reasoned action theory in predicting water saving behaviors in yazd, iran.

Science.gov (United States)

Morowatisharifabad, Mohammad Ali; Momayyezi, Mahdieh; Ghaneian, Mohammad Taghi

2012-01-01

People's behaviors and intentions about healthy behaviors depend on their beliefs, values, and knowledge about the issue. Various models of health education are used in deter¬mining predictors of different healthy behaviors but their efficacy in cultural behaviors, such as water saving behaviors, are not studied. The study was conducted to explain water saving beha¬viors in Yazd, Iran on the basis of Health Belief Model and Reasoned Action Theory. The cross-sectional study used random cluster sampling to recruit 200 heads of households to collect the data. The survey questionnaire was tested for its content validity and reliability. Analysis of data included descriptive statistics, simple correlation, hierarchical multiple regression. Simple correlations between water saving behaviors and Reasoned Action Theory and Health Belief Model constructs were statistically significant. Health Belief Model and Reasoned Action Theory constructs explained 20.80% and 8.40% of the variances in water saving beha-viors, respectively. Perceived barriers were the strongest Predictor. Additionally, there was a sta¬tistically positive correlation between water saving behaviors and intention. In designing interventions aimed at water waste prevention, barriers of water saving behaviors should be addressed first, followed by people's attitude towards water saving. Health Belief Model constructs, with the exception of perceived severity and benefits, is more powerful than is Reasoned Action Theory in predicting water saving behavior and may be used as a framework for educational interventions aimed at improving water saving behaviors.

Health Belief Model and Reasoned Action Theory in Predicting Water Saving Behaviors in Yazd, Iran

Directory of Open Access Journals (Sweden)

Mohammad Taghi Ghaneian

2012-12-01

Full Text Available Background: People's behaviors and intentions about healthy behaviors depend on their beliefs, values, and knowledge about the issue. Various models of health education are used in deter-mining predictors of different healthy behaviors but their efficacy in cultural behaviors, such as water saving behaviors, are not studied. The study was conducted to explain water saving beha-viors in Yazd, Iran on the basis of Health Belief Model and Reasoned Action Theory. Methods: The cross-sectional study used random cluster sampling to recruit 200 heads of households to collect the data. The survey questionnaire was tested for its content validity and reliability. Analysis of data included descriptive statistics, simple correlation, hierarchical multiple regression. Results: Simple correlations between water saving behaviors and Reasoned Action Theory and Health Belief Model constructs were statistically significant. Health Belief Model and Reasoned Action Theory constructs explained 20.80% and 8.40% of the variances in water saving beha-viors, respectively. Perceived barriers were the strongest Predictor. Additionally, there was a sta-tistically positive correlation between water saving behaviors and intention. Conclusion: In designing interventions aimed at water waste prevention, barriers of water saving behaviors should be addressed first, followed by people's attitude towards water saving. Health Belief Model constructs, with the exception of perceived severity and benefits, is more powerful than is Reasoned Action Theory in predicting water saving behavior and may be used as a framework for educational interventions aimed at improving water saving behaviors.

Effect of the Implicit Combinatorial Model on Combinatorial Reasoning in Secondary School Pupils.

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Batanero, Carmen; And Others

1997-01-01

Elementary combinatorial problems may be classified into three different combinatorial models: (1) selection; (2) partition; and (3) distribution. The main goal of this research was to determine the effect of the implicit combinatorial model on pupils' combinatorial reasoning before and after instruction. Gives an analysis of variance of the…

Enriching the hierarchical model of achievement motivation: autonomous and controlling reasons underlying achievement goals.

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Michou, Aikaterini; Vansteenkiste, Maarten; Mouratidis, Athanasios; Lens, Willy

2014-12-01

The hierarchical model of achievement motivation presumes that achievement goals channel the achievement motives of need for achievement and fear of failure towards motivational outcomes. Yet, less is known whether autonomous and controlling reasons underlying the pursuit of achievement goals can serve as additional pathways between achievement motives and outcomes. We tested whether mastery approach, performance approach, and performance avoidance goals and their underlying autonomous and controlling reasons would jointly explain the relation between achievement motives (i.e., fear of failure and need for achievement) and learning strategies (Study 1). Additionally, we examined whether the autonomous and controlling reasons underlying learners' dominant achievement goal would account for the link between achievement motives and the educational outcomes of learning strategies and cheating (Study 2). Six hundred and six Greek adolescent students (Mage = 15.05, SD = 1.43) and 435 university students (Mage M = 20.51, SD = 2.80) participated in studies 1 and 2, respectively. In both studies, a correlational design was used and the hypotheses were tested via path modelling. Autonomous and controlling reasons underlying the pursuit of achievement goals mediated, respectively, the relation of need for achievement and fear of failure to aspects of learning outcomes. Autonomous and controlling reasons underlying achievement goals could further explain learners' functioning in achievement settings. © 2014 The British Psychological Society.

Explanatory item response modelling of an abstract reasoning assessment: A case for modern test design

OpenAIRE

Helland, Fredrik

2016-01-01

Assessment is an integral part of society and education, and for this reason it is important to know what you measure. This thesis is about explanatory item response modelling of an abstract reasoning assessment, with the objective to create a modern test design framework for automatic generation of valid and precalibrated items of abstract reasoning. Modern test design aims to strengthen the connections between the different components of a test, with a stress on strong theory, systematic it...

Intelligent tutoring system for clinical reasoning skill acquisition in dental students.

Science.gov (United States)

Suebnukarn, Siriwan

2009-10-01

Learning clinical reasoning is an important core activity of the modern dental curriculum. This article describes an intelligent tutoring system (ITS) for clinical reasoning skill acquisition. The system is designed to provide an experience that emulates that of live human-tutored problem-based learning (PBL) sessions as much as possible, while at the same time permitting the students to participate collaboratively from disparate locations. The system uses Bayesian networks to model individual student knowledge and activity, as well as that of the group. Tutoring algorithms use the models to generate tutoring hints. The system incorporates a multimodal interface that integrates text and graphics so as to provide a rich communication channel between the students and the system, as well as among students in the group. Comparison of learning outcomes shows that student clinical reasoning gains from the ITS are similar to those obtained from human-tutored sessions.

Substance Use Among Adolescents with Attention-Deficit/Hyperactivity Disorder: Reasons for Use, Knowledge of Risks, and Provider Messaging/Education.

Science.gov (United States)

Harstad, Elizabeth; Wisk, Lauren E; Ziemnik, Rosemary; Huang, Qian; Salimian, Parissa; Weitzman, Elissa R; Levy, Sharon

Adolescents with attention-deficit/hyperactivity disorder (ADHD) are at increased risk for alcohol and marijuana use. This study's objective is to describe adolescents' ADHD-specific reasons for marijuana use, knowledge of ADHD-specific alcohol risks, and reported subspecialty provider messaging/education regarding alcohol use among adolescents with ADHD. Youths with ADHD aged 12 to 18 years completed a survey about alcohol and marijuana use, ADHD-specific reasons for marijuana use, knowledge of ADHD-specific alcohol risks, and reported provider messaging/education regarding alcohol use. We assessed knowledge toward substance use using descriptive statistics. We used χ and t tests to determine whether knowledge or provider messaging/education differed by sociodemographic characteristics. Of the 96 participants, 61.5% were male, average age was 15.7 years; 31.3% reported past-year alcohol use and 20.8% reported past-year marijuana use. The majority (65.2%) said "no/don't know" to both "Can alcohol make ADHD symptoms worse?" and "Can alcohol interfere or get in the way of the medications you take?" Older participants were more likely to correctly answer the medication question "yes." Despite most (74%) participants reporting that their provider asked about alcohol use, few youth reported that their providers gave specific messages/education that alcohol could make ADHD symptoms worse (9.4%) or interfere with ADHD medications (14.6%); older participants and past-year alcohol users were more likely to have received these alcohol-specific messages. Many youth with ADHD are unaware of the risks of alcohol use in relation to ADHD and providers are not consistently discussing these risks in the context of clinical ADHD care.

Low level radiation: how does the linear without threshold model provide the safety of Canadian

International Nuclear Information System (INIS)

Anon.

2010-01-01

The linear without threshold model is a model of risk used worldwide by the most of health organisms of nuclear regulation in order to establish dose limits for workers and public. It is in the heart of the approach adopted by the Canadian commission of nuclear safety (C.C.S.N.) in matter of radiation protection. The linear without threshold model presumes reasonably it exists a direct link between radiation exposure and cancer rate. It does not exist scientific evidence that chronicle exposure to radiation doses under 100 milli sievert (mSv) leads harmful effects on health. Several scientific reports highlighted scientific evidences that seem indicate a low level of radiation is less harmful than the linear without threshold predicts. As the linear without threshold model presumes that any radiation exposure brings risks, the ALARA principle obliges the licensees to get the radiation exposure at the lowest reasonably achievable level, social and economical factors taken into account. ALARA principle constitutes a basic principle in the C.C.S.N. approach in matter of radiation protection; On the radiation protection plan, C.C.S.N. gets a careful approach that allows to provide health and safety of Canadian people and the protection of their environment. (N.C.)

Causal Reasoning in Medicine: Analysis of a Protocol.

Science.gov (United States)

Kuipers, Benjamin; Kassirer, Jerome P.

1984-01-01

Describes the construction of a knowledge representation from the identification of the problem (nephrotic syndrome) to a running computer simulation of causal reasoning to provide a vertical slice of the construction of a cognitive model. Interactions between textbook knowledge, observations of human experts, and computational requirements are…

Fitting identity in the reasoned action framework: A meta-analysis and model comparison.

Science.gov (United States)

Paquin, Ryan S; Keating, David M

2017-01-01

Several competing models have been put forth regarding the role of identity in the reasoned action framework. The standard model proposes that identity is a background variable. Under a typical augmented model, identity is treated as an additional direct predictor of intention and behavior. Alternatively, it has been proposed that identity measures are inadvertent indicators of an underlying intention factor (e.g., a manifest-intention model). In order to test these competing hypotheses, we used data from 73 independent studies (total N = 23,917) to conduct a series of meta-analytic structural equation models. We also tested for moderation effects based on whether there was a match between identity constructs and the target behaviors examined (e.g., if the study examined a "smoker identity" and "smoking behavior," there would be a match; if the study examined a "health conscious identity" and "smoking behavior," there would not be a match). Average effects among primary reasoned action variables were all substantial, rs = .37-.69. Results gave evidence for the manifest-intention model over the other explanations, and a moderation effect by identity-behavior matching.

Theory-based Bayesian models of inductive learning and reasoning.

Science.gov (United States)

Tenenbaum, Joshua B; Griffiths, Thomas L; Kemp, Charles

2006-07-01

Inductive inference allows humans to make powerful generalizations from sparse data when learning about word meanings, unobserved properties, causal relationships, and many other aspects of the world. Traditional accounts of induction emphasize either the power of statistical learning, or the importance of strong constraints from structured domain knowledge, intuitive theories or schemas. We argue that both components are necessary to explain the nature, use and acquisition of human knowledge, and we introduce a theory-based Bayesian framework for modeling inductive learning and reasoning as statistical inferences over structured knowledge representations.

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.

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.

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.

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

A framework for providing telecommuting as a reasonable accommodation: some considerations on a comparative case study.

Science.gov (United States)

Kaplan, Shelley; Weiss, Sally; Moon, Nathan W; Baker, Paul

2006-01-01

Telecommuting, whether full time, part time, or over short periods when the need arises, can be an important accommodation for employees with disabilities. Indeed, telecommuting may be the only form of accommodation that offers employees whose disabilities fluctuate a means to stay consistently and gainfully employed. This article describes one employer's experience in considering a request for telecommuting as a reasonable accommodation for a particular employee. Drawing on real-life examples, both positive and negative, this article provides a win/win framework for decision-making that can help employers evaluate the use of telecommuting as a possible accommodation and facilitates open and ongoing communication between employer and employee.

Heuristic reasoning

CERN Document Server

2015-01-01

How can we advance knowledge? Which methods do we need in order to make new discoveries? How can we rationally evaluate, reconstruct and offer discoveries as a means of improving the ‘method’ of discovery itself? And how can we use findings about scientific discovery to boost funding policies, thus fostering a deeper impact of scientific discovery itself? The respective chapters in this book provide readers with answers to these questions. They focus on a set of issues that are essential to the development of types of reasoning for advancing knowledge, such as models for both revolutionary findings and paradigm shifts; ways of rationally addressing scientific disagreement, e.g. when a revolutionary discovery sparks considerable disagreement inside the scientific community; frameworks for both discovery and inference methods; and heuristics for economics and the social sciences.

The use of the bi-factor model to test the uni-dimensionality of a battery of reasoning tests.

Science.gov (United States)

Primi, Ricardo; Rocha da Silva, Marjorie Cristina; Rodrigues, Priscila; Muniz, Monalisa; Almeida, Leandro S

2013-02-01

The Battery of Reasoning Tests 5 (BPR-5) aims to assess the reasoning ability of individuals, using sub-tests with different formats and contents that require basic processes of inductive and deductive reasoning for their resolution. The BPR has three sequential forms: BPR-5i (for children from first to fifth grade), BPR-5 - Form A (for children from sixth to eighth grade) and BPR-5 - form B (for high school and undergraduate students). The present study analysed 412 questionnaires concerning BPR-5i, 603 questionnaires concerning BPR-5 - Form A and 1748 questionnaires concerning BPR-5 - Form B. The main goal was to test the uni-dimensionality of the battery and its tests in relation to items using the bi-factor model. Results suggest that the g factor loadings (extracted by the uni-dimensional model) do not change when the data is adjusted for a more flexible multi-factor model (bi-factor model). A general reasoning factor underlying different contents items is supported.

Using the theory of reasoned action to model retention in rural primary care physicians.

Science.gov (United States)

Feeley, Thomas Hugh

2003-01-01

Much research attention has focused on medical students', residents', and physicians' decisions to join a rural practice, but far fewer studies have examined retention of rural primary care physicians. The current review uses Fishbein and Ajzen's Theory of Reasoned Action (TRA) to organize the literature on the predictors and correlates of retention of rural practicing physicians. TRA suggests turnover behavior is directly predicted by one's turnover intentions, which are, in turn, predicted by one's attitudes about rural practice and perceptions of salient others' (eg, spouse's) attitudes about rural practice and rural living. Narrative literature review of scholarship in predicting and understanding predictors and correlates of rural physician retention. The TRA model provides a useful conceptual model to organize the literature on rural physician retention. Physicians' subjective norms regarding rural practice are an important source of influence in the decision to remain or leave one's position, and this relation should be more fully examined in future research.

The Balance-Scale Task Revisited: A Comparison of Statistical Models for Rule-Based and Information-Integration Theories of Proportional Reasoning.

Directory of Open Access Journals (Sweden)

Abe D Hofman

Full Text Available We propose and test three statistical models for the analysis of children's responses to the balance scale task, a seminal task to study proportional reasoning. We use a latent class modelling approach to formulate a rule-based latent class model (RB LCM following from a rule-based perspective on proportional reasoning and a new statistical model, the Weighted Sum Model, following from an information-integration approach. Moreover, a hybrid LCM using item covariates is proposed, combining aspects of both a rule-based and information-integration perspective. These models are applied to two different datasets, a standard paper-and-pencil test dataset (N = 779, and a dataset collected within an online learning environment that included direct feedback, time-pressure, and a reward system (N = 808. For the paper-and-pencil dataset the RB LCM resulted in the best fit, whereas for the online dataset the hybrid LCM provided the best fit. The standard paper-and-pencil dataset yielded more evidence for distinct solution rules than the online data set in which quantitative item characteristics are more prominent in determining responses. These results shed new light on the discussion on sequential rule-based and information-integration perspectives of cognitive development.

THE USAGE OF SOCIAL MEDIA FOR LEARNING AND TEACHING PURPOSES: AN IMPLEMENTATION OF EXTENDED THEORY OF REASONED ACTION MODEL

OpenAIRE

AKMAN, İbrahim; TURHAN, Çiğdem

2014-01-01

The growing popularity of the social networking siteshas presented new options for the development of learning and teachingenvironments to provide informal learning. In this study, the usage of socialnetworking sites for the purpose of learning and teaching has been analyzedusing the extended Theory of Reasoned Action (TRA) model. A survey has beenconducted to analyze the behavior in regard to the acceptance of social mediafor learning and teaching and the results were systematically analyzed...

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.

Exploring students' patterns of reasoning

Science.gov (United States)

Matloob Haghanikar, Mojgan

As part of a collaborative study of the science preparation of elementary school teachers, we investigated the quality of students' reasoning and explored the relationship between sophistication of reasoning and the degree to which the courses were considered inquiry oriented. To probe students' reasoning, we developed open-ended written content questions with the distinguishing feature of applying recently learned concepts in a new context. We devised a protocol for developing written content questions that provided a common structure for probing and classifying students' sophistication level of reasoning. In designing our protocol, we considered several distinct criteria, and classified students' responses based on their performance for each criterion. First, we classified concepts into three types: Descriptive, Hypothetical, and Theoretical and categorized the abstraction levels of the responses in terms of the types of concepts and the inter-relationship between the concepts. Second, we devised a rubric based on Bloom's revised taxonomy with seven traits (both knowledge types and cognitive processes) and a defined set of criteria to evaluate each trait. Along with analyzing students' reasoning, we visited universities and observed the courses in which the students were enrolled. We used the Reformed Teaching Observation Protocol (RTOP) to rank the courses with respect to characteristics that are valued for the inquiry courses. We conducted logistic regression for a sample of 18courses with about 900 students and reported the results for performing logistic regression to estimate the relationship between traits of reasoning and RTOP score. In addition, we analyzed conceptual structure of students' responses, based on conceptual classification schemes, and clustered students' responses into six categories. We derived regression model, to estimate the relationship between the sophistication of the categories of conceptual structure and RTOP scores. However, the

Epimenides: Interoperability Reasoning for Digital Preservation

NARCIS (Netherlands)

Kargakis, Yannis; Tzitzikas, Yannis; van Horik, M.P.M.

2014-01-01

This paper presents Epimenides, a system that implements a novel interoperability dependency reasoning approach for assisting digital preservation activities. A distinctive feature is that it can model also converters and emulators, and the adopted modelling approach enables the automatic reasoning

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.

A clinical reasoning model focused on clients' behaviour change with reference to physiotherapists: its multiphase development and validation.

Science.gov (United States)

Elvén, Maria; Hochwälder, Jacek; Dean, Elizabeth; Söderlund, Anne

2015-05-01

A biopsychosocial approach and behaviour change strategies have long been proposed to serve as a basis for addressing current multifaceted health problems. This emphasis has implications for clinical reasoning of health professionals. This study's aim was to develop and validate a conceptual model to guide physiotherapists' clinical reasoning focused on clients' behaviour change. Phase 1 consisted of the exploration of existing research and the research team's experiences and knowledge. Phases 2a and 2b consisted of validation and refinement of the model based on input from physiotherapy students in two focus groups (n = 5 per group) and from experts in behavioural medicine (n = 9). Phase 1 generated theoretical and evidence bases for the first version of a model. Phases 2a and 2b established the validity and value of the model. The final model described clinical reasoning focused on clients' behaviour change as a cognitive, reflective, collaborative and iterative process with multiple interrelated levels that included input from the client and physiotherapist, a functional behavioural analysis of the activity-related target behaviour and the selection of strategies for behaviour change. This unique model, theory- and evidence-informed, has been developed to help physiotherapists to apply clinical reasoning systematically in the process of behaviour change with their clients.

How many kinds of reasoning? Inference, probability, and natural language semantics.

Science.gov (United States)

Lassiter, Daniel; Goodman, Noah D

2015-03-01

The "new paradigm" unifying deductive and inductive reasoning in a Bayesian framework (Oaksford & Chater, 2007; Over, 2009) has been claimed to be falsified by results which show sharp differences between reasoning about necessity vs. plausibility (Heit & Rotello, 2010; Rips, 2001; Rotello & Heit, 2009). We provide a probabilistic model of reasoning with modal expressions such as "necessary" and "plausible" informed by recent work in formal semantics of natural language, and show that it predicts the possibility of non-linear response patterns which have been claimed to be problematic. Our model also makes a strong monotonicity prediction, while two-dimensional theories predict the possibility of reversals in argument strength depending on the modal word chosen. Predictions were tested using a novel experimental paradigm that replicates the previously-reported response patterns with a minimal manipulation, changing only one word of the stimulus between conditions. We found a spectrum of reasoning "modes" corresponding to different modal words, and strong support for our model's monotonicity prediction. This indicates that probabilistic approaches to reasoning can account in a clear and parsimonious way for data previously argued to falsify them, as well as new, more fine-grained, data. It also illustrates the importance of careful attention to the semantics of language employed in reasoning experiments. Copyright © 2014 Elsevier B.V. All rights reserved.

Probabilistic reasoning with graphical security models

NARCIS (Netherlands)

Kordy, Barbara; Pouly, Marc; Schweitzer, Patrick

This work provides a computational framework for meaningful probabilistic evaluation of attack–defense scenarios involving dependent actions. We combine the graphical security modeling technique of attack–defense trees with probabilistic information expressed in terms of Bayesian networks. In order

How, when, and for what reasons does land use modelling contribute to societal problem solving?

NARCIS (Netherlands)

Sterk, B.; Ittersum, van M.K.; Leeuwis, C.

2011-01-01

This paper reports and reflects on the contributions of land use models to societal problem solving. Its purpose is to inform model development and application and thus to increase chances for societal benefit of the modelling work. The key question is: How, when, and for what reasons does land use

Knowledge representation requirements for model sharing between model-based reasoning and simulation in process flow domains

Science.gov (United States)

Throop, David R.

1992-01-01

The paper examines the requirements for the reuse of computational models employed in model-based reasoning (MBR) to support automated inference about mechanisms. Areas in which the theory of MBR is not yet completely adequate for using the information that simulations can yield are identified, and recent work in these areas is reviewed. It is argued that using MBR along with simulations forces the use of specific fault models. Fault models are used so that a particular fault can be instantiated into the model and run. This in turn implies that the component specification language needs to be capable of encoding any fault that might need to be sensed or diagnosed. It also means that the simulation code must anticipate all these faults at the component level.

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.

Expert system for failures detection and non-monotonic reasoning

International Nuclear Information System (INIS)

Assis, Abilio de; Schirru, Roberto

1997-01-01

This paper presents the development of a shell denominated TIGER that has the purpose to serve as environment to the development of expert systems in diagnosis of faults in industrial complex plants. A model of knowledge representation and an inference engine based on non monotonic reasoning has been developed in order to provide flexibility in the representation of complex plants as well as performance to satisfy restrictions of real time. The TIGER is able to provide both the occurred fault and a hierarchical view of the several reasons that caused the fault to happen. As a validation of the developed shell a monitoring system of the critical safety functions of Angra-1 has been developed. 7 refs., 7 figs., 2 tabs

Teaching Complex Concepts in the Geosciences by Integrating Analytical Reasoning with GIS

Science.gov (United States)

Houser, Chris; Bishop, Michael P.; Lemmons, Kelly

2017-01-01

Conceptual models have long served as a means for physical geographers to organize their understanding of feedback mechanisms and complex systems. Analytical reasoning provides undergraduate students with an opportunity to develop conceptual models based upon their understanding of surface processes and environmental conditions. This study…

The Theory of Reasoned Action as Parallel Constraint Satisfaction: Towards a Dynamic Computational Model of Health Behavior

OpenAIRE

Orr, Mark G.; Thrush, Roxanne; Plaut, David C.

2013-01-01

The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence). To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA) using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constrain...

A Pro-Environmental Reasoned Action Model for Measuring Citizens’ Intentions regarding Ecolabel Product Usage

Directory of Open Access Journals (Sweden)

Reny Nadlifatin

2016-11-01

Full Text Available Ecolabel products are one approach towards environmental sustainability. Ecolabel programs have been socialized by governments all over the world to reduce environmental harm caused by the daily life cycles of the products that citizens use. The present study was aimed at measuring citizens’ behavior intention (BI regarding ecolabel product usage. An extended theory of reasoned action (TRA, namely that of pro-environmental reasoned action (PERA, is used as the predictor model. A total of 213 questionnaire data, collected from citizens of Indonesia, was analyzed using structural equation modeling. The analysis results show that the PERA model is able to describe 68% of citizens’ BI regarding ecolabel product usage. The analysis results also reveal that attitude is a key determinant factor. Several practical suggestions based on the results can be used as input for policy makers and company management to consider in their efforts to increase citizens’ BI to use ecolabel products.

Tactical Diagrammatic Reasoning

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Sven Linker

2017-01-01

Full Text Available Although automated reasoning with diagrams has been possible for some years, tools for diagrammatic reasoning are generally much less sophisticated than their sentential cousins. The tasks of exploring levels of automation and abstraction in the construction of proofs and of providing explanations of solutions expressed in the proofs remain to be addressed. In this paper we take an interactive proof assistant for Euler diagrams, Speedith, and add tactics to its reasoning engine, providing a level of automation in the construction of proofs. By adding tactics to Speedith's repertoire of inferences, we ease the interaction between the user and the system and capture a higher level explanation of the essence of the proof. We analysed the design options for tactics by using metrics which relate to human readability, such as the number of inferences and the amount of clutter present in diagrams. Thus, in contrast to the normal case with sentential tactics, our tactics are designed to not only prove the theorem, but also to support explanation.

A Semantic Reasoning Method Towards Ontological Model for Automated Learning Analysis

OpenAIRE

Okoye, Kingsley; Tawil, Abdel-Rahman; Naeem, Usman; Lamine, Elyes

2015-01-01

Semantic reasoning can help solve the problem of regulating the evolving and static measures of knowledge at theoretical and technological levels. The technique has been proven to enhance the capability of process models by making inferences, retaining and applying what they have learned as well as discovery of new processes. The work in this paper propose a semantic rule-based approach directed towards discovering learners interaction patterns within a learning knowledge base, and then respo...

Customer-Provider Strategic Alignment: A Maturity Model

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Luftman, Jerry; Brown, Carol V.; Balaji, S.

This chapter presents a new model for assessing the maturity of a ­customer-provider relationship from a collaborative service delivery perspective: the Customer-Provider Strategic Alignment Maturity (CPSAM) Model. This model builds on recent research for effectively managing the customer-provider relationship in IT service outsourcing contexts and a validated model for assessing alignment across internal IT service units and their business customers within the same organization. After reviewing relevant literature by service science and information systems researchers, the six overarching components of the maturity model are presented: value measurements, governance, partnership, communications, human resources and skills, and scope and architecture. A key assumption of the model is that all of the components need be addressed to assess and improve customer-provider alignment. Examples of specific metrics for measuring the maturity level of each component over the five levels of maturity are also presented.

Public policy, rationality and reason

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Rodolfo Canto Sáenz

2015-07-01

Full Text Available This work suggests the incorporation of practical reason in the design, implementation and evaluation of public policies, alongside instrumental rationality. It takes two proposals that today point in this direction: Rawls distinction between reasonable (practical reason and rational (instrumental reason and what this author calls the CI Procedure (categorical imperative procedure and Habermas model of deliberative democracy. The main conclusion is that the analysis of public policies can not be limited to rather narrow limits of science, but requires the contribution of political and moral philosophy.

Reasoning=working Memoryattention

Science.gov (United States)

Buehner, M.; Krumm, S.; Pick, M.

2005-01-01

The purpose of this study was to clarify the relationship between attention, components of working memory, and reasoning. Therefore, twenty working memory tests, two attention tests, and nine intelligence subtests were administered to 135 students. Using structural equation modeling, we were able to replicate a functional model of working memory…

GLOBAL PUBLIC PRIVATE PARTNERSHIP: AN ANALOGICAL REASONING MODEL

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Hyuk KIM

2015-06-01

Full Text Available This paper aims to introduce a new strategic direction for the multinational pharmaceutical companies in terms of the access to essential, life-saving medicines. The multinational pharmaceutical companies have been severely criticized by their various stakeholders because of their business models, particularly because of the stringent patent protection on the pharmaceutical products. The multinational pharmaceutical companies should find a new strategic direction to balance their R&D-intensive, expensive business with the access to essential, lifesaving medicines since favorable public relations are critical for the multinational pharmaceutical companies to maintain their profitable business. This paper adopts an Analogical Reasoning Model (ARM to propose a new strategic direction for the multinational pharmaceutical companies in an effort to balance their expensive business with the enhanced social responsibility. In essence, the ARM helps the multinational pharmaceutical companies formulate viable strategies that can realize a win-win situation not only for their stakeholders but also for the pharmaceutical companies themselves. The ARM is constructed, analyzing the food and beverage industry as a source environment, and suggests a comprehensive, industry-wide, multi-stakeholder public-private partnership, led not by the public sector but by the multinational pharmaceutical companies.

OWL Reasoning Framework over Big Biological Knowledge Network

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Chen, Huajun; Chen, Xi; Gu, Peiqin; Wu, Zhaohui; Yu, Tong

2014-01-01

Recently, huge amounts of data are generated in the domain of biology. Embedded with domain knowledge from different disciplines, the isolated biological resources are implicitly connected. Thus it has shaped a big network of versatile biological knowledge. Faced with such massive, disparate, and interlinked biological data, providing an efficient way to model, integrate, and analyze the big biological network becomes a challenge. In this paper, we present a general OWL (web ontology language) reasoning framework to study the implicit relationships among biological entities. A comprehensive biological ontology across traditional Chinese medicine (TCM) and western medicine (WM) is used to create a conceptual model for the biological network. Then corresponding biological data is integrated into a biological knowledge network as the data model. Based on the conceptual model and data model, a scalable OWL reasoning method is utilized to infer the potential associations between biological entities from the biological network. In our experiment, we focus on the association discovery between TCM and WM. The derived associations are quite useful for biologists to promote the development of novel drugs and TCM modernization. The experimental results show that the system achieves high efficiency, accuracy, scalability, and effectivity. PMID:24877076

Mangroves can provide protection against wind damage during storms

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Das, Saudamini; Crépin, Anne-Sophie

2013-12-01

Research has established that mangroves can protect lives and property from storms by buffering the impacts of storm surges. However, their effects in attenuating wind velocity and providing protection from wind damage during storms are not known. This study examined whether mangroves attenuate damage from cyclonic winds and found that they provide substantial protection to properties, even relatively far away from mangroves and the coast. We devised a theoretical model of wind protection by mangroves and calibrated and applied this model using data from the 1999 cyclone in the Odisha region of India. The model predicted and quantified the actual level of damage reasonably accurately and showed that mangroves reduced wind damage to houses. The wind protection value of mangroves in reducing house damage amounted to approximately US$177 per hectare at 1999 prices. This provides additional evidence of the storm protection ecosystem services that mangroves supply in the region and an additional reason to invest in mangrove ecosystems to provide better adaptability to coastal disasters such as storms.

Applications of Temporal Reasoning to Intensive Care Units

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J. M. Juarez

2010-01-01

Full Text Available Intensive Care Units (ICUs are hospital departments that focus on the evolution of patients. In this scenario, the temporal dimension plays an essential role in understanding the state of the patients from their temporal information. The development of methods for the acquisition, modelling, reasoning and knowledge discovery of temporal information is, therefore, useful to exploit the large amount of temporal data recorded daily in the ICU. During the past decades, some subfields of Artificial Intelligence have been devoted to the study of temporal models and techniques to solve generic problems and towards their practical applications in the medical domain. The main goal of this paper is to present our view of some aspects of practical problems of temporal reasoning in the ICU field, and to describe our practical experience in the field in the last decade. This paper provides a non-exhaustive review of some of the efforts made in the field and our particular contributions in the development of temporal reasoning methods to partially solve some of these problems. The results are a set of software tools that help physicians to better understand the patient's temporal evolution.

Adolescents' reasons for tanning and appearance motives: a preliminary study.

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Prior, Suzanne M; Fenwick, Kimberley D; Peterson, Jasmine C

2014-01-01

We examined adolescents' reasons for tanning and how these relate to appearance evaluation and orientation. Two hundred and sixty-four Canadian adolescents (age range 15-19 years) in grades 10, 11, and 12 completed a survey that included scales measuring their reasons for tanning, appearance evaluation, and appearance orientation. It was found that girls and boys differed on four of nine subscales measuring reasons for tanning. Girls believed more strongly than boys that tanning improved their general appearance and that friends influenced their decision to tan. Girls also expressed less concern than boys that tanning caused immediate skin damage or premature aging. The pattern of correlations between the reasons for tanning and appearance orientation was similar for girls and boys. For both, appearance reasons for tanning and sociocultural influences on tanning were positively associated with appearance orientation. Suggestions for future research with adolescents and a proposal for a guiding model are provided. Copyright © 2013 Elsevier Ltd. All rights reserved.

Intuitionistic Fuzzy Time Series Forecasting Model Based on Intuitionistic Fuzzy Reasoning

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Ya’nan Wang

2016-01-01

Full Text Available Fuzzy sets theory cannot describe the data comprehensively, which has greatly limited the objectivity of fuzzy time series in uncertain data forecasting. In this regard, an intuitionistic fuzzy time series forecasting model is built. In the new model, a fuzzy clustering algorithm is used to divide the universe of discourse into unequal intervals, and a more objective technique for ascertaining the membership function and nonmembership function of the intuitionistic fuzzy set is proposed. On these bases, forecast rules based on intuitionistic fuzzy approximate reasoning are established. At last, contrast experiments on the enrollments of the University of Alabama and the Taiwan Stock Exchange Capitalization Weighted Stock Index are carried out. The results show that the new model has a clear advantage of improving the forecast accuracy.

Teaching Quantitative Reasoning: A Better Context for Algebra

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Eric Gaze

2014-01-01

Full Text Available This editorial questions the preeminence of algebra in our mathematics curriculum. The GATC (Geometry, Algebra, Trigonometry, Calculus sequence abandons the fundamental middle school math topics necessary for quantitative literacy, while the standard super-abundance of algebra taught in the abstract fosters math phobia and supports a culturally acceptable stance that math is not relevant to everyday life. Although GATC is seen as a pipeline to STEM (Science, Technology, Engineering, Mathematics, it is a mistake to think that the objective of producing quantitatively literate citizens is at odds with creating more scientists and engineers. The goal must be to create a curriculum that addresses the quantitative reasoning needs of all students, providing meaningful engagement in mathematics that will simultaneously develop quantitative literacy and spark an interest in STEM fields. In my view, such a curriculum could be based on a foundation of proportional reasoning leading to higher-order quantitative reasoning via modeling (including algebraic reasoning and problem solving and statistical literacy (through the exploration and study of data.

A Model for Subjective Well-Being in Adolescence: Need Satisfaction and Reasons for Living

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Eryilmaz, Ali

2012-01-01

Subjective well-being is as important for adolescents as it is in other stages of life. This study thus aims to develop a model for subjective well-being, which is limited to need satisfaction in adolescence and reasons for living, and to test the validity of the model. Participants were a total of 227 individuals, 120 females and 107 males. Data…

Adversarial reasoning: challenges and approaches

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Kott, Alexander; Ownby, Michael

2005-05-01

This paper defines adversarial reasoning as computational approaches to inferring and anticipating an enemy's perceptions, intents and actions. It argues that adversarial reasoning transcends the boundaries of game theory and must also leverage such disciplines as cognitive modeling, control theory, AI planning and others. To illustrate the challenges of applying adversarial reasoning to real-world problems, the paper explores the lessons learned in the CADET -- a battle planning system that focuses on brigade-level ground operations and involves adversarial reasoning. From this example of current capabilities, the paper proceeds to describe RAID -- a DARPA program that aims to build capabilities in adversarial reasoning, and how such capabilities would address practical requirements in Defense and other application areas.

Transforming Undergraduate Education Through the use of Analytical Reasoning (TUETAR)

Science.gov (United States)

Bishop, M. P.; Houser, C.; Lemmons, K.

2015-12-01

Traditional learning limits the potential for self-discovery, and the use of data and knowledge to understand Earth system relationships, processes, feedback mechanisms and system coupling. It is extremely difficult for undergraduate students to analyze, synthesize, and integrate quantitative information related to complex systems, as many concepts may not be mathematically tractable or yet to be formalized. Conceptual models have long served as a means for Earth scientists to organize their understanding of Earth's dynamics, and have served as a basis for human analytical reasoning and landscape interpretation. Consequently, we evaluated the use of conceptual modeling, knowledge representation and analytical reasoning to provide undergraduate students with an opportunity to develop and test geocomputational conceptual models based upon their understanding of Earth science concepts. This study describes the use of geospatial technologies and fuzzy cognitive maps to predict desertification across the South-Texas Sandsheet in an upper-level geomorphology course. Students developed conceptual models based on their understanding of aeolian processes from lectures, and then compared and evaluated their modeling results against an expert conceptual model and spatial predictions, and the observed distribution of dune activity in 2010. Students perceived that the analytical reasoning approach was significantly better for understanding desertification compared to traditional lecture, and promoted reflective learning, working with data, teamwork, student interaction, innovation, and creative thinking. Student evaluations support the notion that the adoption of knowledge representation and analytical reasoning in the classroom has the potential to transform undergraduate education by enabling students to formalize and test their conceptual understanding of Earth science. A model for developing and utilizing this geospatial technology approach in Earth science is presented.

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

Supporting Students’ Reasoning About Multiplication of Fractions by Constructing an Array Model

Directory of Open Access Journals (Sweden)

Ronal Rifandi

2017-08-01

Full Text Available The aim of the research is to support students in constructing an array model as a bridge from their informal knowledge to the formal one in understanding the part-whole relation concept. The part-whole relation concept is important for students to reason about multiplication of fractions. Realistic Mathematics Education which is in Indonesia adapted as Pendidikan Matematika Realistik Indonesia (PMRI is used as an approach in designing a series of lessons. For this purpose, hypothetical learning trajectory (HLT became the base for conducting a teaching experiment and designing its learning materials.  The research was conducted in the fifth grade of SD Al Hikmah Surabaya, an elementary school in Indonesia, with five students as the participants. The collected data were qualitative data in the form of students’ written works and the transcript of video recording during the lesson. The data were analyzed retrospectively by confronting the conjecture of students’ thinking in the HLT with the fact in the teaching experiment. The result of the research shows that most students could use the contextual problem in promoting their ability on constructing their own array model to reason about part-whole relation.

Diagnostic reasoning: where we've been, where we're going.

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Monteiro, Sandra M; Norman, Geoffrey

2013-01-01

Recently, clinical diagnostic reasoning has been characterized by "dual processing" models, which postulate a fast, unconscious (System 1) component and a slow, logical, analytical (System 2) component. However, there are a number of variants of this basic model, which may lead to conflicting claims. This paper critically reviews current theories and evidence about the nature of clinical diagnostic reasoning. We begin by briefly discussing the history of research in clinical reasoning. We then focus more specifically on the evidence to support dual-processing models. We conclude by identifying knowledge gaps about clinical reasoning and provide suggestions for future research. In contrast to work on analytical and nonanalytical knowledge as a basis for reasoning, these theories focus on the thinking process, not the nature of the knowledge retrieved. Ironically, this appears to be a revival of an outdated concept. Rather than defining diagnostic performance by problem-solving skills, it is now being defined by processing strategy. The version of dual processing that has received most attention in the literature in medical diagnosis might be labeled a "default/interventionist" model,(17) which suggests that a default system of cognitive processes (System 1) is responsible for cognitive biases that lead to diagnostic errors and that System 2 intervenes to correct these errors. Consequently, from this model, the best strategy for reducing errors is to make students aware of the biases and to encourage them to rely more on System 2. However, an accumulation of evidence suggests that (a) strategies directed at increasing analytical (System 2) processing, by slowing down, reducing distractions, paying conscious attention, and (b) strategies directed at making students aware of the effect of cognitive biases, have no impact on error rates. Conversely, strategies based on increasing application of relevant knowledge appear to have some success and are consistent with basic

Bioethical reasoning and the orientation towards corporate social responsibility of business students

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Silvia López Paláu

2011-10-01

Full Text Available Ethical conflicts are ever more complex and require more interdisciplinary reflection to attain a solution. Bioethical reasoning can contribute to the understanding and eventual solution of many ethical conflicts in business. This study seeks to determine if a relationship exist among the social responsibility of business and the bioethical reasoning. A conceptual model using the multidimensional enterprise model proposed by Carroll (1979 and the bioethical principles proposed by Beauchamp and Childress (1979 is presented. A measurement instrument reliable for both constructs is developed. The results provide invaluable information that can help design new approaches for the ethical education of students.

Gating the holes in the Swiss cheese (part I): Expanding professor Reason's model for patient safety.

Science.gov (United States)

Seshia, Shashi S; Bryan Young, G; Makhinson, Michael; Smith, Preston A; Stobart, Kent; Croskerry, Pat

2018-02-01

Although patient safety has improved steadily, harm remains a substantial global challenge. Additionally, safety needs to be ensured not only in hospitals but also across the continuum of care. Better understanding of the complex cognitive factors influencing health care-related decisions and organizational cultures could lead to more rational approaches, and thereby to further improvement. A model integrating the concepts underlying Reason's Swiss cheese theory and the cognitive-affective biases plus cascade could advance the understanding of cognitive-affective processes that underlie decisions and organizational cultures across the continuum of care. Thematic analysis, qualitative information from several sources being used to support argumentation. Complex covert cognitive phenomena underlie decisions influencing health care. In the integrated model, the Swiss cheese slices represent dynamic cognitive-affective (mental) gates: Reason's successive layers of defence. Like firewalls and antivirus programs, cognitive-affective gates normally allow the passage of rational decisions but block or counter unsounds ones. Gates can be breached (ie, holes created) at one or more levels of organizations, teams, and individuals, by (1) any element of cognitive-affective biases plus (conflicts of interest and cognitive biases being the best studied) and (2) other potential error-provoking factors. Conversely, flawed decisions can be blocked and consequences minimized; for example, by addressing cognitive biases plus and error-provoking factors, and being constantly mindful. Informed shared decision making is a neglected but critical layer of defence (cognitive-affective gate). The integrated model can be custom tailored to specific situations, and the underlying principles applied to all methods for improving safety. The model may also provide a framework for developing and evaluating strategies to optimize organizational cultures and decisions. The concept is abstract, the

Gating the holes in the Swiss cheese (part I): Expanding professor Reason's model for patient safety

Science.gov (United States)

Bryan Young, G.; Makhinson, Michael; Smith, Preston A.; Stobart, Kent; Croskerry, Pat

2017-01-01

Abstract Introduction Although patient safety has improved steadily, harm remains a substantial global challenge. Additionally, safety needs to be ensured not only in hospitals but also across the continuum of care. Better understanding of the complex cognitive factors influencing health care–related decisions and organizational cultures could lead to more rational approaches, and thereby to further improvement. Hypothesis A model integrating the concepts underlying Reason's Swiss cheese theory and the cognitive‐affective biases plus cascade could advance the understanding of cognitive‐affective processes that underlie decisions and organizational cultures across the continuum of care. Methods Thematic analysis, qualitative information from several sources being used to support argumentation. Discussion Complex covert cognitive phenomena underlie decisions influencing health care. In the integrated model, the Swiss cheese slices represent dynamic cognitive‐affective (mental) gates: Reason's successive layers of defence. Like firewalls and antivirus programs, cognitive‐affective gates normally allow the passage of rational decisions but block or counter unsounds ones. Gates can be breached (ie, holes created) at one or more levels of organizations, teams, and individuals, by (1) any element of cognitive‐affective biases plus (conflicts of interest and cognitive biases being the best studied) and (2) other potential error‐provoking factors. Conversely, flawed decisions can be blocked and consequences minimized; for example, by addressing cognitive biases plus and error‐provoking factors, and being constantly mindful. Informed shared decision making is a neglected but critical layer of defence (cognitive‐affective gate). The integrated model can be custom tailored to specific situations, and the underlying principles applied to all methods for improving safety. The model may also provide a framework for developing and evaluating strategies to

Developing a new model for cross-cultural research: synthesizing the Health Belief Model and the Theory of Reasoned Action.

Science.gov (United States)

Poss, J E

2001-06-01

This article discusses the development of a new model representing the synthesis of two models that are often used to study health behaviors: the Health Belief Model and the Theory of Reasoned Action. The new model was developed as the theoretic framework for an investigation of the factors affecting participation by Mexican migrant workers in tuberculosis screening. Development of the synthesized model evolved from the concern that models used to investigate health-seeking behaviors of mainstream Anglo groups in the United States might not be appropriate for studying migrant workers or persons from other cultural backgrounds.

Obtaining reasonable assurance on geochemical aspects of performance assessment of deep geologic repositories

International Nuclear Information System (INIS)

Van Luik, A.E.; Serne, R.J.

1986-01-01

Providing reasonable assurance that a deep geologic disposal system will perform as required by regulation involves, in part, the building of confidence by providing a sound scientific basis for the site characterization, engineered system design, and system performance modeling efforts. Geochemistry plays a role in each of these activities. Site characterization must result in a description of the in situ geochemical environment that will support the design of the engineered system and the modeling of the transport of specific radionuclides to the accessible environment. Judging the adequacy of this site characterization effort is a major aspect of providing reasonable assurance. Within site characterization, there are a number of geochemical issues that need to be addressed such as the usefulness of natural analog studies, and assessing the very long-term stability of the site geochemistry, given expected temperature and radiation conditions

A study of critical reasoning in online learning: application of the Occupational Performance Process Model.

Science.gov (United States)

Mitchell, Anita Witt; Batorski, Rosemary E

2009-01-01

This study examined the effect of an online guided independent study on critical reasoning skills. Twenty-one first-semester Master of Occupational Therapy students completed an online assignment designed to facilitate application of the Occupational Performance Process Model (Fearing & Clark) and kept reflective journals. Data from the journals were analyzed in relation to the three sets of questions, question type and results of the Watson-Glaser Critical Thinking Appraisal (WGCTA). This assignment appeared to be effective for enhancing awareness and use of critical reasoning skills. Differences in patterns of critical reasoning between students with high and low WGCTA scores and results of an inductive analysis of the journal entries are discussed. Future research investigating the types of feedback that effectively facilitate development of critical reasoning and whether students with high and low WGCTA scores might benefit from different types of instruction and/or feedback is recommended. Copyright (c) 2009 John Wiley & Sons, Ltd.

The theory of reasoned action as parallel constraint satisfaction: towards a dynamic computational model of health behavior.

Directory of Open Access Journals (Sweden)

Mark G Orr

Full Text Available The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior, does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence. To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual's pre-existing belief structure and the beliefs of others in the individual's social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics.

The theory of reasoned action as parallel constraint satisfaction: towards a dynamic computational model of health behavior.

Science.gov (United States)

Orr, Mark G; Thrush, Roxanne; Plaut, David C

2013-01-01

The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence). To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA) using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning) with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual's pre-existing belief structure and the beliefs of others in the individual's social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics.

Theory of mind broad and narrow: reasoning about social exchange engages ToM areas, precautionary reasoning does not.

Science.gov (United States)

Ermer, Elsa; Guerin, Scott A; Cosmides, Leda; Tooby, John; Miller, Michael B

2006-01-01

Baron-Cohen (1995) proposed that the theory of mind (ToM) inference system evolved to promote strategic social interaction. Social exchange--a form of co-operation for mutual benefit--involves strategic social interaction and requires ToM inferences about the contents of other individuals' mental states, especially their desires, goals, and intentions. There are behavioral and neuropsychological dissociations between reasoning about social exchange and reasoning about equivalent problems tapping other, more general content domains. It has therefore been proposed that social exchange behavior is regulated by social contract algorithms: a domain-specific inference system that is functionally specialized for reasoning about social exchange. We report an fMRI study using the Wason selection task that provides further support for this hypothesis. Precautionary rules share so many properties with social exchange rules--they are conditional, deontic, and involve subjective utilities--that most reasoning theories claim they are processed by the same neurocomputational machinery. Nevertheless, neuroimaging shows that reasoning about social exchange activates brain areas not activated by reasoning about precautionary rules, and vice versa. As predicted, neural correlates of ToM (anterior and posterior temporal cortex) were activated when subjects interpreted social exchange rules, but not precautionary rules (where ToM inferences are unnecessary). We argue that the interaction between ToM and social contract algorithms can be reciprocal: social contract algorithms requires ToM inferences, but their functional logic also allows ToM inferences to be made. By considering interactions between ToM in the narrower sense (belief-desire reasoning) and all the social inference systems that create the logic of human social interaction--ones that enable as well as use inferences about the content of mental states--a broader conception of ToM may emerge: a computational model embodying

Reasoning with Causal Cycles

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Rehder, Bob

2017-01-01

This article assesses how people reason with categories whose features are related in causal cycles. Whereas models based on causal graphical models (CGMs) have enjoyed success modeling category-based judgments as well as a number of other cognitive phenomena, CGMs are only able to represent causal structures that are acyclic. A number of new…

Inductive reasoning about causally transmitted properties.

Science.gov (United States)

Shafto, Patrick; Kemp, Charles; Bonawitz, Elizabeth Baraff; Coley, John D; Tenenbaum, Joshua B

2008-11-01

Different intuitive theories constrain and guide inferences in different contexts. Formalizing simple intuitive theories as probabilistic processes operating over structured representations, we present a new computational model of category-based induction about causally transmitted properties. A first experiment demonstrates undergraduates' context-sensitive use of taxonomic and food web knowledge to guide reasoning about causal transmission and shows good qualitative agreement between model predictions and human inferences. A second experiment demonstrates strong quantitative and qualitative fits to inferences about a more complex artificial food web. A third experiment investigates human reasoning about complex novel food webs where species have known taxonomic relations. Results demonstrate a double-dissociation between the predictions of our causal model and a related taxonomic model [Kemp, C., & Tenenbaum, J. B. (2003). Learning domain structures. In Proceedings of the 25th annual conference of the cognitive science society]: the causal model predicts human inferences about diseases but not genes, while the taxonomic model predicts human inferences about genes but not diseases. We contrast our framework with previous models of category-based induction and previous formal instantiations of intuitive theories, and outline challenges in developing a complete model of context-sensitive reasoning.

Contextual factors and clinical reasoning: differences in diagnostic and therapeutic reasoning in board certified versus resident physicians.

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McBee, Elexis; Ratcliffe, Temple; Picho, Katherine; Schuwirth, Lambert; Artino, Anthony R; Yepes-Rios, Ana Monica; Masel, Jennifer; van der Vleuten, Cees; Durning, Steven J

2017-11-15

The impact of context on the complex process of clinical reasoning is not well understood. Using situated cognition as the theoretical framework and videos to provide the same contextual "stimulus" to all participants, we examined the relationship between specific contextual factors on diagnostic and therapeutic reasoning accuracy in board certified internists versus resident physicians. Each participant viewed three videotaped clinical encounters portraying common diagnoses in internal medicine. We explicitly modified the context to assess its impact on performance (patient and physician contextual factors). Patient contextual factors, including English as a second language and emotional volatility, were portrayed in the videos. Physician participant contextual factors were self-rated sleepiness and burnout.. The accuracy of diagnostic and therapeutic reasoning was compared with covariates using Fisher Exact, Mann-Whitney U tests and Spearman Rho's correlations as appropriate. Fifteen board certified internists and 10 resident physicians participated from 2013 to 2014. Accuracy of diagnostic and therapeutic reasoning did not differ between groups despite residents reporting significantly higher rates of sleepiness (mean rank 20.45 vs 8.03, U = 0.5, p reasoning performance. Further, the processes of diagnostic and therapeutic reasoning, although related, may not be interchangeable. This raises important questions about the impact that contextual factors have on clinical reasoning and provides insight into how clinical reasoning processes in more authentic settings may be explained by situated cognition theory.

Foundations for Reasoning in Cognition-Based Computational Representations of Human Decision Making; TOPICAL

International Nuclear Information System (INIS)

SENGLAUB, MICHAEL E.; HARRIS, DAVID L.; RAYBOURN, ELAINE M.

2001-01-01

In exploring the question of how humans reason in ambiguous situations or in the absence of complete information, we stumbled onto a body of knowledge that addresses issues beyond the original scope of our effort. We have begun to understand the importance that philosophy, in particular the work of C. S. Peirce, plays in developing models of human cognition and of information theory in general. We have a foundation that can serve as a basis for further studies in cognition and decision making. Peircean philosophy provides a foundation for understanding human reasoning and capturing behavioral characteristics of decision makers due to cultural, physiological, and psychological effects. The present paper describes this philosophical approach to understanding the underpinnings of human reasoning. We present the work of C. S. Peirce, and define sets of fundamental reasoning behavior that would be captured in the mathematical constructs of these newer technologies and would be able to interact in an agent type framework. Further, we propose the adoption of a hybrid reasoning model based on his work for future computational representations or emulations of human cognition

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....

Reasoning strategies modulate gender differences in emotion processing.

Science.gov (United States)

Markovits, Henry; Trémolière, Bastien; Blanchette, Isabelle

2018-01-01

The dual strategy model of reasoning has proposed that people's reasoning can be understood asa combination of two different ways of processing information related to problem premises: a counterexample strategy that examines information for explicit potential counterexamples and a statistical strategy that uses associative access to generate a likelihood estimate of putative conclusions. Previous studies have examined this model in the context of basic conditional reasoning tasks. However, the information processing distinction that underlies the dual strategy model can be seen asa basic description of differences in reasoning (similar to that described by many general dual process models of reasoning). In two studies, we examine how these differences in reasoning strategy may relate to processing very different information, specifically we focus on previously observed gender differences in processing negative emotions. Study 1 examined the intensity of emotional reactions to a film clip inducing primarily negative emotions. Study 2 examined the speed at which participants determine the emotional valence of sequences of negative images. In both studies, no gender differences were observed among participants using a counterexample strategy. Among participants using a statistical strategy, females produce significantly stronger emotional reactions than males (in Study 1) and were faster to recognize the valence of negative images than were males (in Study 2). Results show that the processing distinction underlying the dual strategy model of reasoning generalizes to the processing of emotions. Copyright © 2017 Elsevier B.V. All rights reserved.

Uncertain relational reasoning in the parietal cortex.

Science.gov (United States)

Ragni, Marco; Franzmeier, Imke; Maier, Simon; Knauff, Markus

2016-04-01

The psychology of reasoning is currently transitioning from the study of deductive inferences under certainty to inferences that have degrees of uncertainty in both their premises and conclusions; however, only a few studies have explored the cortical basis of uncertain reasoning. Using transcranial magnetic stimulation (TMS), we show that areas in the right superior parietal lobe (rSPL) are necessary for solving spatial relational reasoning problems under conditions of uncertainty. Twenty-four participants had to decide whether a single presented order of objects agreed with a given set of indeterminate premises that could be interpreted in more than one way. During the presentation of the order, 10-Hz TMS was applied over the rSPL or a sham control site. Right SPL TMS during the inference phase disrupted performance in uncertain relational reasoning. Moreover, we found differences in the error rates between preferred mental models, alternative models, and inconsistent models. Our results suggest that different mechanisms are involved when people reason spatially and evaluate different kinds of uncertain conclusions. Copyright © 2016 Elsevier Inc. All rights reserved.

Concept model semantics for DL preferential reasoning

CSIR Research Space (South Africa)

Britz, K

2011-07-01

Full Text Available ., Olivetti, N., Gliozzi, V., Pozzato, G.: ALC +T : a preferential exten- sion of description logics. Fund. Informatica 96(3), 341{372 (2009) 7. Kraus, S., Lehmann, D., Magidor, M.: Nonmonotonic reasoning, preferential mod- els and cumulative logics. Arti...

From Biomedical to Psychosomatic Reasoning: A Theoretical Framework

Directory of Open Access Journals (Sweden)

Alireza Monajemi

2014-01-01

Full Text Available Despite a general acceptance of the biopsychosocial model, medical education and patient care are still largely biomedical in focus, and physicians have many deficiencies in biopsychosocial formulations and care. Education in medical schools puts more emphasis on providing biomedical education (BM than biopsychosocial education (BPS; the initial knowledge formed in medical students is mainly with a biomedical approach. Therefore, it seems that psychosocial aspects play a minor role at this level and PSM knowledge will lag behind BM knowledge. However, it seems that the integration of biomedical and psychosocial-knowledge is crucial for a successful and efficient patient encounter. In this paper, based on the theory of medical expertise development, the steps through which biomedical reasoning transforms to psychosomatic reasoning will be discussed.

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.

Clinical Reasoning in Medicine: A Concept Analysis

Directory of Open Access Journals (Sweden)

Shahram Yazdani

2018-01-01

Full Text Available Background: Clinical reasoning plays an important role in the ability of physicians to make diagnoses and decisions. It is considered the physician’s most critical competence, but it is an ambiguous conceptin medicine that needs a clear analysis and definition. Our aim was to clarify the concept of clinical reasoning in medicine by identifying its components and to differentiate it from other similar concepts.It is necessary to have an operational definition of clinical reasoning, and its components must be precisely defined in order to design successful interventions and use it easily in future research.Methods: McKenna’s nine-step model was applied to facilitate the clarification of the concept of clinical reasoning. The literature for this concept analysis was retrieved from several databases, including Scopus, Elsevier, PubMed, ISI, ISC, Medline, and Google Scholar, for the years 1995– 2016 (until September 2016. An extensive search of the literature was conducted using the electronic database. Accordingly, 17 articles and one book were selected for the review. We applied McKenna’s method of concept analysis in studying clinical reasoning, so that definitional attributes, antecedents, and consequences of this concept were extracted.Results: Clinical reasoning has nine major attributes in medicine. These attributes include: (1 clinical reasoning as a cognitive process; (2 knowledge acquisition and application of different types of knowledge; (3 thinking as a part of the clinical reasoning process; (4 patient inputs; (5 contextdependent and domain-specific processes; (6 iterative and complex processes; (7 multi-modal cognitive processes; (8 professional principles; and (9 health system mandates. These attributes are influenced by the antecedents of workplace context, practice frames of reference, practice models of the practitioner, and clinical skills. The consequences of clinical reasoning are the metacognitive improvement of

Evaluation of high-level waste pretreatment processes with an approximate reasoning model

International Nuclear Information System (INIS)

Bott, T.F.; Eisenhawer, S.W.; Agnew, S.F.

1999-01-01

The development of an approximate-reasoning (AR)-based model to analyze pretreatment options for high-level waste is presented. AR methods are used to emulate the processes used by experts in arriving at a judgment. In this paper, the authors first consider two specific issues in applying AR to the analysis of pretreatment options. They examine how to combine quantitative and qualitative evidence to infer the acceptability of a process result using the example of cesium content in low-level waste. They then demonstrate the use of simple physical models to structure expert elicitation and to produce inferences consistent with a problem involving waste particle size effects

Reasons Internalism and the function of normative reasons

OpenAIRE

Sinclair, Neil

2017-01-01

What is the connection between reasons and motives? According to Reasons Internalism there is a non-trivial conceptual connection between normative reasons and the possibility of rationally accessing relevant motivation. Reasons Internalism is attractive insofar as it captures the thought that reasons are for reasoning with and repulsive insofar as it fails to generate sufficient critical distance between reasons and motives. Rather than directly adjudicate this dispute, I extract from it two...

Autonomous e-coaching in the wild: Empirical validation of a model-based reasoning system

OpenAIRE

Kamphorst, B.A.; Klein, M.C.A.; van Wissen, A.

2014-01-01

Autonomous e-coaching systems have the potential to improve people's health behaviors on a large scale. The intelligent behavior change support system eMate exploits a model of the human agent to support individuals in adopting a healthy lifestyle. The system attempts to identify the causes of a person's non-adherence by reasoning over a computational model (COMBI) that is based on established psychological theories of behavior change. The present work presents an extensive, monthlong empiric...

Team reasoning: Solving the puzzle of coordination.

Science.gov (United States)

Colman, Andrew M; Gold, Natalie

2017-11-03

In many everyday activities, individuals have a common interest in coordinating their actions. Orthodox game theory cannot explain such intuitively obvious forms of coordination as the selection of an outcome that is best for all in a common-interest game. Theories of team reasoning provide a convincing solution by proposing that people are sometimes motivated to maximize the collective payoff of a group and that they adopt a distinctive mode of reasoning from preferences to decisions. This also offers a compelling explanation of cooperation in social dilemmas. A review of team reasoning and related theories suggests how team reasoning could be incorporated into psychological theories of group identification and social value orientation theory to provide a deeper understanding of these phenomena.

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...

Modeling Market Shares of Competing (e)Care Providers

Science.gov (United States)

van Ooteghem, Jan; Tesch, Tom; Verbrugge, Sofie; Ackaert, Ann; Colle, Didier; Pickavet, Mario; Demeester, Piet

In order to address the increasing costs of providing care to the growing group of elderly, efficiency gains through eCare solutions seem an obvious solution. Unfortunately not many techno-economic business models to evaluate the return of these investments are available. The construction of a business case for care for the elderly as they move through different levels of dependency and the effect of introducing an eCare service, is the intended application of the model. The simulation model presented in this paper allows for modeling evolution of market shares of competing care providers. Four tiers are defined, based on the dependency level of the elderly, for which the market shares are determined. The model takes into account available capacity of the different care providers, in- and outflow distribution between tiers and churn between providers within tiers.

Development and necessary norms of reasoning

Science.gov (United States)

Markovits, Henry

2014-01-01

The question of whether reasoning can, or should, be described by a single normative model is an important one. In the following, I combine epistemological considerations taken from Piaget’s notion of genetic epistemology, a hypothesis about the role of reasoning in communication and developmental data to argue that some basic logical principles are in fact highly normative. I argue here that explicit, analytic human reasoning, in contrast to intuitive reasoning, uniformly relies on a form of validity that allows distinguishing between valid and invalid arguments based on the existence of counterexamples to conclusions. PMID:24904501

MENGEMBANGKAN PENALARAN ILMIAH (SCIENTIFIC REASONING SISWA MELALUI MODEL PEMBELAJRAN 5E PADA SISWA KELAS X SMAN 15 SURABAYA

Directory of Open Access Journals (Sweden)

N. Shofiyah

2013-04-01

Full Text Available Tujuan dari penelitian ini adalah untuk mengembangkan perangkat pembelajaran menggunakan model 5E untuk meningkatkan keterampilan penalaran ilmiah siswa. Hasil dari penelitian ini menunjukkan bahwa perangkat pembelajaran yang dikembangkan dengan model 5E valid untuk diterapkan di dalam kelas, BAS memiliki keterbacaan yang bagus, keterlaksanaan RPP dikategorikan baik, model pembelajaran 5E secara efektif dapat mening-katkan keterampilan penalaran ilmiah siswa dan siswa memberikan respon yang positif terhadap pembelajaran. The purpose of this research is to develop the 5E model of learning to improve students’ scientific reasoning skills. The results of this study show that the developed learning model 5E valid to be applied in the classroom, BAS has good readability, keterlaksanaan RPP well categorized, 5E learning model can effectively improve students’ scientific reasoning skills and the students responded positively to the learning.

Towards Automated Reasoning on ORM Schemes

Science.gov (United States)

Jarrar, Mustafa

The goal of this article is to formalize Object Role Modeling (ORM) using the {DLR} description logic. This would enable automated reasoning on the formal properties of ORM diagrams, such as detecting constraint contradictions and implications. In addition, the expressive, methodological, and graphical capabilities of ORM make it a good candidate for use as a graphical notation for most description logic languages. In this way, industrial experts who are not IT savvy will still be able to build and view axiomatized theories (such as ontologies, business rules, etc.) without needing to know the logic or reasoning foundations underpinning them. Our formalization in this paper is structured as 29 formalization rules, that map all ORM primitives and constraints into {DLR}, and 2 exceptions of complex cases. To this end, we illustrate the implementation of our formalization as an extension to DogmaModeler, which automatically maps ORM into DIG and uses Racer as a background reasoning engine to reason about ORM diagrams.

Approximate reasoning in physical systems

International Nuclear Information System (INIS)

Mutihac, R.

1991-01-01

The theory of fuzzy sets provides excellent ground to deal with fuzzy observations (uncertain or imprecise signals, wavelengths, temperatures,etc.) fuzzy functions (spectra and depth profiles) and fuzzy logic and approximate reasoning. First, the basic ideas of fuzzy set theory are briefly presented. Secondly, stress is put on application of simple fuzzy set operations for matching candidate reference spectra of a spectral library to an unknown sample spectrum (e.g. IR spectroscopy). Thirdly, approximate reasoning is applied to infer an unknown property from information available in a database (e.g. crystal systems). Finally, multi-dimensional fuzzy reasoning techniques are suggested. (Author)

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.

What is the role of induction and deduction in reasoning and scientific inquiry?

Science.gov (United States)

Lawson, Anton E.

2005-08-01

A long-standing and continuing controversy exists regarding the role of induction and deduction in reasoning and in scientific inquiry. Given the inherent difficulty in reconstructing reasoning patterns based on personal and historical accounts, evidence about the nature of human reasoning in scientific inquiry has been sought from a controlled experiment designed to identify the role played by enumerative induction and deduction in cognition as well as from the relatively new field of neural modeling. Both experimental results and the neurological models imply that induction across a limited set of observations plays no role in task performance and in reasoning. Therefore, support has been obtained for Popper's hypothesis that enumerative induction does not exist as a psychological process. Instead, people appear to process information in terms of increasingly abstract cycles of hypothetico-deductive reasoning. Consequently, science instruction should provide students with opportunities to generate and test increasingly complex and abstract hypotheses and theories in a hypothetico-deductive manner. In this way students can be expected to become increasingly conscious of their underlying hypothetico-deductive thought processes, increasingly skilled in their application, and hence increasingly scientifically literate.

The operator model as a framework of research on errors and temporal, qualitative and analogical reasoning

International Nuclear Information System (INIS)

Decortis, F.; Drozdowicz, B.; Masson, M.

1990-01-01

In this paper the needs and requirements for developing a cognitive model of a human operator are discussed and the computer architecture, currently being developed, is described. Given the approach taken, namely the division of the problem into specialised tasks within an area and using the architecture chosen, it is possible to build independently several cognitive and psychological models such as errors and stress models, as well as models of temporal, qualitative and an analogical reasoning. (author)

Characteristics of Adolescents Lacking Provider-Recommended Human Papillomavirus Vaccination.

Science.gov (United States)

Krakow, Melinda; Beavis, Anna; Cosides, Olivia; Rositch, Anne F

2017-05-01

To characterize subgroups of teens in the United States for whom provider recommendation is less likely to impact human papillomavirus (HPV) vaccine initiation. We analyzed provider-verified vaccination data from the Centers for Disease Control and Prevention's 2014 National Immunization Survey-Teen. Poisson regression models identified characteristics associated with the lack of HPV vaccine initiation among teens who received a provider recommendation (n = 12,742). Top qualitative reasons for nonvaccination among teens who received a provider recommendation were summarized (n = 1,688). Among teens with provider recommendations, males, younger teens, and white teens were less likely to initiate vaccination, compared to peers. Believing the vaccine was unnecessary, concerns about safety and lack of vaccine knowledge were common reasons parents did not initiate the vaccine, despite receiving provider recommendations. These key subgroups and barriers to HPV vaccination should be targeted with interventions that complement provider recommendation to achieve broad vaccine uptake in the United States. Published by Elsevier Inc.

Modeling patients' acceptance of provider-delivered e-health.

Science.gov (United States)

Wilson, E Vance; Lankton, Nancy K

2004-01-01

Health care providers are beginning to deliver a range of Internet-based services to patients; however, it is not clear which of these e-health services patients need or desire. The authors propose that patients' acceptance of provider-delivered e-health can be modeled in advance of application development by measuring the effects of several key antecedents to e-health use and applying models of acceptance developed in the information technology (IT) field. This study tested three theoretical models of IT acceptance among patients who had recently registered for access to provider-delivered e-health. An online questionnaire administered items measuring perceptual constructs from the IT acceptance models (intrinsic motivation, perceived ease of use, perceived usefulness/extrinsic motivation, and behavioral intention to use e-health) and five hypothesized antecedents (satisfaction with medical care, health care knowledge, Internet dependence, information-seeking preference, and health care need). Responses were collected and stored in a central database. All tested IT acceptance models performed well in predicting patients' behavioral intention to use e-health. Antecedent factors of satisfaction with provider, information-seeking preference, and Internet dependence uniquely predicted constructs in the models. Information technology acceptance models provide a means to understand which aspects of e-health are valued by patients and how this may affect future use. In addition, antecedents to the models can be used to predict e-health acceptance in advance of system development.

Analogical reasoning abilities of recovering alcoholics.

Science.gov (United States)

Gardner, M K; Clark, E; Bowman, M A; Miller, P J

1989-08-01

This study investigated analogical reasoning abilities of alcoholics who had been abstinent from alcohol for at least 1 year. Their performance was compared to that of nonalcoholic controls matched as a group for education, age, and gender. Solution times and error rates were modeled using a regression model. Results showed a nonsignificant trend for alcoholics to be faster, but more error prone, than controls. The same componential model applied to both groups, and fit them equally well. Although differences have been found in analogical reasoning ability between controls and alcoholics immediately following detoxification, we find no evidence of differences after extended periods of sobriety.

A logic for inductive probabilistic reasoning

DEFF Research Database (Denmark)

Jaeger, Manfred

2005-01-01

Inductive probabilistic reasoning is understood as the application of inference patterns that use statistical background information to assign (subjective) probabilities to single events. The simplest such inference pattern is direct inference: from '70% of As are Bs" and "a is an A" infer...... that a is a B with probability 0.7. Direct inference is generalized by Jeffrey's rule and the principle of cross-entropy minimization. To adequately formalize inductive probabilistic reasoning is an interesting topic for artificial intelligence, as an autonomous system acting in a complex environment may have...... to base its actions on a probabilistic model of its environment, and the probabilities needed to form this model can often be obtained by combining statistical background information with particular observations made, i.e., by inductive probabilistic reasoning. In this paper a formal framework...

The effect of emotion on interpretation and logic in a conditional reasoning task.

Science.gov (United States)

Blanchette, Isabelle

2006-07-01

The effect of emotional content on logical reasoning is explored in three experiments. Theparticipants completed a conditional reasoning task (If p, then q) with emotional and neutral contents. In Experiment 1, existing emotional and neutral words were used. The emotional value of initially neutral words was experimentally manipulated in Experiments 1B and 2, using classical conditioning. In all experiments, participants were less likely to provide normatively correct answers when reasoning about emotional stimuli, compared with neutral stimuli. This was true for both negative (Experiments 1B and 2) and positive contents (Experiment 2). The participants' interpretations of the conditional statements were also measured (perceived sufficiency, necessity, causality, and plausibility). The results showed the expected relationship between interpretation and reasoning. However, emotion did not affect interpretation. Emotional and neutral conditional statements were interpreted similarly. The results are discussed in light of current models of emotion and reasoning.

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

Patterns of Reasoning about Ecological Systemic Reasoning for Early Elementary Students

Science.gov (United States)

Hokayem, H.

2016-01-01

Systems and system models are recognized as a crosscutting concept in the newly released framework for K-12 science education (NRC [National Research Council], 2012). In previous work, I developed a learning progression for systemic reasoning in ecology at the elementary level. The learning progression captured five levels of students' reasoning…

Stimulating Mathematical Reasoning with Simple Open-Ended Tasks

Science.gov (United States)

West, John

2018-01-01

The importance of mathematical reasoning is unquestioned and providing opportunities for students to become involved in mathematical reasoning is paramount. The open-ended tasks presented incorporate mathematical content explored through the contexts of problem solving and reasoning. This article presents a number of simple tasks that may be…

Nurses' perception of the quality of care they provide to hospitalized drug addicts: testing the theory of reasoned action.

Science.gov (United States)

Natan, Merav Ben; Beyil, Valery; Neta, Okev

2009-12-01

A correlational design was used to examine nursing staff attitudes and subjective norms manifested in intended and actual care of drug users based on the Theory of Reasoned Action. One hundred and thirty-five nursing staff from three central Israeli hospitals completed a questionnaire examining theory-based variables as well as sociodemographic and professional characteristics. Most respondents reported a high to very high level of actual or intended care of drug users. Nurses' stronger intentions to provide quality care to drug users were associated with more positive attitudes. Nursing staff members had moderately negative attitudes towards drug users. Nurses were found to hold negative stereotypes of drug addict patients and most considered the management of this group difficult. Positive attitudes towards drug users, perceived expectations of others and perceived correctness of the behaviour are important in their effect on the intention of nurses to provide high-quality care to hospitalized patients addicted to drugs.

CONFLICTING REASONS

OpenAIRE

Parfit, Derek

2016-01-01

Sidgwick believed that, when impartial reasons conflict with self-interested reasons, there are no truths about their relative strength. There are such truths, I claim, but these truths are imprecise. Many self-interested reasons are decisively outweighed by conflicting impar-tial moral reasons. But we often have sufficient self-interested reasons to do what would make things go worse, and we sometimes have sufficient self-interested reasons to act wrongly. If we reject Act Consequentialism, ...

Development of the Statistical Reasoning in Biology Concept Inventory (SRBCI)

Science.gov (United States)

Deane, Thomas; Nomme, Kathy; Jeffery, Erica; Pollock, Carol; Birol, Gülnur

2016-01-01

We followed established best practices in concept inventory design and developed a 12-item inventory to assess student ability in statistical reasoning in biology (Statistical Reasoning in Biology Concept Inventory [SRBCI]). It is important to assess student thinking in this conceptual area, because it is a fundamental requirement of being statistically literate and associated skills are needed in almost all walks of life. Despite this, previous work shows that non–expert-like thinking in statistical reasoning is common, even after instruction. As science educators, our goal should be to move students along a novice-to-expert spectrum, which could be achieved with growing experience in statistical reasoning. We used item response theory analyses (the one-parameter Rasch model and associated analyses) to assess responses gathered from biology students in two populations at a large research university in Canada in order to test SRBCI’s robustness and sensitivity in capturing useful data relating to the students’ conceptual ability in statistical reasoning. Our analyses indicated that SRBCI is a unidimensional construct, with items that vary widely in difficulty and provide useful information about such student ability. SRBCI should be useful as a diagnostic tool in a variety of biology settings and as a means of measuring the success of teaching interventions designed to improve statistical reasoning skills. PMID:26903497

Using Popular Culture to Teach Quantitative Reasoning

Science.gov (United States)

Hillyard, Cinnamon

2007-01-01

Popular culture provides many opportunities to develop quantitative reasoning. This article describes a junior-level, interdisciplinary, quantitative reasoning course that uses examples from movies, cartoons, television, magazine advertisements, and children's literature. Some benefits from and cautions to using popular culture to teach…

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.…

Systematic Clinical Reasoning in Physical Therapy (SCRIPT): Tool for the Purposeful Practice of Clinical Reasoning in Orthopedic Manual Physical Therapy.

Science.gov (United States)

Baker, Sarah E; Painter, Elizabeth E; Morgan, Brandon C; Kaus, Anna L; Petersen, Evan J; Allen, Christopher S; Deyle, Gail D; Jensen, Gail M

2017-01-01

Clinical reasoning is essential to physical therapist practice. Solid clinical reasoning processes may lead to greater understanding of the patient condition, early diagnostic hypothesis development, and well-tolerated examination and intervention strategies, as well as mitigate the risk of diagnostic error. However, the complex and often subconscious nature of clinical reasoning can impede the development of this skill. Protracted tools have been published to help guide self-reflection on clinical reasoning but might not be feasible in typical clinical settings. This case illustrates how the Systematic Clinical Reasoning in Physical Therapy (SCRIPT) tool can be used to guide the clinical reasoning process and prompt a physical therapist to search the literature to answer a clinical question and facilitate formal mentorship sessions in postprofessional physical therapist training programs. The SCRIPT tool enabled the mentee to generate appropriate hypotheses, plan the examination, query the literature to answer a clinical question, establish a physical therapist diagnosis, and design an effective treatment plan. The SCRIPT tool also facilitated the mentee's clinical reasoning and provided the mentor insight into the mentee's clinical reasoning. The reliability and validity of the SCRIPT tool have not been formally studied. Clinical mentorship is a cornerstone of postprofessional training programs and intended to develop advanced clinical reasoning skills. However, clinical reasoning is often subconscious and, therefore, a challenging skill to develop. The use of a tool such as the SCRIPT may facilitate developing clinical reasoning skills by providing a systematic approach to data gathering and making clinical judgments to bring clinical reasoning to the conscious level, facilitate self-reflection, and make a mentored physical therapist's thought processes explicit to his or her clinical mentor. © 2017 American Physical Therapy Association

Giving Devices the Ability to Exercise Reason

Directory of Open Access Journals (Sweden)

Thomas Keeley

2008-10-01

Full Text Available One of the capabilities that separates humans from computers has been the ability to exercise "reason / judgment". Computers and computerized devices have provided excellent platforms for following rules. Computer programs provide the scripts for processing the rules. The exercise of reason, however, is more of an image processing function than a function composed of a series of rules. The exercise of reason is more right brain than left brain. It involves the interpretation of information and balancing inter-related alternatives. This paper will discuss a new way to define and process information that will give devices the ability to exercise human-like reasoning and judgment. The paper will discuss the characteristics of a "dynamic graphical language" in the context of addressing judgment, since judgment is often required to adjust rules when operating in a dynamic environment. The paper will touch on architecture issues and how judgment is integrated with rule processing.

Logic, probability, and human reasoning.

Science.gov (United States)

Johnson-Laird, P N; Khemlani, Sangeet S; Goodwin, Geoffrey P

2015-04-01

This review addresses the long-standing puzzle of how logic and probability fit together in human reasoning. Many cognitive scientists argue that conventional logic cannot underlie deductions, because it never requires valid conclusions to be withdrawn - not even if they are false; it treats conditional assertions implausibly; and it yields many vapid, although valid, conclusions. A new paradigm of probability logic allows conclusions to be withdrawn and treats conditionals more plausibly, although it does not address the problem of vapidity. The theory of mental models solves all of these problems. It explains how people reason about probabilities and postulates that the machinery for reasoning is itself probabilistic. Recent investigations accordingly suggest a way to integrate probability and deduction. Copyright © 2015 Elsevier Ltd. All rights reserved.

Comparison of Ontology Reasoners: Racer, Pellet, Fact++

Science.gov (United States)

Huang, T.; Li, W.; Yang, C.

2008-12-01

In this paper, we examine some key aspects of three of the most popular and effective Semantic reasoning engines that have been developed: Pellet, RACER, and Fact++. While these reasonably advanced reasoners share some notable similarities, it is ultimately the creativity and unique nature of these reasoning engines that have resulted in the successes of each of these reasoners. Of the numerous dissimilarities, the most obvious example might be that while Pellet is written in Java, RACER employs the Lisp programming language and Fact++ was developed using C++. From this and many other distinctions in the system architecture, we can understand the benefits of each reasoner and potentially discover certain properties that may contribute to development of an optimal reasoner in the future. The objective of this paper is to establish a solid comparison of the reasoning engines based on their system architectures, features, and overall performances in real world application. In the end, we expect to produce a valid conclusion about the advantages and problems in each reasoner. While there may not be a decisive first place among the three reasoners, the evaluation will also provide some answers as to which of these current reasoning tools will be most effective in common, practical situations.

Probabilistic reasoning in intelligent systems networks of plausible inference

CERN Document Server

Pearl, Judea

1988-01-01

Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic. The author distinguishes syntactic and semantic approaches to uncertainty--and offers techniques, based on belief networks, that provid

Relating Derived Relations as a Model of Analogical Reasoning: Reaction Times and Event-Related Potentials

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Barnes-Holmes, Dermot; Regan, Donal; Barnes-Holmes, Yvonne; Commins, Sean; Walsh, Derek; Stewart, Ian; Smeets, Paul M.; Whelan, Robert; Dymond, Simon

2005-01-01

The current study aimed to test a Relational Frame Theory (RFT) model of analogical reasoning based on the relating of derived same and derived difference relations. Experiment 1 recorded reaction time measures of similar-similar (e.g., "apple is to orange as dog is to cat") versus different-different (e.g., "he is to his brother as…

Promoting Modeling and Covariational Reasoning among Secondary School Students in the Context of Big Data

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Gil, Einat; Gibbs, Alison L.

2017-01-01

In this study, we follow students' modeling and covariational reasoning in the context of learning about big data. A three-week unit was designed to allow 12th grade students in a mathematics course to explore big and mid-size data using concepts such as trend and scatter to describe the relationships between variables in multivariate settings.…

The effect of creative problem solving on students’ mathematical adaptive reasoning

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Muin, A.; Hanifah, S. H.; Diwidian, F.

2018-01-01

This research was conducted to analyse the effect of creative problem solving (CPS) learning model on the students’ mathematical adaptive reasoning. The method used in this study was a quasi-experimental with randomized post-test only control group design. Samples were taken as many as two classes by cluster random sampling technique consisting of experimental class (CPS) as many as 40 students and control class (conventional) as many as 40 students. Based on the result of hypothesis testing with the t-test at the significance level of 5%, it was obtained that significance level of 0.0000 is less than α = 0.05. This shows that the students’ mathematical adaptive reasoning skills who were taught by CPS model were higher than the students’ mathematical adaptive reasoning skills of those who were taught by conventional model. The result of this research showed that the most prominent aspect of adaptive reasoning that could be developed through a CPS was inductive intuitive. Two aspects of adaptive reasoning, which were inductive intuitive and deductive intuitive, were mostly balanced. The different between inductive intuitive and deductive intuitive aspect was not too big. CPS model can develop student mathematical adaptive reasoning skills. CPS model can facilitate development of mathematical adaptive reasoning skills thoroughly.

Content-related interactions and methods of reasoning within self-initiated organic chemistry study groups

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Christian, Karen Jeanne

2011-12-01

Students often use study groups to prepare for class or exams; yet to date, we know very little about how these groups actually function. This study looked at the ways in which undergraduate organic chemistry students prepared for exams through self-initiated study groups. We sought to characterize the methods of social regulation, levels of content processing, and types of reasoning processes used by students within their groups. Our analysis showed that groups engaged in predominantly three types of interactions when discussing chemistry content: co-construction, teaching, and tutoring. Although each group engaged in each of these types of interactions at some point, their prevalence varied between groups and group members. Our analysis suggests that the types of interactions that were most common depended on the relative content knowledge of the group members as well as on the difficulty of the tasks in which they were engaged. Additionally, we were interested in characterizing the reasoning methods used by students within their study groups. We found that students used a combination of three content-relevant methods of reasoning: model-based reasoning, case-based reasoning, or rule-based reasoning, in conjunction with one chemically-irrelevant method of reasoning: symbol-based reasoning. The most common way for groups to reason was to use rules, whereas the least common way was for students to work from a model. In general, student reasoning correlated strongly to the subject matter to which students were paying attention, and was only weakly related to student interactions. Overall, results from this study may help instructors to construct appropriate tasks to guide what and how students study outside of the classroom. We found that students had a decidedly strategic approach in their study groups, relying heavily on material provided by their instructors, and using the reasoning strategies that resulted in the lowest levels of content processing. We suggest

Reason with me : 'Confabulation' and interpersonal moral reasoning

NARCIS (Netherlands)

Nyholm, S.R.

2015-01-01

According to Haidt’s ‘social intuitionist model’, empirical moral psychology supports the following conclusion: intuition comes first, strategic reasoning second. Critics have responded by arguing that intuitions can depend on non-conscious reasons, that not being able to articulate one’s reasons

Human rights reasoning and medical law: a sceptical essay.

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Wall, Jesse

2015-03-01

I am sceptical as to the contribution that human rights can make to our evaluation of medical law. I will argue here that viewing medical law through a human rights framework provides no greater clarity, insight or focus. If anything, human rights reasoning clouds any bioethical or evaluative analysis. In Section 1 of this article, I outline the general structure of human rights reasoning. I will describe human rights reasoning as (a) reasoning from rights that each person has 'by virtue of their humanity', (b) reasoning from rights that provide 'hard to defeat' reasons for action and (c) reasoning from abstract norms to specified duties. I will then argue in Section 2 that, unless we (a) re-conceive of human rights as narrow categories of liberties, it becomes (b) necessary for our human rights reasoning to gauge the normative force of each claim or liberty. When we apply this approach to disputes in medical law, we (in the best case scenario) end up (c) 'looking straight through' the human right to the (disagreement about) values and features that each person has by virtue of their humanity. © 2014 John Wiley & Sons Ltd.

Theoretical and practical significance of formal reasoning

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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.

Priming analogical reasoning with false memories.

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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.

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

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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,…

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

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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.

EXPLORATION OF RELEVANCE EFFECTS IN REASONING

OpenAIRE

VENN, SIMON FRANCIS

2003-01-01

The study examines possible underlying mechanisms that may be responsible for generally observed biased response patterns in two conditional reasoning tasks: the Wason selection task and the conditional inference evaluation task. It is proposed that memory processes that may account for priming phenomenon, may also account for the phenomena of matching bias and double-negation effects in reasoning. A new mental activation model is proposed, based on distributed theories of memo...

Effects of Inquiry-Based Agriscience Instruction on Student Scientific Reasoning

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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…

Reasoning about the past

DEFF Research Database (Denmark)

Nielsen, Mogens

1998-01-01

In this extended abstract, we briefly recall the abstract (categorical) notion of bisimulation from open morphisms, as introduced by Joyal, Nielsen and Winskel. The approach is applicable across a wide range of models of computation, and any such bisimulation comes automatically with characterist...... of reasoning about the past....

Eye Movements Reveal Optimal Strategies for Analogical Reasoning.

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Vendetti, Michael S; Starr, Ariel; Johnson, Elizabeth L; Modavi, Kiana; Bunge, Silvia A

2017-01-01

Analogical reasoning refers to the process of drawing inferences on the basis of the relational similarity between two domains. Although this complex cognitive ability has been the focus of inquiry for many years, most models rely on measures that cannot capture individuals' thought processes moment by moment. In the present study, we used participants' eye movements to investigate reasoning strategies in real time while solving visual propositional analogy problems (A:B::C:D). We included both a semantic and a perceptual lure on every trial to determine how these types of distracting information influence reasoning strategies. Participants spent more time fixating the analogy terms and the target relative to the other response choices, and made more saccades between the A and B items than between any other items. Participants' eyes were initially drawn to perceptual lures when looking at response choices, but they nonetheless performed the task accurately. We used participants' gaze sequences to classify each trial as representing one of three classic analogy problem solving strategies and related strategy usage to analogical reasoning performance. A project-first strategy, in which participants first extrapolate the relation between the AB pair and then generalize that relation for the C item, was both the most commonly used strategy as well as the optimal strategy for solving visual analogy problems. These findings provide new insight into the role of strategic processing in analogical problem solving.

Eye Movements Reveal Optimal Strategies for Analogical Reasoning

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Michael S. Vendetti

2017-06-01

Full Text Available Analogical reasoning refers to the process of drawing inferences on the basis of the relational similarity between two domains. Although this complex cognitive ability has been the focus of inquiry for many years, most models rely on measures that cannot capture individuals' thought processes moment by moment. In the present study, we used participants' eye movements to investigate reasoning strategies in real time while solving visual propositional analogy problems (A:B::C:D. We included both a semantic and a perceptual lure on every trial to determine how these types of distracting information influence reasoning strategies. Participants spent more time fixating the analogy terms and the target relative to the other response choices, and made more saccades between the A and B items than between any other items. Participants' eyes were initially drawn to perceptual lures when looking at response choices, but they nonetheless performed the task accurately. We used participants' gaze sequences to classify each trial as representing one of three classic analogy problem solving strategies and related strategy usage to analogical reasoning performance. A project-first strategy, in which participants first extrapolate the relation between the AB pair and then generalize that relation for the C item, was both the most commonly used strategy as well as the optimal strategy for solving visual analogy problems. These findings provide new insight into the role of strategic processing in analogical problem solving.

Thematic Reasoning and Theory of Mind. Accounting for Social Inference Difficulties in Schizophrenia

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Rhiannon Corcoran

2005-01-01

Full Text Available Background Corcoran (2000, 2001 has suggested that theory of mind judgements can be arrived at using analogical reasoning skills and she has proposed that this is the route that people with schizophrenia take when they make inferences about others' mental states. Recent work has demonstrated a robust relationship between mental state inference and autobiographical memory, providing initial support for the model. This study examines the model further by exploring the assertion that in schizophrenia the ability to infer the mental states of others also depends upon effective social reasoning in conditional contexts. Method 59 people with a DSM IV diagnosis of schizophrenia and 44 healthy subjects performed four versions of the thematic selection task. The versions varied according to the familiarity and social nature of the material they incorporated. The same subjects also completed the Hinting Task, a measure of theory of mind and tests of intellectual functioning and narrative recall. Results The schizophrenia and the normal control groups differed in their performance on all of the measures except that of intellectual functioning. Explorations within the schizophrenia group indicated that social reasoning was most markedly affected in the patients with negative signs and in those with paranoid delusions while for the hinting task, those with negative signs performed significantly worse than those in remission but this difference seemed to be due to these patients' poorer narrative memory. There was evidence in the schizophrenia data to support the hypothesis of a relationship between theory of mind and social conditional reasoning. Conclusion This work provided further support for the idea that in patients with schizophrenia at least, judgements about the mental states of others are achieved using analogical reasoning.

Reasoning about Magnetism at the Microscopic Level

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Cheng, Meng-Fei; Cheng, Yufang; Hung, Shuo-Hsien

2014-01-01

Based on our experience of teaching physics in middle and senior secondary school, we have found that students have difficulty in reasoning at the microscopic level. Their reasoning is limited to the observational level so they have problems in developing scientific models of magnetism. Here, we suggest several practical activities and the use of…

Artificial intelligence: Deep neural reasoning

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Jaeger, Herbert

2016-10-01

The human brain can solve highly abstract reasoning problems using a neural network that is entirely physical. The underlying mechanisms are only partially understood, but an artificial network provides valuable insight. See Article p.471

Using Relational Reasoning Strategies to Help Improve Clinical Reasoning Practice.

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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.

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.

The ethical reasoning variations of personal characteristics

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Khalizani Khalid

2012-06-01

Full Text Available This study provides a comparison of the ethical reasoning components of business managers and executives based on personal characteristics of working experiences, gender and age group. Data were collected in Malaysia within the small and medium sized industry in the form of questionnaires which contain vignettes of questionable ethical reasoning issues. Factor analysis was used to identify the major ethical reasoning dimensions which were then used as the basic comparison. Our study reviews that SMEs managers’ and executives’ ethical reasoning influenced by their years of working experiences. The gap analysis between male and female managers and executives revealed that the significant difference only occurs for ethical awareness in business management and business practices but not for other dimensions. Besides, there are indications that generally, business people tend to have higher ethical reasoning evaluation when they reach thirty six years old. Based on our results, recommendations are made to improve the ethical reasoning evaluation of business managers and executives.

Investigating Students' Reasoning about Acid-Base Reactions

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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…

Research of Uncertainty Reasoning in Pineapple Disease Identification System

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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.

Strategic reasoning and bargaining in catastrophic climate change games

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Verendel, Vilhelm; Johansson, Daniel J. A.; Lindgren, Kristian

2016-03-01

Two decades of international negotiations show that agreeing on emission levels for climate change mitigation is a hard challenge. However, if early warning signals were to show an upcoming tipping point with catastrophic damage, theory and experiments suggest this could simplify collective action to reduce greenhouse gas emissions. At the actual threshold, no country would have a free-ride incentive to increase emissions over the tipping point, but it remains for countries to negotiate their emission levels to reach these agreements. We model agents bargaining for emission levels using strategic reasoning to predict emission bids by others and ask how this affects the possibility of reaching agreements that avoid catastrophic damage. It is known that policy elites often use a higher degree of strategic reasoning, and in our model this increases the risk for climate catastrophe. Moreover, some forms of higher strategic reasoning make agreements to reduce greenhouse gases unstable. We use empirically informed levels of strategic reasoning when simulating the model.

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.

Comprehensive Care For Joint Replacement Model - Provider Data

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U.S. Department of Health & Human Services — Comprehensive Care for Joint Replacement Model - provider data. This data set includes provider data for two quality measures tracked during an episode of care:...

H2RM: A Hybrid Rough Set Reasoning Model for Prediction and Management of Diabetes Mellitus

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Rahman Ali

2015-07-01

Full Text Available Diabetes is a chronic disease characterized by high blood glucose level that results either from a deficiency of insulin produced by the body, or the body’s resistance to the effects of insulin. Accurate and precise reasoning and prediction models greatly help physicians to improve diagnosis, prognosis and treatment procedures of different diseases. Though numerous models have been proposed to solve issues of diagnosis and management of diabetes, they have the following drawbacks: (1 restricted one type of diabetes; (2 lack understandability and explanatory power of the techniques and decision; (3 limited either to prediction purpose or management over the structured contents; and (4 lack competence for dimensionality and vagueness of patient’s data. To overcome these issues, this paper proposes a novel hybrid rough set reasoning model (H2RM that resolves problems of inaccurate prediction and management of type-1 diabetes mellitus (T1DM and type-2 diabetes mellitus (T2DM. For verification of the proposed model, experimental data from fifty patients, acquired from a local hospital in semi-structured format, is used. First, the data is transformed into structured format and then used for mining prediction rules. Rough set theory (RST based techniques and algorithms are used to mine the prediction rules. During the online execution phase of the model, these rules are used to predict T1DM and T2DM for new patients. Furthermore, the proposed model assists physicians to manage diabetes using knowledge extracted from online diabetes guidelines. Correlation-based trend analysis techniques are used to manage diabetic observations. Experimental results demonstrate that the proposed model outperforms the existing methods with 95.9% average and balanced accuracies.

H2RM: A Hybrid Rough Set Reasoning Model for Prediction and Management of Diabetes Mellitus.

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Ali, Rahman; Hussain, Jamil; Siddiqi, Muhammad Hameed; Hussain, Maqbool; Lee, Sungyoung

2015-07-03

Diabetes is a chronic disease characterized by high blood glucose level that results either from a deficiency of insulin produced by the body, or the body's resistance to the effects of insulin. Accurate and precise reasoning and prediction models greatly help physicians to improve diagnosis, prognosis and treatment procedures of different diseases. Though numerous models have been proposed to solve issues of diagnosis and management of diabetes, they have the following drawbacks: (1) restricted one type of diabetes; (2) lack understandability and explanatory power of the techniques and decision; (3) limited either to prediction purpose or management over the structured contents; and (4) lack competence for dimensionality and vagueness of patient's data. To overcome these issues, this paper proposes a novel hybrid rough set reasoning model (H2RM) that resolves problems of inaccurate prediction and management of type-1 diabetes mellitus (T1DM) and type-2 diabetes mellitus (T2DM). For verification of the proposed model, experimental data from fifty patients, acquired from a local hospital in semi-structured format, is used. First, the data is transformed into structured format and then used for mining prediction rules. Rough set theory (RST) based techniques and algorithms are used to mine the prediction rules. During the online execution phase of the model, these rules are used to predict T1DM and T2DM for new patients. Furthermore, the proposed model assists physicians to manage diabetes using knowledge extracted from online diabetes guidelines. Correlation-based trend analysis techniques are used to manage diabetic observations. Experimental results demonstrate that the proposed model outperforms the existing methods with 95.9% average and balanced accuracies.

Young Children's Reasoning About Physical & Behavioural Family Resemblance: Is There a Place for a Precursor Model of Inheritance?

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Ergazaki, Marida; Alexaki, Aspa; Papadopoulou, Chrysa; Kalpakiori, Marieleni

2014-02-01

This paper aims at exploring (a) whether preschoolers recognize that offspring share physical traits with their parents due to birth and behavioural ones due to nurture, and (b) whether they seem ready to explain shared physical traits with a `pre-biological' causal model that includes the contribution of both parents and a rudimentary notion of genes. This exploration is supposed to provide evidence for our next step, which is the development of an early years' learning environment about inheritance. Conducting individual, semi-structured interviews with 90 preschoolers (age 4.5-5.5) of four public kindergartens in Patras, we attempted to trace their reasoning about (a) whether and why offspring share physical and behavioural traits with parents and (b) which mechanism could better explain the shared physical traits. The probes were a modified six-case version of Solomon et al. (Child Dev 67:151-171, 1996) `adoption task, as well as a three-case task based on Springer's (Child Dev 66:547-558, 1995) `mechanism task' and on Solomon and Johnson's (Br J Dev Psychol 18(1):81-96, 2000) idea of genes as a `conceptual placeholder'. The qualitative and quantitative analysis of the interviews showed overlapping reasoning about the origin of physical and behavioural family resemblance. Nevertheless, we did trace the `birth-driven' argument for the attribution of the offspring's physical traits to the biological parents, as well as a preference for the `pre-biological' model that introduces a rudimentary idea of genes in order to explain shared physical traits between parents and offspring. The findings of the study and the educational implications are thoroughly discussed.

Quantitative Reasoning in Environmental Science: A Learning Progression

Science.gov (United States)

Mayes, Robert Lee; Forrester, Jennifer Harris; Christus, Jennifer Schuttlefield; Peterson, Franziska Isabel; Bonilla, Rachel; Yestness, Nissa

2014-01-01

The ability of middle and high school students to reason quantitatively within the context of environmental science was investigated. A quantitative reasoning (QR) learning progression was created with three progress variables: quantification act, quantitative interpretation, and quantitative modeling. An iterative research design was used as it…

Fair and Reasonable Rate Calculation Data -

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Department of Transportation — This dataset provides guidelines for calculating the fair and reasonable rates for U.S. flag vessels carrying preference cargoes subject to regulations contained at...

Midwives׳ clinical reasoning during second stage labour: Report on an interpretive study.

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Jefford, Elaine; Fahy, Kathleen

2015-05-01

clinical reasoning was once thought to be the exclusive domain of medicine - setting it apart from 'non-scientific' occupations like midwifery. Poor assessment, clinical reasoning and decision-making skills are well known contributors to adverse outcomes in maternity care. Midwifery decision-making models share a common deficit: they are insufficiently detailed to guide reasoning processes for midwives in practice. For these reasons we wanted to explore if midwives actively engaged in clinical reasoning processes within their clinical practice and if so to what extent. The study was conducted using post structural, feminist methodology. to what extent do midwives engage in clinical reasoning processes when making decisions in the second stage labour? twenty-six practising midwives were interviewed. Feminist interpretive analysis was conducted by two researchers guided by the steps of a model of clinical reasoning process. Six narratives were excluded from analysis because they did not sufficiently address the research question. The midwives narratives were prepared via data reduction. A theoretically informed analysis and interpretation was conducted. using a feminist, interpretive approach we created a model of midwifery clinical reasoning grounded in the literature and consistent with the data. Thirteen of the 20 participant narratives demonstrate analytical clinical reasoning abilities but only nine completed the process and implemented the decision. Seven midwives used non-analytical decision-making without adequately checking against assessment data. over half of the participants demonstrated the ability to use clinical reasoning skills. Less than half of the midwives demonstrated clinical reasoning as their way of making decisions. The new model of Midwifery Clinical Reasoning includes 'intuition' as a valued way of knowing. Using intuition, however, should not replace clinical reasoning which promotes through decision-making can be made transparent and be

An experimental investigation of emotional reasoning processes in depression.

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Berle, David; Moulds, Michelle L

2013-09-01

Cognitive models of depression emphasize how distorted thoughts and interpretations contribute to low mood. Emotional reasoning is considered to be one such interpretative style. We used an experimental procedure to determine whether elevated levels of emotional reasoning characterize depression. Participants who were currently experiencing a major depressive episode (n = 27) were compared with those who were non-depressed (n = 25 who had never been depressed and n = 26 previously but not currently depressed) on an emotional reasoning task. Although there were some trends for depressed participants to show greater levels of emotional reasoning relative to non-depressed participants, none of these differences attained significance. Interestingly, previously depressed participants engaged in more non-self-referent emotional reasoning than never-depressed participants. Emotional reasoning does not appear to characterize mild to moderate levels of depression. The lack of significant differences in emotional reasoning between currently depressed and non-depressed participants may have been a consequence of the fact that participants in our currently depressed group were, for the most part, only mildly depressed. Non-self-referent emotional reasoning may nevertheless be a risk factor for subsequent depressive episodes, or else serve as a 'cognitive scar' from previous episodes. In contrast with the predictions of cognitive models of depression, emotional reasoning tendencies may not be especially prominent in currently depressed individuals. Depressed individuals vary greatly in the degree to which they engage in emotional reasoning. Individuals with remitted depression may show elevated of levels non-self-referent emotional reasoning compared with those who have never had a depressive episode, that is, rely on their emotions when forming interpretations about situations. Our findings require replication using alternative indices of emotional reasoning. Our currently

Rule-Based and Case-Based Reasoning in Housing Prices

OpenAIRE

Gabrielle Gayer; Itzhak Gilboa; Offer Lieberman

2004-01-01

People reason about real-estate prices both in terms of general rules and in terms of analogies to similar cases. We propose to empirically test which mode of reasoning fits the data better. To this end, we develop the statistical techniques required for the estimation of the case-based model. It is hypothesized that case-based reasoning will have relatively more explanatory power in databases of rental apartments, whereas rule-based reasoning will have a relative advantage in sales data. We ...

STOCHASTIC AND GEOMETRIC REASONING FOR INDOOR BUILDING MODELS WITH ELECTRIC INSTALLATIONS – BRIDGING THE GAP BETWEEN GIS AND BIM

Directory of Open Access Journals (Sweden)

Y. Dehbi

2017-10-01

Full Text Available 3D city and building models according to CityGML encode the geometry, represent the structure and model semantically relevant building parts such as doors, windows and balconies. Building information models support the building design, construction and the facility management. In contrast to CityGML, they include also objects which cannot be observed from the outside. The three dimensional indoor models characterize a missing link between both worlds. Their derivation, however, is expensive. The semantic automatic interpretation of 3D point clouds of indoor environments is a methodically demanding task. The data acquisition is costly and difficult. The laser scanners and image-based methods require the access to every room. Based on an approach which does not require an additional geometry acquisition of building indoors, we propose an attempt for filling the gaps between 3D building models and building information models. Based on sparse observations such as the building footprint and room areas, 3D indoor models are generated using combinatorial and stochastic reasoning. The derived models are expanded by a-priori not observable structures such as electric installation. Gaussian mixtures, linear and bi-linear constraints are used to represent the background knowledge and structural regularities. The derivation of hypothesised models is performed by stochastic reasoning using graphical models, Gauss-Markov models and MAP-estimators.

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 Teacher Competency Enhancement Model based on the Coaching Processes to Increase Mathematical Reasoning Abilities of Lower-Secondary Students

Directory of Open Access Journals (Sweden)

Uaychai Sukanalam

2017-09-01

Full Text Available This research study aimed to: 1 investigate problems and needs for the learning management that helps increase capacities of mathematics teachers at the lower-secondary level, 2 develop a teacher competency enhancement model based on the coaching processes to enhance mathematical reasoning abilities of lower-secondary students, 3 find out the educational supervisors’ opinions on the model designed. The samples of the study comprised 212 mathematics teachers at the lower-secondary level from 60 schools under jurisdiction of the Office of Secondary Educational Service Area 27, who were selected through the simple random sampling technique ; and 201 educational supervisors in charge of the mathematics learning strand from 42 educational service areas, who were selected through the purposive sampling technique. This study was conducted in the academic year 2015. The research instruments included: 1 a teacher competency enhancement manual that illustrated the steps and procedures for increasing the teacher’s capacities based on the coaching processes in order to enhance mathematical reasoning abilities of lower-secondary students, 2 a survey on problems and needs for the learning management to enhance capacities of mathematics teachers at the lower-secondary level, 3 A questionnaire concerning the educational supervisor’s opinion on the model designed. The statistics used included percentage, mean, and standard deviation. The study results showed that: 1. According to the study and analysis of basic data, problems and needs, it was found that the needs for increasing capacities of mathematics teachers at the lower-secondary level was overall at the high level. In terms of identifying behaviors as “mathematical competencies”, there were some problems associated with thinking and reasoning abilities of the teachers, and their needs in developing the learning management were at the highest level. To solve such problems, it is suggested that

Fluid reasoning and the developing brain

Directory of Open Access Journals (Sweden)

Emilio Ferrer

2009-05-01

Full Text Available Fluid reasoning is a cornerstone of human cognition, both during development and in adulthood. In spite of this, the neural mechanisms underlying the development of fluid reasoning are largely unknown. Here we provide an overview of this important cognitive ability, how it is measured, how it changes over childhood and adolescence, and what is known about its neurobiological underpinnings. We review important findings from the psychometric, cognitive, and neuroscientific literatures, and outline important future directions for this interdisciplinary research.

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.

Operator support and diagnostic reasoning in an industrial process

Energy Technology Data Exchange (ETDEWEB)

Aaker, O.

1996-12-31

Efficient use of energy in production plants requires that the various processes are well controlled. The main focus of this doctoral thesis is on detection of errors and malfunctions using analytical redundancy and on state estimation using an open loop nonlinear model. A ``residual`` is present if a system does not behave as expected, or if a certain rule is violated. ``Reasoning`` is the action of finding process malfunctions based on observed residuals. The thesis applies a new formalism for comparing diagnostic reasoning methods both in terms of what knowledge is used and how it is used, and suggests a formal model of what is known about the process. The formalism is used to illustrate the difference between diagnostic reasoning based on physically interconnected process units and streams, and reasoning about goals and functions for finding a diagnosis. As an example of application, results and experiences from a test implementation using an open loop model for operator support in a complex fertilizer factory are reported. 108 refs., 61 figs., 37 tabs.

Theories of reasoned action and planned behavior as models of condom use: a meta-analysis.

Science.gov (United States)

Albarracín, D; Johnson, B T; Fishbein, M; Muellerleile, P A

2001-01-01

To examine how well the theories of reasoned action and planned behavior predict condom use, the authors synthesized 96 data sets (N = 22,594) containing associations between the models' key variables. Consistent with the theory of reasoned action's predictions, (a) condom use was related to intentions (weighted mean r. = .45), (b) intentions were based on attitudes (r. = .58) and subjective norms (r. = .39), and (c) attitudes were associated with behavioral beliefs (r. = .56) and norms were associated with normative beliefs (r. = .46). Consistent with the theory of planned behavior's predictions, perceived behavioral control was related to condom use intentions (r. = .45) and condom use (r. = .25), but in contrast to the theory, it did not contribute significantly to condom use. The strength of these associations, however, was influenced by the consideration of past behavior. Implications of these results for HIV prevention efforts are discussed.

REASON for Europa

Science.gov (United States)

Moussessian, A.; Blankenship, D. D.; Plaut, J. J.; Patterson, G. W.; Gim, Y.; Schroeder, D. M.; Soderlund, K. M.; Grima, C.; Young, D. A.; Chapin, E.

2015-12-01

The science goal of the Europa multiple flyby mission is to "explore Europa to investigate its habitability". One of the primary instruments selected for the scientific payload is a multi-frequency, multi-channel ice penetrating radar system. This "Radar for Europa Assessment and Sounding: Ocean to Near-surface (REASON)" would revolutionize our understanding of Europa's ice shell by providing the first direct measurements of its surface character and subsurface structure. REASON addresses key questions regarding Europa's habitability, including the existence of any liquid water, through the innovative use of radar sounding, altimetry, reflectometry, and plasma/particles analyses. These investigations require a dual-frequency radar (HF and VHF frequencies) instrument with concurrent shallow and deep sounding that is designed for performance robustness in the challenging environment of Europa. The flyby-centric mission configuration is an opportunity to collect and transmit minimally processed data back to Earth and exploit advanced processing approaches developed for terrestrial airborne data sets. The observation and characterization of subsurface features beneath Europa's chaotic surface require discriminating abundant surface clutter from a relatively weak subsurface signal. Finally, the mission plan also includes using REASON as a nadir altimeter capable of measuring tides to test ice shell and ocean hypotheses as well as characterizing roughness across the surface statistically to identify potential follow-on landing sites. We will present a variety of measurement concepts for addressing these challenges.

Knowledge engineering tools for reasoning with scientific observations and interpretations: a neural connectivity use case.

Science.gov (United States)

Russ, Thomas A; Ramakrishnan, Cartic; Hovy, Eduard H; Bota, Mihail; Burns, Gully A P C

2011-08-22

We address the goal of curating observations from published experiments in a generalizable form; reasoning over these observations to generate interpretations and then querying this interpreted knowledge to supply the supporting evidence. We present web-application software as part of the 'BioScholar' project (R01-GM083871) that fully instantiates this process for a well-defined domain: using tract-tracing experiments to study the neural connectivity of the rat brain. The main contribution of this work is to provide the first instantiation of a knowledge representation for experimental observations called 'Knowledge Engineering from Experimental Design' (KEfED) based on experimental variables and their interdependencies. The software has three parts: (a) the KEfED model editor - a design editor for creating KEfED models by drawing a flow diagram of an experimental protocol; (b) the KEfED data interface - a spreadsheet-like tool that permits users to enter experimental data pertaining to a specific model; (c) a 'neural connection matrix' interface that presents neural connectivity as a table of ordinal connection strengths representing the interpretations of tract-tracing data. This tool also allows the user to view experimental evidence pertaining to a specific connection. BioScholar is built in Flex 3.5. It uses Persevere (a noSQL database) as a flexible data store and PowerLoom® (a mature First Order Logic reasoning system) to execute queries using spatial reasoning over the BAMS neuroanatomical ontology. We first introduce the KEfED approach as a general approach and describe its possible role as a way of introducing structured reasoning into models of argumentation within new models of scientific publication. We then describe the design and implementation of our example application: the BioScholar software. This is presented as a possible biocuration interface and supplementary reasoning toolkit for a larger, more specialized bioinformatics system: the Brain

Application of qualitative reasoning with functional knowledge represented by Multilevel Flow Modeling to diagnosis of accidental situation in nuclear power plant

International Nuclear Information System (INIS)

Yoshida, Kazuo; Tanabe, Fumiya; Kawase, Katumi.

1996-01-01

It has been proposed to use the Multilevel Flow Modeling (MFM) by M. Lind as a framework for functional knowledge representation for qualitative reasoning in a complex process system such as nuclear power plant. To build a knowledge base with MFM framework makes it possible to represent functional characteristics in different levels of abstraction and aggregation. A pilot inference system based on the qualitative reasoning with MFM has been developed to diagnose a cause of abnormal events in a typical PWR power plant. Some single failure events has been diagnosed with this system to verify the proposed method. In the verification study, some investigation has been also performed to clarify the effects of this knowledge representation in efficiency of reasoning and ambiguity of qualitative reasoning. (author)

Everyday life reasoning, possible worlds and cultural processes.

Science.gov (United States)

Smorti, Andrea

2008-06-01

Discussing Faiciuc's paper, I first tackle the problem of fallacies in deductive reasoning showing how, in a possible world theory, non correct forms of reasoning can be useful strategies for discovery, providing these strategies remain at a hypothesis level. Secondly, everyday reasoning and its specificity in comparison to logical-normative one are analyzed. This topic stresses the notion of interpretation and, in this context, the role of the community and of cultural canons shared by the subject. From this point of view, reasoning does not occur, only, in the brain of a person but in everyday exchanges occurring between individuals and the history of their community.

Relating derived relations as a model of analogical reasoning: reaction times and event-related potentials.

Science.gov (United States)

Barnes-Holmes, Dermot; Regan, Donal; Barnes-Holmes, Yvonne; Commins, Sean; Walsh, Derek; Stewart, Ian; Smeets, Paul M; Whelan, Robert; Dymond, Simon

2005-11-01

The current study aimed to test a Relational Frame Theory (RFT) model of analogical reasoning based on the relating of derived same and derived difference relations. Experiment 1 recorded reaction time measures of similar-similar (e.g., "apple is to orange as dog is to cat") versus different-different (e.g., "he is to his brother as chalk is to cheese") derived relational responding, in both speed-contingent and speed-noncontingent conditions. Experiment 2 examined the event-related potentials (ERPs) associated with these two response patterns. Both experiments showed similar-similar responding to be significantly faster than different-different responding. Experiment 2 revealed significant differences between the waveforms of the two response patterns in the left-hemispheric prefrontal regions; different-different waveforms were significantly more negative than similar-similar waveforms. The behavioral and neurophysiological data support the RFT prediction that, all things being equal, similar-similar responding is relationally "simpler" than, and functionally distinct from, different-different analogical responding. The ERP data were fully consistent with findings in the neurocognitive literature on analogy. These findings strengthen the validity of the RFT model of analogical reasoning and supplement the behavior-analytic approach to analogy based on the relating of derived relations.

Development of Model for Providing Feasible Scholarship

Directory of Open Access Journals (Sweden)

Harry Dhika

2016-05-01

Full Text Available The current work focuses on the development of a model to determine a feasible scholarship recipient on the basis of the naiv¨e Bayes’ method using very simple and limited attributes. Those attributes are the applicants academic year, represented by their semester, academic performance, represented by their GPa, socioeconomic ability, which represented the economic capability to attend a higher education institution, and their level of social involvement. To establish and evaluate the model performance, empirical data are collected, and the data of 100 students are divided into 80 student data for the model training and the remaining of 20 student data are for the model testing. The results suggest that the model is capable to provide recommendations for the potential scholarship recipient at the level of accuracy of 95%.

Quantitative Reasoning in Problem Solving

Science.gov (United States)

Ramful, Ajay; Ho, Siew Yin

2015-01-01

In this article, Ajay Ramful and Siew Yin Ho explain the meaning of quantitative reasoning, describing how it is used in the to solve mathematical problems. They also describe a diagrammatic approach to represent relationships among quantities and provide examples of problems and their solutions.

Development of the Statistical Reasoning in Biology Concept Inventory (SRBCI).

Science.gov (United States)

Deane, Thomas; Nomme, Kathy; Jeffery, Erica; Pollock, Carol; Birol, Gülnur

2016-01-01

We followed established best practices in concept inventory design and developed a 12-item inventory to assess student ability in statistical reasoning in biology (Statistical Reasoning in Biology Concept Inventory [SRBCI]). It is important to assess student thinking in this conceptual area, because it is a fundamental requirement of being statistically literate and associated skills are needed in almost all walks of life. Despite this, previous work shows that non-expert-like thinking in statistical reasoning is common, even after instruction. As science educators, our goal should be to move students along a novice-to-expert spectrum, which could be achieved with growing experience in statistical reasoning. We used item response theory analyses (the one-parameter Rasch model and associated analyses) to assess responses gathered from biology students in two populations at a large research university in Canada in order to test SRBCI's robustness and sensitivity in capturing useful data relating to the students' conceptual ability in statistical reasoning. Our analyses indicated that SRBCI is a unidimensional construct, with items that vary widely in difficulty and provide useful information about such student ability. SRBCI should be useful as a diagnostic tool in a variety of biology settings and as a means of measuring the success of teaching interventions designed to improve statistical reasoning skills. © 2016 T. Deane et al. CBE—Life Sciences Education © 2016 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).

Understanding Predisposition in College Choice: Toward an Integrated Model of College Choice and Theory of Reasoned Action

Science.gov (United States)

Pitre, Paul E.; Johnson, Todd E.; Pitre, Charisse Cowan

2006-01-01

This article seeks to improve traditional models of college choice that draw from recruitment and enrollment management paradigms. In adopting a consumer approach to college choice, this article seeks to build upon consumer-related research, which centers on behavior and reasoning. More specifically, this article seeks to move inquiry beyond the…

Neural correlates of depth of strategic reasoning in medial prefrontal cortex

Science.gov (United States)

Coricelli, Giorgio; Nagel, Rosemarie

2009-01-01

We used functional MRI (fMRI) to investigate human mental processes in a competitive interactive setting—the “beauty contest” game. This game is well-suited for investigating whether and how a player's mental processing incorporates the thinking process of others in strategic reasoning. We apply a cognitive hierarchy model to classify subject's choices in the experimental game according to the degree of strategic reasoning so that we can identify the neural substrates of different levels of strategizing. According to this model, high-level reasoners expect the others to behave strategically, whereas low-level reasoners choose based on the expectation that others will choose randomly. The data show that high-level reasoning and a measure of strategic IQ (related to winning in the game) correlate with the neural activity in the medial prefrontal cortex, demonstrating its crucial role in successful mentalizing. This supports a cognitive hierarchy model of human brain and behavior. PMID:19470476

A Framework for Assessing High School Students' Statistical Reasoning.

Science.gov (United States)

Chan, Shiau Wei; Ismail, Zaleha; Sumintono, Bambang

2016-01-01

Based on a synthesis of literature, earlier studies, analyses and observations on high school students, this study developed an initial framework for assessing students' statistical reasoning about descriptive statistics. Framework descriptors were established across five levels of statistical reasoning and four key constructs. The former consisted of idiosyncratic reasoning, verbal reasoning, transitional reasoning, procedural reasoning, and integrated process reasoning. The latter include describing data, organizing and reducing data, representing data, and analyzing and interpreting data. In contrast to earlier studies, this initial framework formulated a complete and coherent statistical reasoning framework. A statistical reasoning assessment tool was then constructed from this initial framework. The tool was administered to 10 tenth-grade students in a task-based interview. The initial framework was refined, and the statistical reasoning assessment tool was revised. The ten students then participated in the second task-based interview, and the data obtained were used to validate the framework. The findings showed that the students' statistical reasoning levels were consistent across the four constructs, and this result confirmed the framework's cohesion. Developed to contribute to statistics education, this newly developed statistical reasoning framework provides a guide for planning learning goals and designing instruction and assessments.

Proof in Algebra: Reasoning beyond Examples

Science.gov (United States)

Otten, Samuel; Herbel-Eisenmann, Beth A.; Males, Lorraine M.

2010-01-01

The purpose of this article is to provide an image of what proof could look like in beginning algebra, a course that nearly every secondary school student encounters. The authors present an actual classroom vignette in which a rich opportunity for student reasoning arose. After analyzing the proof schemes at play, the authors provide a…

Information processing systems, reasoning modules, and reasoning system design methods

Science.gov (United States)

Hohimer, Ryan E; Greitzer, Frank L; Hampton, Shawn D

2014-03-04

Information processing systems, reasoning modules, and reasoning system design methods are described. According to one aspect, an information processing system includes working memory comprising a semantic graph which comprises a plurality of abstractions, wherein the abstractions individually include an individual which is defined according to an ontology and a reasoning system comprising a plurality of reasoning modules which are configured to process different abstractions of the semantic graph, wherein a first of the reasoning modules is configured to process a plurality of abstractions which include individuals of a first classification type of the ontology and a second of the reasoning modules is configured to process a plurality of abstractions which include individuals of a second classification type of the ontology, wherein the first and second classification types are different.

Information processing systems, reasoning modules, and reasoning system design methods

Energy Technology Data Exchange (ETDEWEB)

Hohimer, Ryan E.; Greitzer, Frank L.; Hampton, Shawn D.

2016-08-23

Information processing systems, reasoning modules, and reasoning system design methods are described. According to one aspect, an information processing system includes working memory comprising a semantic graph which comprises a plurality of abstractions, wherein the abstractions individually include an individual which is defined according to an ontology and a reasoning system comprising a plurality of reasoning modules which are configured to process different abstractions of the semantic graph, wherein a first of the reasoning modules is configured to process a plurality of abstractions which include individuals of a first classification type of the ontology and a second of the reasoning modules is configured to process a plurality of abstractions which include individuals of a second classification type of the ontology, wherein the first and second classification types are different.

Information processing systems, reasoning modules, and reasoning system design methods

Energy Technology Data Exchange (ETDEWEB)

Hohimer, Ryan E.; Greitzer, Frank L.; Hampton, Shawn D.

2015-08-18

Information processing systems, reasoning modules, and reasoning system design methods are described. According to one aspect, an information processing system includes working memory comprising a semantic graph which comprises a plurality of abstractions, wherein the abstractions individually include an individual which is defined according to an ontology and a reasoning system comprising a plurality of reasoning modules which are configured to process different abstractions of the semantic graph, wherein a first of the reasoning modules is configured to process a plurality of abstractions which include individuals of a first classification type of the ontology and a second of the reasoning modules is configured to process a plurality of abstractions which include individuals of a second classification type of the ontology, wherein the first and second classification types are different.

SAFETY: an integrated clinical reasoning and reflection framework for undergraduate nursing students.

Science.gov (United States)

Hicks Russell, Bedelia; Geist, Melissa J; House Maffett, Jenny

2013-01-01

Nurse educators can no longer focus on imparting to students knowledge that is merely factual and content specific. Activities that provide students with opportunities to apply concepts in real-world scenarios can be powerful tools. Nurse educators should take advantage of student-patient interactions to model clinical reasoning and allow students to practice complex decision making throughout the entire curriculum. In response to this change in nursing education, faculty in a pediatric course designed a reflective clinical reasoning activity based on the SAFETY template, which is derived from the National Council of State Boards of Nursing RN practice analysis. Students were able to prioritize key components of nursing care, as well as integrate practice issues such as delegation, Health Insurance Portability and Accountability Act violations, and questioning the accuracy of orders. SAFETY is proposed as a framework for integration of content knowledge, clinical reasoning, and reflection on authentic professional nursing concerns. Copyright 2012, SLACK Incorporated.

Constructionism and the space of reasons

Science.gov (United States)

Mackrell, Kate; Pratt, Dave

2017-12-01

Constructionism, best known as the framework for action underpinning Seymour Papert's work with Logo, has stressed the importance of engaging students in creating their own products. Noss and Hoyles have argued that such activity enables students to participate increasingly in a web of connections to further their activity. Ainley and Pratt have elaborated that learning is best facilitated when the student is engaged in a purposeful activity that leads to appreciation of the power of mathematical ideas. Constructionism gives prominence to how the learner's logical reasoning and emotion-driven reasons for engagement are inseparable. We argue that the dependence of constructionism upon the orienting framework of constructivism fails to provide sufficient theoretical underpinning for these ideas. We therefore propose an alternative orienting framework, in which learning takes place through initiation into the space of reasons, such that a person's thoughts, actions and feelings are increasingly open to critique and justification. We argue that knowing as responsiveness to reasons encompasses not only the powerful ideas of mathematics and disciplinary knowledge of modes of enquiry but also the extralogical, such as in feelings of the aesthetic, control, excitement, elegance and efficiency. We discuss the implication that mathematics educators deeply consider the learner's reasons for purposeful activity and design settings in which these reasons can be made public and open to critique.

Predicting Condom Use: A Comparison of the Theory of Reasoned Action, the Theory of Planned Behavior and an Extended Model of TPB

Directory of Open Access Journals (Sweden)

Alexandra Isabel Cabral da Silva Gomes

2018-01-01

Full Text Available ABSTRACT It was our goal to give a contribution to the prediction of condom use using socio-cognitive models, comparing classic theories to an extended model. A cross-sectional study was conducted using a questionnaire of self-reported measures. From the students who agreed to participate in the study, 140 were eligible for the full study. A confirmatory analysis was used to assess the predictive value of the researched model. The model tested had slightly better fit indexes and predictive value than classic Theories of Reasoned Action and Planned Behaviour. Although the results found, discussion continues to understand the gap between intention and behaviour, as further investigation is necessary to fully understand the reasons for condom use inconsistency.

Integrated software health management for aerospace guidance, navigation, and control systems: A probabilistic reasoning approach

Science.gov (United States)

Mbaya, Timmy

Embedded Aerospace Systems have to perform safety and mission critical operations in a real-time environment where timing and functional correctness are extremely important. Guidance, Navigation, and Control (GN&C) systems substantially rely on complex software interfacing with hardware in real-time; any faults in software or hardware, or their interaction could result in fatal consequences. Integrated Software Health Management (ISWHM) provides an approach for detection and diagnosis of software failures while the software is in operation. The ISWHM approach is based on probabilistic modeling of software and hardware sensors using a Bayesian network. To meet memory and timing constraints of real-time embedded execution, the Bayesian network is compiled into an Arithmetic Circuit, which is used for on-line monitoring. This type of system monitoring, using an ISWHM, provides automated reasoning capabilities that compute diagnoses in a timely manner when failures occur. This reasoning capability enables time-critical mitigating decisions and relieves the human agent from the time-consuming and arduous task of foraging through a multitude of isolated---and often contradictory---diagnosis data. For the purpose of demonstrating the relevance of ISWHM, modeling and reasoning is performed on a simple simulated aerospace system running on a real-time operating system emulator, the OSEK/Trampoline platform. Models for a small satellite and an F-16 fighter jet GN&C (Guidance, Navigation, and Control) system have been implemented. Analysis of the ISWHM is then performed by injecting faults and analyzing the ISWHM's diagnoses.

The Linear Logistic Test Model (LLTM as the methodological foundation of item generating rules for a new verbal reasoning test

Directory of Open Access Journals (Sweden)

HERBERT POINSTINGL

2009-06-01

Full Text Available Based on the demand for new verbal reasoning tests to enrich psychological test inventory, a pilot version of a new test was analysed: the 'Family Relation Reasoning Test' (FRRT; Poinstingl, Kubinger, Skoda & Schechtner, forthcoming, in which several basic cognitive operations (logical rules have been embedded/implemented. Given family relationships of varying complexity embedded in short stories, testees had to logically conclude the correct relationship between two individuals within a family. Using empirical data, the linear logistic test model (LLTM; Fischer, 1972, a special case of the Rasch model, was used to test the construct validity of the test: The hypothetically assumed basic cognitive operations had to explain the Rasch model's item difficulty parameters. After being shaped in LLTM's matrices of weights ((qij, none of these operations were corroborated by means of the Andersen's Likelihood Ratio Test.

Using AberOWL for fast and scalable reasoning over BioPortal ontologies

KAUST Repository

Slater, Luke

2016-08-08

Background: Reasoning over biomedical ontologies using their OWL semantics has traditionally been a challenging task due to the high theoretical complexity of OWL-based automated reasoning. As a consequence, ontology repositories, as well as most other tools utilizing ontologies, either provide access to ontologies without use of automated reasoning, or limit the number of ontologies for which automated reasoning-based access is provided. Methods: We apply the AberOWL infrastructure to provide automated reasoning-based access to all accessible and consistent ontologies in BioPortal (368 ontologies). We perform an extensive performance evaluation to determine query times, both for queries of different complexity and for queries that are performed in parallel over the ontologies. Results and conclusions: We demonstrate that, with the exception of a few ontologies, even complex and parallel queries can now be answered in milliseconds, therefore allowing automated reasoning to be used on a large scale, to run in parallel, and with rapid response times.

41 CFR Appendix A to Part 60 - 250-Guidelines on a Contractor's Duty To Provide Reasonable Accommodation

Science.gov (United States)

2010-07-01

... modified work schedules. For instance, flexible or adjusted work schedules could benefit special disabled... difficulty performing his or her job. 1. A contractor is required to make reasonable accommodations to the... the skill, experience, education and other job-related selection criteria, and can perform the...

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

Teaching for clinical reasoning - helping students make the conceptual links.

Science.gov (United States)

McMillan, Wendy Jayne

2010-01-01

Dental educators complain that students struggle to apply what they have learnt theoretically in the clinical context. This paper is premised on the assumption that there is a relationship between conceptual thinking and clinical reasoning. The paper provides a theoretical framework for understanding the relationship between conceptual learning and clinical reasoning. A review of current literature is used to explain the way in which conceptual understanding influences clinical reasoning and the transfer of theoretical understandings to the clinical context. The paper argues that the connections made between concepts are what is significant about conceptual understanding. From this point of departure the paper describes teaching strategies that facilitate the kinds of learning opportunities that students need in order to develop conceptual understanding and to be able to transfer knowledge from theoretical to clinical contexts. Along with a variety of teaching strategies, the value of concept maps is discussed. The paper provides a framework for understanding the difficulties that students have in developing conceptual networks appropriate for later clinical reasoning. In explaining how students learn for clinical application, the paper provides a theoretical framework that can inform how dental educators facilitate the conceptual learning, and later clinical reasoning, of their students.

Reasonable assurance and in-situ testing

International Nuclear Information System (INIS)

Rhoderick, J.E.; Nelson, J.W.

1986-01-01

The Department of Energy is currently preparing site characterization plans for sites being considered for the first geologic repository. The site investigations described in these plans will be aimed at providing ''reasonable assurance'' to the Nuclear Regulatory Commission that the performance objectives and criteria specified in 10 CFR Part 60 will be met. The in-situ testing being planned by the DOE for site characterization, and the subsequent testing conducted as part of performance confirmation, reflects how the basis for ''reasonable assurance'' will change through the licensing process

Clinical reasoning as social deliberation

DEFF Research Database (Denmark)

Thorgård, Keld

2014-01-01

In this paper I will challenge the individualistic model of clinical reasoning. I will argue that sometimes clinical practice is rather machine-like, and information is called to mind and weighed, but the clinician is not just calculating how to use particular means to reach fixed ends. Often...

41 CFR Appendix A to Part 60 - 741-Guidelines on a Contractor's Duty To Provide Reasonable Accommodation

Science.gov (United States)

2010-07-01

... disability. Job restructuring may also involve allowing part-time or modified work schedules. For instance, flexible or adjusted work schedules could benefit persons who cannot work a standard schedule because of... having significant difficulty performing his or her job. 1. A contractor is required to make reasonable...

A Framework for a Clinical Reasoning Knowledge Warehouse

DEFF Research Database (Denmark)

Vilstrup Pedersen, Klaus; Boye, Niels

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. This paper presents a framework for a Clinical Reasoning Knowledge Warehouse that combines theories and models from Artificial Intelligence...... 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...

Local Reasoning about Programs that Alter Data Structures

DEFF Research Database (Denmark)

O'Hearn, Peter W.; Reynolds, John Clifton; Yang, Hongseok

2001-01-01

We describe an extension of Hoare's logic for reasoning about programs that alter data structures. We consider a low-level storage model based on a heap with associated lookup, update, allocation and deallocation operations, and unrestricted address arithmetic. The assertion language is based....... Through these and a number of examples we show that the formalism supports local reasoning: A speci-cation and proof can concentrate on only those cells in memory that a program accesses. This paper builds on earlier work by Burstall, Reynolds, Ishtiaq and O'Hearn on reasoning about data structures....

A Reasoned Action Approach to Health Promotion

OpenAIRE

Fishbein, Martin

2008-01-01

This article describes the integrative model of behavioral prediction (IM), the latest formulation of a reasoned action approach. The IM attempts to identify a limited set of variables that can account for a considerable proportion of the variance in any given behavior. More specifically, consistent with the original theory of reasoned action, the IM assumes that intentions are the immediate antecedents of behavior, but in addition, the IM recognizes that environmental factors and skills and ...

Faculty Development for Fostering Clinical Reasoning Skills in Early Medical Students Using a Modified Bayesian Approach.

Science.gov (United States)

Addy, Tracie Marcella; Hafler, Janet; Galerneau, France

2016-01-01

Clinical reasoning is a necessary skill for medical students to acquire in the course of their education, and there is evidence that they can start this process at the undergraduate level. However, physician educators who are experts in their given fields may have difficulty conveying their complex thought processes to students. Providing faculty development that equips educators with tools to teach clinical reasoning may support skill development in early medical students. We provided faculty development on a modified Bayesian method of teaching clinical reasoning to clinician educators who facilitated small-group, case-based workshops with 2nd-year medical students. We interviewed them before and after the module regarding their perceptions on teaching clinical reasoning. We solicited feedback from the students about the effectiveness of the method in developing their clinical reasoning skills. We carried out this project during an institutional curriculum rebuild where clinical reasoning was a defined goal. At the time of the intervention, there was also increased involvement of the Teaching and Learning Center in elevating the status of teaching and learning. There was high overall satisfaction with the faculty development program. Both the faculty and the students described the modified Bayesian approach as effective in fostering the development of clinical reasoning skills. Through this work, we learned how to form a beneficial partnership between a clinician educator and Teaching and Learning Center to promote faculty development on a clinical reasoning teaching method for early medical students. We uncovered challenges faced by both faculty and early learners in this study. We observed that our faculty chose to utilize the method of teaching clinical reasoning in a variety of manners in the classroom. Despite obstacles and differing approaches utilized, we believe that this model can be emulated at other institutions to foster the development of clinical

Activity in the fronto-parietal network indicates numerical inductive reasoning beyond calculation: An fMRI study combined with a cognitive model.

Science.gov (United States)

Liang, Peipeng; Jia, Xiuqin; Taatgen, Niels A; Borst, Jelmer P; Li, Kuncheng

2016-05-19

Numerical inductive reasoning refers to the process of identifying and extrapolating the rule involved in numeric materials. It is associated with calculation, and shares the common activation of the fronto-parietal regions with calculation, which suggests that numerical inductive reasoning may correspond to a general calculation process. However, compared with calculation, rule identification is critical and unique to reasoning. Previous studies have established the central role of the fronto-parietal network for relational integration during rule identification in numerical inductive reasoning. The current question of interest is whether numerical inductive reasoning exclusively corresponds to calculation or operates beyond calculation, and whether it is possible to distinguish between them based on the activity pattern in the fronto-parietal network. To directly address this issue, three types of problems were created: numerical inductive reasoning, calculation, and perceptual judgment. Our results showed that the fronto-parietal network was more active in numerical inductive reasoning which requires more exchanges between intermediate representations and long-term declarative knowledge during rule identification. These results survived even after controlling for the covariates of response time and error rate. A computational cognitive model was developed using the cognitive architecture ACT-R to account for the behavioral results and brain activity in the fronto-parietal network.

Case-based Reasoning in Conflict Negotiation in Concurrent Engineering

Institute of Scientific and Technical Information of China (English)

无

1999-01-01

Case-based reasoning (CBR) is a kind of analogous reasoning that is widely used in artificial intelligence. Conflicts are pervasive in Concurrent Engineering design environment. Conflict negotiation is necessary when conflicts occur. It is difficult to resolve conflicts due to several reasons. An approach to resolving conflicts by case-based reasoning is proposed in this paper. The knowledge representation of conflict negotiation cases, the judgment of case similarity, the retrieval model of cases, the management of case bases, and the process of case-based conflict negotiation are studied. The implementation structure of the Case-based Conflict Solving System (CCSS) is also given.

Using the SEE-SEP Model to Analyze Upper Secondary Students' Use of Supporting Reasons in Arguing Socioscientific Issues

Science.gov (United States)

Christenson, Nina; Chang Rundgren, Shu-Nu; Höglund, Hans-Olof

2012-06-01

To achieve the goal of scientific literacy, the skills of argumentation have been emphasized in science education during the past decades. But the extent to which students can apply scientific knowledge to their argumentation is still unclear. The purpose of this study was to analyse 80 Swedish upper secondary students' informal argumentation on four socioscientific issues (SSIs) to explore students' use of supporting reasons and to what extent students used scientific knowledge in their arguments. Eighty upper secondary students were asked to express their opinions on one SSI topic they chose through written reports. The four SSIs in this study include global warming, genetically modified organisms (GMO), nuclear power, and consumption. To analyse students' supporting reasons from a holistic view, we used the SEE-SEP model, which links the six subject areas of sociology/culture (So), environment (En), economy (Ec), science (Sc), ethics/morality (Et) and policy (Po) connecting with three aspects, knowledge, value and personal experience (KVP). The results showed that students used value to a greater extent (67%) than they did scientific knowledge (27%) for all four SSI topics. According to the SEE-SEP model, the distribution of supporting reasons generated by students differed among the SSI topics. Also, some alternative concepts were disclosed in students' arguments. The implications for research and education are discussed.

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

Representing Causality and Reasoning about Controllability of Multi-level Flow-Systems

DEFF Research Database (Denmark)

Heussen, Kai; Lind, Morten

2010-01-01

Safe operation of complex processes requires that operators maintain situational-awareness even in highly automated environments. Automatic reasoning can support operators as well as the automation system itself to react effectively and appropriately to disturbances. However, knowledge......-based reasoning about control situations remains a challenge due to the entanglement of process and control systems that co-establish the intended causal structure of a process. Due to this entanglement, reasoning about such systems depends on a coherent representation of control and process. This paper explains...... modeling of controlled processes with multilevelflow models and proposes a new framework for modeling causal influence in multilevel flow models on the basis of a flow/potential analogy. The results are illustrated on examples from the domain of electric power systems....

Development of Learning Management Model Based on Constructivist Theory and Reasoning Strategies for Enhancing the Critical Thinking of Secondary Students

Science.gov (United States)

Chaipichit, Dudduan; Jantharajit, Nirat; Chookhampaeng, Sumalee

2015-01-01

The objectives of this research were to study issues around the management of science learning, problems that are encountered, and to develop a learning management model to address those problems. The development of that model and the findings of its study were based on Constructivist Theory and literature on reasoning strategies for enhancing…

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...

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...

Team reasoning and collective rationality: piercing the veil of obviousness.

Science.gov (United States)

Colman, Andrew M; Pulford, Briony D; Rose, Jo

2008-06-01

The experiments reported in our target article provide strong evidence of collective utility maximization, and the findings suggest that team reasoning should now be included among the social value orientations used in cognitive and social psychology. Evidential decision theory offers a possible alternative explanation for our results but fails to predict intuitively compelling strategy choices in simple games with asymmetric team-reasoning outcomes. Although many of our experimental participants evidently used team reasoning, some appear to have ignored the other players' expected strategy choices and used lower-level, nonstrategic forms of reasoning. Standard payoff transformations cannot explain the experimental findings, nor team reasoning in general, without an unrealistic assumption that players invariably reason nonstrategically.

A Pure Logic-Based Approach to Natural Reasoning

NARCIS (Netherlands)

Abzianidze, Lasha

2015-01-01

The paper presents a model for natural reasoning that combines theorem proving techniques with natural logic. The model is a tableau system for a higher-order logic the formulas of which resemble linguistic expressions. A textual entailment system LangPro, an implementation of the model, represents

How Exemplary Inpatient Teaching Physicians Foster Clinical Reasoning.

Science.gov (United States)

Houchens, Nathan; Harrod, Molly; Fowler, Karen E; Moody, Stephanie; Saint, Sanjay

2017-09-01

Clinical reasoning is a crucial component of training in health professions. These cognitive skills are necessary to provide quality care and avoid diagnostic error. Much previous literature has focused on teaching clinical reasoning in nonclinical environments and does not include learner reflections. The authors sought to explore, through multiple perspectives including learners, techniques used by exemplary inpatient clinician-educators for explicitly cultivating clinical reasoning. The authors conducted (2014-2015) a multisite, exploratory qualitative study examining how excellent clinician-educators foster clinical reasoning during general medicine rounds. This was accomplished through interviews of educators, focus group discussions with learners, and direct observations of clinical teaching. The authors reviewed field notes and transcripts using techniques of thematic analysis. Twelve clinician-educators, 57 current learners, and 26 former learners participated in observations and interviews. The techniques and behaviors of educators were categorized into 4 themes, including 1) emphasizing organization and prioritization, 2) accessing prior knowledge, 3) thinking aloud, and 4) analyzing the literature. The findings of this comprehensive study both confirm strategies found in previous literature and provide novel approaches. This is the first study to incorporate the perspectives of learners. Educators' techniques and behaviors, identified through direct observation and supported by reflections from the entire team, can inform best practices for the teaching of clinical reasoning. Copyright © 2017 Elsevier Inc. All rights reserved.

Reasoning about Users' Actions in a Graphical User Interface.

Science.gov (United States)

Virvou, Maria; Kabassi, Katerina

2002-01-01

Describes a graphical user interface called IFM (Intelligent File Manipulator) that provides intelligent help to users. Explains two underlying reasoning mechanisms, one an adaptation of human plausible reasoning and one that performs goal recognition based on the effects of users' commands; and presents results of an empirical study that…

41 CFR Appendix A to Part 60 - 300-Guidelines on a Contractor's Duty To Provide Reasonable Accommodation

Science.gov (United States)

2010-07-01

... allowing part-time or modified work schedules. For instance, flexible or adjusted work schedules could... performing his or her job. 1. A contractor is required to make reasonable accommodations to the known... qualified with respect to that process. One is “otherwise qualified” if he or she is qualified for a job...

[Clinical reasoning in undergraduate nursing education: a scoping review].

Science.gov (United States)

Menezes, Sáskia Sampaio Cipriano de; Corrêa, Consuelo Garcia; Silva, Rita de Cássia Gengo E; Cruz, Diná de Almeida Monteiro Lopes da

2015-12-01

This study aimed at analyzing the current state of knowledge on clinical reasoning in undergraduate nursing education. A systematic scoping review through a search strategy applied to the MEDLINE database, and an analysis of the material recovered by extracting data done by two independent reviewers. The extracted data were analyzed and synthesized in a narrative manner. From the 1380 citations retrieved in the search, 23 were kept for review and their contents were summarized into five categories: 1) the experience of developing critical thinking/clinical reasoning/decision-making process; 2) teaching strategies related to the development of critical thinking/clinical reasoning/decision-making process; 3) measurement of variables related to the critical thinking/clinical reasoning/decision-making process; 4) relationship of variables involved in the critical thinking/clinical reasoning/decision-making process; and 5) theoretical development models of critical thinking/clinical reasoning/decision-making process for students. The biggest challenge for developing knowledge on teaching clinical reasoning seems to be finding consistency between theoretical perspectives on the development of clinical reasoning and methodologies, methods, and procedures in research initiatives in this field.

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.

Is there a reasonable excuse for not providing post-operative analgesia when using animal models of peripheral neuropathic pain for research purposes?

Directory of Open Access Journals (Sweden)

Sara Hestehave

Full Text Available The induction of neuropathic pain-like behaviors in rodents often requires surgical intervention. This engages acute nociceptive signaling events that contribute to pain and stress post-operatively that from a welfare perspective demands peri-operative analgesic treatment. However, a large number of researchers avoid providing such care based largely on anecdotal opinions that it might interfere with model pathophysiology in the longer term.To investigate effects of various peri-operative analgesic regimens encapsulating different mechanisms and duration of action, on the development of post-operative stress/welfare and pain-like behaviors in the Spared Nerve Injury (SNI-model of neuropathic pain.Starting on the day of surgery, male Sprague-Dawley rats were administered either vehicle (s.c., carprofen (5.0mg/kg, s.c., buprenorphine (0.1mg/kg s.c. or 1.0mg/kg p.o. in Nutella®, lidocaine/bupivacaine mixture (local irrigation or a combination of all analgesics, with coverage from a single administration, and up to 72 hours. Post-operative stress and recovery were assessed using welfare parameters, bodyweight, food-consumption, and fecal corticosterone, and hindpaw mechanical allodynia was tested for assessing development of neuropathic pain for 28 days.None of the analgesic regimes compromised the development of mechanical allodynia. Unexpectedly, the combined treatment with 0.1mg/kg s.c. buprenorphine and carprofen for 72 hours and local irrigation with lidocaine/bupivacaine, caused severe adverse effects with peritonitis. This was not observed when the combination included a lower dose of buprenorphine (0.05mg/kg, s.c., or when buprenorphine was administered alone (0.1mg/kg s.c. or 1.0mg/kg p.o. for 72 hours. An elevated rate of wound dehiscence was observed especially in the combined treatment groups, underlining the need for balanced analgesia. Repeated buprenorphine injections had positive effects on body weight the first day after surgery

Others and Imagination in Reasoning and Argumentation: Improving our Critical Creative Capacity

OpenAIRE

Michael D. Baumtrog

2017-01-01

Contemporary argumentation theories highlight the importance of Others for contributing to and critiquing an individual’s reasoning and/or argumentation. Reasoners and arguers are encouraged to interact with imagined constructs such as a community of model interlocutors or universal audience. These model interlocutors are theoretically meant to bring to mind reasons and counter-considerations that may not have been conceived of otherwise so as to improve the overall quality of an instance of ...

Reasoning and Proving Opportunities in Textbooks: A Comparative Analysis

Science.gov (United States)

Hong, Dae S.; Choi, Kyong Mi

2018-01-01

In this study, we analyzed and compared reasoning and proving opportunities in geometry lessons from American standard-based textbooks and Korean textbooks to understand how these textbooks provide student opportunities to engage in reasoning and proving activities. Overall, around 40% of exercise problems in Core Plus Mathematics Project (CPMP)…

Reasoning about plans

CERN Document Server

Allen, James; Pelavin, Richard; Tenenberg, Josh

1991-01-01

This book presents four contributions to planning research within an integrated framework. James Allen offers a survey of his research in the field of temporal reasoning, and then describes a planning system formalized and implemented directly as an inference process in the temporal logic. Starting from the same logic, Henry Kautz develops the first formal specification of the plan recognition process and develops a powerful family of algorithms for plan recognition in complex situations. Richard Pelavin then extends the temporal logic with model operators that allow the representation to

Using Discourse Analysis to Understand Variation in Students' Reasoning from Accepted Ways of Reasoning

Science.gov (United States)

Gruver, John

2017-01-01

In this study, I use a systemic functional linguistics approach to examine mathematics classroom discourse with the aim of providing a plausible explanation of how students could actively participate in productive classroom discussions without adopting ways of reasoning that were accepted in the classroom community. In this way, I work in the…

Pertinent reasoning

CSIR Research Space (South Africa)

Britz, K

2010-05-01

Full Text Available In this paper the authors venture beyond one of the fundamental assumptions in the non-monotonic reasoning community, namely that non-monotonic entailment is supra-classical. They investigate reasoning which uses an infra-classical entailment...

Assessment of Scientific Reasoning: the Effects of Task Context, Data, and Design on Student Reasoning in Control of Variables.

Science.gov (United States)

Zhou, Shaona; Han, Jing; Koenig, Kathleen; Raplinger, Amy; Pi, Yuan; Li, Dan; Xiao, Hua; Fu, Zhao; Bao, Lei

2016-03-01

Scientific reasoning is an important component under the cognitive strand of the 21st century skills and is highly emphasized in the new science education standards. This study focuses on the assessment of student reasoning in control of variables (COV), which is a core sub-skill of scientific reasoning. The main research question is to investigate the extent to which the existence of experimental data in questions impacts student reasoning and performance. This study also explores the effects of task contexts on student reasoning as well as students' abilities to distinguish between testability and causal influences of variables in COV experiments. Data were collected with students from both USA and China. Students received randomly one of two test versions, one with experimental data and one without. The results show that students from both populations (1) perform better when experimental data are not provided, (2) perform better in physics contexts than in real-life contexts, and (3) students have a tendency to equate non-influential variables to non-testable variables. In addition, based on the analysis of both quantitative and qualitative data, a possible progression of developmental levels of student reasoning in control of variables is proposed, which can be used to inform future development of assessment and instruction.

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.

Reason for hospital admission: a pilot study comparing patient statements with chart reports.

Science.gov (United States)

Berger, Zackary; Dembitzer, Anne; Beach, Mary Catherine

2013-01-01

Providers and patients bring different understandings of health and disease to their encounters in the hospital setting. The literature to date only infrequently addresses patient and provider concordance on the reported reason for hospitalization, that is, whether they express this reason in similar ways. An agreement or common ground between such understandings can serve as a basis for future communication regarding an illness and its treatment. We interviewed a convenience sample of patients on the medical wards of an urban academic medical center. We asked subjects to state the reason why their doctors admitted them to the hospital, and then compared their statement with the reason in the medical record. We defined concordance on reported reason for hospitalization as agreement between the patient's report and the reason abstracted from the chart. We interviewed and abstracted chart data from a total of 46 subjects. Concordance on reported reason for hospitalization was present in 24 (52%) and discordance in 17 (37%); 5 patients (11%) could not give any reason for their hospitalization. Among the 17 patients whose report was discordant with their chart, 12 (71%) reported a different organ system than was recorded in the chart. A significant proportion of medical inpatients could not state their physicians' reason for admission. In addition, patients who identify a different reason for hospitalization than the chart often give a different organ system altogether. Providers should explore patient understanding of the reason for their hospitalization to facilitate communication and shared decision making.

Nash Equilibria in Theory of Reasoned Action

Science.gov (United States)

Almeida, Leando; Cruz, José; Ferreira, Helena; Pinto, Alberto Adrego

2009-08-01

Game theory and Decision Theory have been applied to many different areas such as Physics, Economics, Biology, etc. In its application to Psychology, we introduce, in the literature, a Game Theoretical Model of Planned Behavior or Reasoned Action by establishing an analogy between two specific theories. In this study we take in account that individual decision-making is an outcome of a process where group decisions can determine individual probabilistic behavior. Using Game Theory concepts, we describe how intentions can be transformed in behavior and according to the Nash Equilibrium, this process will correspond to the best individual decision/response taking in account the collective response. This analysis can be extended to several examples based in the Game Theoretical Model of Planned Behavior or Reasoned Action.

Science Thought and Practices: A Professional Development Workshop on Teaching Scientific Reasoning, Mathematical Modeling and Data Analysis

Science.gov (United States)

Robbins, Dennis; Ford, K. E. Saavik

2018-01-01

The NSF-supported “AstroCom NYC” program, a collaboration of the City University of New York and the American Museum of Natural History (AMNH), has developed and offers hands-on workshops to undergraduate faculty on teaching science thought and practices. These professional development workshops emphasize a curriculum and pedagogical strategies that uses computers and other digital devices in a laboratory environment to teach students fundamental topics, including: proportional reasoning, control of variables thinking, experimental design, hypothesis testing, reasoning with data, and drawing conclusions from graphical displays. Topics addressed here are rarely taught in-depth during the formal undergraduate years and are frequently learned only after several apprenticeship research experiences. The goal of these workshops is to provide working and future faculty with an interactive experience in science learning and teaching using modern technological tools.

Reasonable selection of automatic exposure density compensation of ionization chamber

International Nuclear Information System (INIS)

Tian Fuqiang; Nie Shikun; Wang Zhihong; Zeng Jianhua; Cheng Guanxun; Xiang Qian

2000-01-01

Objective: To introduce and discuss the methods of reasonable selection of the automatic exposure density compensation of ionization chamber to provide important references for clinic radiograph and improve the quality of images. Methods: X-ray machines with ionization chamber automatic exposure control system were used in this study. Compared with the standard baseline of the normal density of the object radio-graphed, the reasonable ionization chamber density compensation (IDC) was chosen and compared with the radiograph without IDC through a water model test and density measurement. Results: There was no significant difference between two groups (100 films each) which were randomly divided to the group with or without IDC, but there was statistically significant difference in the special groups. Conclusion: To select suitable IDC is very important for guaranteeing radiographic quality, moreover, to establish a suitable kV is also necessary, usually it is 10 to 20 kV higher than the optioned kV. The relative factors must be fixed relatively and be matched correctly

Reasons why specialist doctors undertake rural outreach services: an Australian cross-sectional study.

Science.gov (United States)

O'Sullivan, Belinda G; McGrail, Matthew R; Stoelwinder, Johannes U

2017-01-07

The purpose of the study is to explore the reasons why specialist doctors travel to provide regular rural outreach services, and whether reasons relate to (1) salaried or private fee-for-service practice and (2) providing rural outreach services in more remote locations. A national cross-sectional study of specialist doctors from the Medicine in Australia: Balancing Employment and Life (MABEL) survey in 2014 was implemented. Specialists providing rural outreach services self-reported on a 5-point scale their level of agreement with five reasons for participating. Chi-squared analysis tested association between agreement and variables of interest. Of 567 specialists undertaking rural outreach services, reasons for participating include to grow the practice (54%), maintain a regional connection (26%), provide complex healthcare (18%), healthcare for disadvantaged people (12%) and support rural staff (6%). Salaried specialists more commonly participated to grow the practice compared with specialists in fee-for-service practice (68 vs 49%). This reason was also related to travelling further and providing outreach services in outer regional/remote locations. Private fee-for-service specialists more commonly undertook outreach services to provide complex healthcare (22 vs 14%). Specialist doctors undertake rural outreach services for a range of reasons, mainly to complement the growth and diversity of their main practice or maintain a regional connection. Structuring rural outreach around the specialist's main practice is likely to support participation and improve service distribution.

Incorporating Quantitative Reasoning in Common Core Courses: Mathematics for The Ghost Map

Directory of Open Access Journals (Sweden)

John R. Jungck

2012-01-01

Full Text Available How can mathematics be integrated into multi-section interdisciplinary courses to enhance thematic understandings and shared common readings? As an example, four forms of quantitative reasoning are used to understand and critique one such common reading: Steven Berlin Johnson’s "The Ghost Map: The Story of London's Most Terrifying Epidemic - and How it Changed Science, Cities and the Modern World" (Riverhead Books, 2006. Geometry, statistics, modeling, and networks are featured in this essay as the means of depicting, understanding, elaborating, and critiquing the public health issues raised in Johnson’s book. Specific pedagogical examples and resources are included to illustrate applications and opportunities for generalization beyond this specific example. Quantitative reasoning provides a robust, yet often neglected, lens for doing literary and historical analyses in interdisciplinary education.

Public Reason Renaturalized

DEFF Research Database (Denmark)

Tønder, Lars

2014-01-01

. The article develops this argument via a sensorial orientation to politics that not only re-frames existing critiques of neo-Kantianism but also includes an alternative, renaturalized conception of public reason, one that allows us to overcome the disconnect between the account we give of reason and the way......This article takes up recent discussions of nature and the sensorium in order to rethink public reason in deeply divided societies. The aim is not to reject the role of reason-giving but rather to infuse it with new meaning, bringing the reasonable back to its sensorially inflected circumstances...... it is mobilized in a world of deep pluralism. The article concludes with a discussion of how a renaturalized conception of public reason might change the positioning of contemporary democratic theory vis-a-vis the struggle for empowerment and pluralization in an age of neo-liberalism and state-surveillance....

Beyond Markov: Accounting for independence violations in causal reasoning.

Science.gov (United States)

Rehder, Bob

2018-06-01

Although many theories of causal cognition are based on causal graphical models, a key property of such models-the independence relations stipulated by the Markov condition-is routinely violated by human reasoners. This article presents three new accounts of those independence violations, accounts that share the assumption that people's understanding of the correlational structure of data generated from a causal graph differs from that stipulated by causal graphical model framework. To distinguish these models, experiments assessed how people reason with causal graphs that are larger than those tested in previous studies. A traditional common cause network (Y 1 ←X→Y 2 ) was extended so that the effects themselves had effects (Z 1 ←Y 1 ←X→Y 2 →Z 2 ). A traditional common effect network (Y 1 →X←Y 2 ) was extended so that the causes themselves had causes (Z 1 →Y 1 →X←Y 2 ←Z 2 ). Subjects' inferences were most consistent with the beta-Q model in which consistent states of the world-those in which variables are either mostly all present or mostly all absent-are viewed as more probable than stipulated by the causal graphical model framework. Substantial variability in subjects' inferences was also observed, with the result that substantial minorities of subjects were best fit by one of the other models (the dual prototype or a leaky gate models). The discrepancy between normative and human causal cognition stipulated by these models is foundational in the sense that they locate the error not in people's causal reasoning but rather in their causal representations. As a result, they are applicable to any cognitive theory grounded in causal graphical models, including theories of analogy, learning, explanation, categorization, decision-making, and counterfactual reasoning. Preliminary evidence that independence violations indeed generalize to other judgment types is presented. Copyright © 2018 Elsevier Inc. All rights reserved.

Defeasibility in Legal Reasoning

OpenAIRE

SARTOR, Giovanni

2009-01-01

I shall first introduce the idea of reasoning, and of defeasible reasoning in particular. I shall then argue that cognitive agents need to engage in defeasible reasoning for coping with a complex and changing environment. Consequently, defeasibility is needed in practical reasoning, and in particular in legal reasoning

Mathematical reasoning in Elementary School and Higher Education

Directory of Open Access Journals (Sweden)

Joana Mata-Pereira

2012-12-01

Full Text Available This paper analyzes the reasoning processes in mathematical tasks of two students in the 9th year of elementary school and two students in the second year of college. It also focuses the representation and meaningfulness, given their close relation with the mathematical reasoning. Results presented are based on two qualitative and interpretive studies which resort to several data sources. These results show that mastering of the algebraic language by the students in the 9th year is still insufficient to promptly solve the problems proposed, which does not occur with the college students though. All students use inductive initial strategies. However, one of the students in the 9th year and both college students revealed clearly their capability to reason deductively. The signification levels vary considerably, and several students have shown skills to build or mobilize relevant meanings. The model of analysis presented, articulating reasoning, representations and meaningfulness proved itself a promising tool to study the students’ reasoning processes.

Knowledge engineering tools for reasoning with scientific observations and interpretations: a neural connectivity use case

Directory of Open Access Journals (Sweden)

Bota Mihail

2011-08-01

Full Text Available Abstract Background We address the goal of curating observations from published experiments in a generalizable form; reasoning over these observations to generate interpretations and then querying this interpreted knowledge to supply the supporting evidence. We present web-application software as part of the 'BioScholar' project (R01-GM083871 that fully instantiates this process for a well-defined domain: using tract-tracing experiments to study the neural connectivity of the rat brain. Results The main contribution of this work is to provide the first instantiation of a knowledge representation for experimental observations called 'Knowledge Engineering from Experimental Design' (KEfED based on experimental variables and their interdependencies. The software has three parts: (a the KEfED model editor - a design editor for creating KEfED models by drawing a flow diagram of an experimental protocol; (b the KEfED data interface - a spreadsheet-like tool that permits users to enter experimental data pertaining to a specific model; (c a 'neural connection matrix' interface that presents neural connectivity as a table of ordinal connection strengths representing the interpretations of tract-tracing data. This tool also allows the user to view experimental evidence pertaining to a specific connection. BioScholar is built in Flex 3.5. It uses Persevere (a noSQL database as a flexible data store and PowerLoom® (a mature First Order Logic reasoning system to execute queries using spatial reasoning over the BAMS neuroanatomical ontology. Conclusions We first introduce the KEfED approach as a general approach and describe its possible role as a way of introducing structured reasoning into models of argumentation within new models of scientific publication. We then describe the design and implementation of our example application: the BioScholar software. This is presented as a possible biocuration interface and supplementary reasoning toolkit for a larger

Knowledge engineering tools for reasoning with scientific observations and interpretations: a neural connectivity use case

Science.gov (United States)

2011-01-01

Background We address the goal of curating observations from published experiments in a generalizable form; reasoning over these observations to generate interpretations and then querying this interpreted knowledge to supply the supporting evidence. We present web-application software as part of the 'BioScholar' project (R01-GM083871) that fully instantiates this process for a well-defined domain: using tract-tracing experiments to study the neural connectivity of the rat brain. Results The main contribution of this work is to provide the first instantiation of a knowledge representation for experimental observations called 'Knowledge Engineering from Experimental Design' (KEfED) based on experimental variables and their interdependencies. The software has three parts: (a) the KEfED model editor - a design editor for creating KEfED models by drawing a flow diagram of an experimental protocol; (b) the KEfED data interface - a spreadsheet-like tool that permits users to enter experimental data pertaining to a specific model; (c) a 'neural connection matrix' interface that presents neural connectivity as a table of ordinal connection strengths representing the interpretations of tract-tracing data. This tool also allows the user to view experimental evidence pertaining to a specific connection. BioScholar is built in Flex 3.5. It uses Persevere (a noSQL database) as a flexible data store and PowerLoom® (a mature First Order Logic reasoning system) to execute queries using spatial reasoning over the BAMS neuroanatomical ontology. Conclusions We first introduce the KEfED approach as a general approach and describe its possible role as a way of introducing structured reasoning into models of argumentation within new models of scientific publication. We then describe the design and implementation of our example application: the BioScholar software. This is presented as a possible biocuration interface and supplementary reasoning toolkit for a larger, more specialized

Varieties of noise: analogical reasoning in synthetic biology.

Science.gov (United States)

Knuuttila, Tarja; Loettgers, Andrea

2014-12-01

The picture of synthetic biology as a kind of engineering science has largely created the public understanding of this novel field, covering both its promises and risks. In this paper, we will argue that the actual situation is more nuanced and complex. Synthetic biology is a highly interdisciplinary field of research located at the interface of physics, chemistry, biology, and computational science. All of these fields provide concepts, metaphors, mathematical tools, and models, which are typically utilized by synthetic biologists by drawing analogies between the different fields of inquiry. We will study analogical reasoning in synthetic biology through the emergence of the functional meaning of noise, which marks an important shift in how engineering concepts are employed in this field. The notion of noise serves also to highlight the differences between the two branches of synthetic biology: the basic science-oriented branch and the engineering-oriented branch, which differ from each other in the way they draw analogies to various other fields of study. Moreover, we show that fixing the mapping between a source domain and the target domain seems not to be the goal of analogical reasoning in actual scientific practice.

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.

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.

A distributed reasoning engine ecosystem for semantic context-management in smart environments.

Science.gov (United States)

Almeida, Aitor; López-de-Ipiña, Diego

2012-01-01

To be able to react adequately a smart environment must be aware of the context and its changes. Modeling the context allows applications to better understand it and to adapt to its changes. In order to do this an appropriate formal representation method is needed. Ontologies have proven themselves to be one of the best tools to do it. Semantic inference provides a powerful framework to reason over the context data. But there are some problems with this approach. The inference over semantic context information can be cumbersome when working with a large amount of data. This situation has become more common in modern smart environments where there are a lot sensors and devices available. In order to tackle this problem we have developed a mechanism to distribute the context reasoning problem into smaller parts in order to reduce the inference time. In this paper we describe a distributed peer-to-peer agent architecture of context consumers and context providers. We explain how this inference sharing process works, partitioning the context information according to the interests of the agents, location and a certainty factor. We also discuss the system architecture, analyzing the negotiation process between the agents. Finally we compare the distributed reasoning with the centralized one, analyzing in which situations is more suitable each approach.

Comparison of reasoners for large ontologies in the OWL 2 EL profile

NARCIS (Netherlands)

Dentler, K.; Cornet, R.; ten Teije, A.C.M.; de Keizer, N.F.

2011-01-01

This paper provides a survey to and a comparison of state-of-the-art Semantic Web reasoners that succeed in classifying large ontologies expressed in the tractable OWL 2 EL profile. Reasoners are characterized along several dimensions: The first dimension comprises underlying reasoning

Inductive and deductive reasoning in obsessive-compulsive disorder.

Science.gov (United States)

Liew, Janice; Grisham, Jessica R; Hayes, Brett K

2018-06-01

This study examined the hypothesis that participants diagnosed with obsessive-compulsive disorder (OCD) show a selective deficit in inductive reasoning but are equivalent to controls in deductive reasoning. Twenty-five participants with OCD and 25 non-clinical controls made inductive and deductive judgments about a common set of arguments that varied in logical validity and the amount of positive evidence provided (premise sample size). A second inductive reasoning task required participants to make forced-choice decisions and rate the usefulness of diverse evidence or non-diverse evidence for evaluating arguments. No differences in deductive reasoning were found between participants diagnosed with OCD and control participants. Both groups saw that the amount of positive evidence supporting a conclusion was an important guide for evaluating inductive arguments. However, those with OCD showed less sensitivity to premise diversity in inductive reasoning than controls. The findings were similar for both emotionally neutral and OCD-relevant stimuli. The absence of a clinical control group means that it is difficult to know whether the deficit in diversity-based reasoning is specific to those with OCD. People with OCD are impaired in some forms of inductive reasoning (using diverse evidence) but not others (use of sample size). Deductive reasoning appears intact in those with OCD. Difficulties using evidence diversity when reasoning inductively may maintain OCD symptoms through reduced generalization of learned safety information. Copyright © 2017 Elsevier Ltd. All rights reserved.

Aspects and modular reasoning in nonmonotonic logic

DEFF Research Database (Denmark)

Ostermann, Klaus

2008-01-01

Nonmonotonic logic is a branch of logic that has been developed to model situations with incomplete information. We argue that there is a connection between AOP and nonmonotonic logic which deserves further study. As a concrete technical contribution and "appetizer", we outline an AO semantics de...... defined in default logic (a form of nonmonotonic logic), propose a definition of modular reasoning, and show that the default logic version of the language semantics admits modular reasoning whereas a conventional language semantics based on weaving does not....

Study of the scientific reasoning methods: Identifying the salient reasoning characteristics exhibited by engineers and scientists in an R&D environment

Science.gov (United States)

Kuhn, William F.

At the core of what it means to be a scientist or engineer is the ability to think rationally using scientific reasoning methods. Yet, typically if asked, scientist and engineers are hard press for a reply what that means. Some may argue that the meaning of scientific reasoning methods is a topic for the philosophers and psychologist, but this study believes and will prove that the answers lie with the scientists and engineers, for who really know the workings of the scientific reasoning thought process than they. This study will provide evidence to the aims: (a) determine the fundamental characteristics of cognitive reasoning methods exhibited by engineer/scientists working in R&D projects, (b) sample the engineer/scientist community to determine their views as to the importance, frequency, and ranking of each of characteristics towards benefiting their R&D projects, (c) make concluding remarks regarding any identified competency gaps in the exhibited or expected cognitive reasoning methods of engineer/scientists working on R&D projects. To drive these aims are the following three research questions. The first, what are the salient characteristics of cognitive reasoning methods exhibited by engineer/scientists in an R&D environment? The second, what do engineer/scientists consider to be the frequency and importance of the salient cognitive reasoning methods characteristics? And the third, to what extent, if at all, do patent holders and technical fellows differ with regard to their perceptions of the importance and frequency of the salient cognitive reasoning characteristics of engineer/scientists? The methodology and empirical approach utilized and described: (a) literature search, (b) Delphi technique composed of seven highly distinguish engineer/scientists, (c) survey instrument directed to distinguish Technical Fellowship, (d) data collection analysis. The results provide by Delphi Team answered the first research question. The collaborative effort validated

Reasoning Abilities and Potential Correlates Among Jordanian School Children.

Science.gov (United States)

Almomani, Fidaa; Al-Momani, Murad O; Alsheyab, Nihayah; Al Mhdawi, Khader

2018-04-01

Objectives To investigate factors related to reasoning skills in 434 school children aged 5-9 years. Methods The Leiter International Performance Scale-Revised was used to assess reasoning skills. Demographic, work and family income data, information on child's daily behavior and school academic achievement were provided by the participating children's parents. Results Reasoning scores increased by 4.56 points with increasing subject's age, 1.71 points with increasing level of father's occupation, 1.86 points with each increase in the subject's GPA, 1.13 points with consumption of breakfast at home and 1.81 points when child slept more hours. Having a father who smoked and living in a rural area decreased scores in reasoning. Conclusions for Practice Screening of reasoning and associated factors is essential for a comprehensive and accurate understanding of the child's abilities and limitations. Understanding the child's reasoning abilities is critical for establishing intervention goals and planning therapeutic activities.

Understanding gender differences in m-health adoption: a modified theory of reasoned action model.

Science.gov (United States)

Zhang, Xiaofei; Guo, Xitong; Lai, Kee-Hung; Guo, Feng; Li, Chenlei

2014-01-01

Mobile health (m-health) services are becoming increasingly popular in healthcare, but research on m-health adoption is rare. This study was designed to obtain a better understanding of m-health adoption intention. We conducted an empirical research of a 481-respondent sample consisting of 44.7% women and 55.3% men and developed a modified theory of reasoned action (TRA) model by incorporating the nonlinearities between attitude and subjective norms and the moderating effect of gender. The results indicate that, based on the study population in China: (1) facilitating conditions, attitude, and subjective norms are significant predictors of m-health adoption intention; (2) the model including the nonlinearities enhances its explanatory ability; (3) males enjoy a higher level of m-health adoption intention compared with females; (4) the modified TRA model can predict men's behavior intention better than that of women; and (5) males have an Edgeworth-Pareto substitutability between attitude and subjective norms in predicting m-health adoption intention. Thus, we found gender differences in m-health adoption from the perspective of social psychology.

The Comparison of Inductive Reasoning under Risk Conditions between Chinese and Japanese Based on Computational Models: Toward the Application to CAE for Foreign Language

Science.gov (United States)

Zhang, Yujie; Terai, Asuka; Nakagawa, Masanori

2013-01-01

Inductive reasoning under risk conditions is an important thinking process not only for sciences but also in our daily life. From this viewpoint, it is very useful for language learning to construct computational models of inductive reasoning which realize the CAE for foreign languages. This study proposes the comparison of inductive reasoning…

Risk of Telemedicine Infeasibility: An Evidential Reasoning Approach

Directory of Open Access Journals (Sweden)

Sofienne Mansouri

2017-10-01

Full Text Available The viability of a telemedicine system is the strength of its business continuity. Business continuity can only stand if the telemedicine system remains continuously feasible. This article studies telemedicine risk in terms of its feasibility on all its five components: economical, technical, social, operational, and legal/ethical. Any deficiencies in one or more of the feasibility components will affect the system business continuity risk and can lead to infeasibility and possible dissolution. The telemedicine computing environment is full of uncertainties and ambiguities and it just involves too much background knowledge that Bayesian theory cannot accommodate. Decision theory however offers a basic evidence-based multi-criteria decision mechanism that can tackle those decision problems treating both quantitative and qualitative criteria under various uncertainties including ignorance and randomness. We propose an evidential reasoning model to assess a telemedicine business continuity risk based on infeasibility. This business continuity risk is modelled using Dempster and Shafer Theory as the plausibility of infeasibility of the telemedicine system. A numerical example is provided to demonstrate the working of the proposed risk assessment model.

Design of Composite Structures Using Knowledge-Based and Case Based Reasoning

Science.gov (United States)

Lambright, Jonathan Paul

1996-01-01

A method of using knowledge based and case based reasoning to assist designers during conceptual design tasks of composite structures was proposed. The cooperative use of heuristics, procedural knowledge, and previous similar design cases suggests a potential reduction in design cycle time and ultimately product lead time. The hypothesis of this work is that the design process of composite structures can be improved by using Case-Based Reasoning (CBR) and Knowledge-Based (KB) reasoning in the early design stages. The technique of using knowledge-based and case-based reasoning facilitates the gathering of disparate information into one location that is easily and readily available. The method suggests that the inclusion of downstream life-cycle issues into the conceptual design phase reduces potential of defective, and sub-optimal composite structures. Three industry experts were interviewed extensively. The experts provided design rules, previous design cases, and test problems. A Knowledge Based Reasoning system was developed using the CLIPS (C Language Interpretive Procedural System) environment and a Case Based Reasoning System was developed using the Design Memory Utility For Sharing Experiences (MUSE) xviii environment. A Design Characteristic State (DCS) was used to document the design specifications, constraints, and problem areas using attribute-value pair relationships. The DCS provided consistent design information between the knowledge base and case base. Results indicated that the use of knowledge based and case based reasoning provided a robust design environment for composite structures. The knowledge base provided design guidance from well defined rules and procedural knowledge. The case base provided suggestions on design and manufacturing techniques based on previous similar designs and warnings of potential problems and pitfalls. The case base complemented the knowledge base and extended the problem solving capability beyond the existence of

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

Science.gov (United States)

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.

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.

Differentiating between precursor and control variables when analyzing reasoned action theories.

Science.gov (United States)

Hennessy, Michael; Bleakley, Amy; Fishbein, Martin; Brown, Larry; Diclemente, Ralph; Romer, Daniel; Valois, Robert; Vanable, Peter A; Carey, Michael P; Salazar, Laura

2010-02-01

This paper highlights the distinction between precursor and control variables in the context of reasoned action theory. Here the theory is combined with structural equation modeling to demonstrate how age and past sexual behavior should be situated in a reasoned action analysis. A two wave longitudinal survey sample of African-American adolescents is analyzed where the target behavior is having vaginal sex. Results differ when age and past behavior are used as control variables and when they are correctly used as precursors. Because control variables do not appear in any form of reasoned action theory, this approach to including background variables is not correct when analyzing data sets based on the theoretical axioms of the Theory of Reasoned Action, the Theory of Planned Behavior, or the Integrative Model.

Abstract analogical reasoning in high-functioning children with autism spectrum disorders.

Science.gov (United States)

Green, Adam E; Kenworthy, Lauren; Mosner, Maya G; Gallagher, Natalie M; Fearon, Edward W; Balhana, Carlos D; Yerys, Benjamin E

2014-12-01

Children with autism spectrum disorders (ASD) exhibit a deficit in spontaneously recognizing abstract similarities that are crucial for generalizing learning to new situations. This may contribute to deficits in the development of appropriate schemas for navigating novel situations, including social interactions. Analogical reasoning is the central cognitive mechanism that enables typically developing children to understand abstract similarities between different situations. Intriguingly, studies of high-functioning children with ASD point to a relative cognitive strength in basic, nonabstract forms of analogical reasoning. If this analogical reasoning ability extends to abstract analogical reasoning (i.e., between superficially dissimilar situations), it may provide a bridge between a cognitive capability and core ASD deficits in areas such as generalization and categorization. This study tested whether preserved analogical reasoning abilities in ASD can be extended to abstract analogical reasoning, using photographs of real-world items and situations. Abstractness of the analogies was determined via a quantitative measure of semantic distance derived from latent semantic analysis. Children with ASD performed as well as typically developing children at identifying abstract analogical similarities when explicitly instructed to apply analogical reasoning. Individual differences in abstract analogical reasoning ability predicted individual differences in a measure of social function in the ASD group. Preliminary analyses indicated that children with ASD, but not typically developing children, showed an effect of age on abstract analogical reasoning. These results provide new evidence that children with ASD are capable of identifying abstract similarities through analogical reasoning, pointing to abstract analogical reasoning as a potential lever for improving generalization skills and social function in ASD. © 2014 International Society for Autism Research, Wiley

Relations as transformations: implications for analogical reasoning.

Science.gov (United States)

Leech, Robert; Mareschal, Denis; Cooper, Richard P

2007-07-01

We present two experiments assessing whether the size of a transformation instantiating a relation between two states of the world (e.g., shrinks) is a performance factor affecting analogical reasoning. The first experiment finds evidence of transformation size as a significant factor in adolescent analogical problem solving while the second experiment finds a similar effect on adult analogical reasoning using a markedly different analogical completion paradigm. The results are interpreted as providing evidence for the more general framework that cognitive representations of relations are best understood as mental transformations.

Qualitative Spatial Reasoning for Visual Grouping in Sketches

National Research Council Canada - National Science Library

Forbus, Kenneth D; Tomai, Emmett; Usher, Jeffrey

2003-01-01

We believe that qualitative spatial reasoning provides a bridge between perception and cognition, by using visual computations to construct structural descriptions that have functional significance...

Teaching clinical reasoning: case-based and coached.

Science.gov (United States)

Kassirer, Jerome P

2010-07-01

Optimal medical care is critically dependent on clinicians' skills to make the right diagnosis and to recommend the most appropriate therapy, and acquiring such reasoning skills is a key requirement at every level of medical education. Teaching clinical reasoning is grounded in several fundamental principles of educational theory. Adult learning theory posits that learning is best accomplished by repeated, deliberate exposure to real cases, that case examples should be selected for their reflection of multiple aspects of clinical reasoning, and that the participation of a coach augments the value of an educational experience. The theory proposes that memory of clinical medicine and clinical reasoning strategies is enhanced when errors in information, judgment, and reasoning are immediately pointed out and discussed. Rather than using cases artificially constructed from memory, real cases are greatly preferred because they often reflect the false leads, the polymorphisms of actual clinical material, and the misleading test results encountered in everyday practice. These concepts foster the teaching and learning of the diagnostic process, the complex trade-offs between the benefits and risks of diagnostic tests and treatments, and cognitive errors in clinical reasoning. The teaching of clinical reasoning need not and should not be delayed until students gain a full understanding of anatomy and pathophysiology. Concepts such as hypothesis generation, pattern recognition, context formulation, diagnostic test interpretation, differential diagnosis, and diagnostic verification provide both the language and the methods of clinical problem solving. Expertise is attainable even though the precise mechanisms of achieving it are not known.

Object reasoning for waste remediation

International Nuclear Information System (INIS)

Pennock, K.A.; Bohn, S.J.; Franklin, A.L.

1991-08-01

A large number of contaminated waste sites across the United States await size remediation efforts. These sites can be physically complex, composed of multiple, possibly interacting, contaminants distributed throughout one or more media. The Remedial Action Assessment System (RAAS) is being designed and developed to support decisions concerning the selection of remediation alternatives. The goal of this system is to broaden the consideration of remediation alternatives, while reducing the time and cost of making these considerations. The Remedial Action Assessment System is a hybrid system, designed and constructed using object-oriented, knowledge- based systems, and structured programming techniques. RAAS uses a combination of quantitative and qualitative reasoning to consider and suggest remediation alternatives. The reasoning process that drives this application is centered around an object-oriented organization of remediation technology information. This paper describes the information structure and organization used to support this reasoning process. In addition, the paper describes the level of detail of the technology related information used in RAAS, discusses required assumptions and procedural implications of these assumptions, and provides rationale for structuring RAAS in this manner. 3 refs., 3 figs

Analysis of students’ mathematical reasoning

Science.gov (United States)

Sukirwan; Darhim; Herman, T.

2018-01-01

The reasoning is one of the mathematical abilities that have very complex implications. This complexity causes reasoning including abilities that are not easily attainable by students. Similarly, studies dealing with reason are quite diverse, primarily concerned with the quality of mathematical reasoning. The objective of this study was to determine the quality of mathematical reasoning based perspective Lithner. Lithner looked at how the environment affects the mathematical reasoning. In this regard, Lithner made two perspectives, namely imitative reasoning and creative reasoning. Imitative reasoning can be memorized and algorithmic reasoning. The Result study shows that although the students generally still have problems in reasoning. Students tend to be on imitative reasoning which means that students tend to use a routine procedure when dealing with reasoning. It is also shown that the traditional approach still dominates on the situation of students’ daily learning.

Others and Imagination in Reasoning and Argumentation: Improving our Critical Creative Capacity

Directory of Open Access Journals (Sweden)

Michael D. Baumtrog

2017-06-01

Full Text Available Contemporary argumentation theories highlight the importance of Others for contributing to and critiquing an individual’s reasoning and/or argumentation. Reasoners and arguers are encouraged to interact with imagined constructs such as a community of model interlocutors or universal audience. These model interlocutors are theoretically meant to bring to mind reasons and counter-considerations that may not have been conceived of otherwise so as to improve the overall quality of an instance of reasoning or argumentation. Overlooked, however, is the impact of differing individual’s imaginative abilities. This paper argues that more important than relying on an Other, real or imagined, reasoners and arguers would do just as well to improve their own creative abilities first. Consulting a real or imagined Other may help in some cases help, but such a strong reliance on Others comes with serious limitations.

Intertwining Evidence- and Model-Based Reasoning in Physics Sensemaking: An Example from Electrostatics

Science.gov (United States)

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

2017-01-01

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…

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...

Reasons for U.S. Producer Selection of a Goat Enterprise

OpenAIRE

Dunn, Brittany; Nyaupane, Narayan; Gillispie, Jeffrey; McMillan, Kenneth

2014-01-01

This paper addresses 14 possible reasons why meat goat producers selected to engage in meat goat production, with results having implications for research, extension, and teaching efforts. A survey of meat goat producers was conducted. Reasons for entering meat goat production were assessed and analyzed using ordered probit models.

Automated reasoning applications to design validation and sneak function analysis

International Nuclear Information System (INIS)

Stratton, R.C.

1984-01-01

Argonne National Laboratory (ANL) is actively involved in the LMFBR Man-Machine Integration (MMI) Safety Program. The objective of this program is to enhance the operational safety and reliability of fast-breeder reactors by optimum integration of men and machines through the application of human factors principles and control engineering to the design, operation, and the control environment. ANL is developing methods to apply automated reasoning and computerization in the validation and sneak function analysis process. This project provides the element definitions and relations necessary for an automated reasoner (AR) to reason about design validation and sneak function analysis. This project also provides a demonstration of this AR application on an Experimental Breeder Reactor-II (EBR-II) system, the Argonne Cooling System

Effect of Religious Belief on Informal Reasoning about Biotechnology Issues

Science.gov (United States)

Pope, Timothy; Dawson, Vaille; Koul, Rekha

2017-01-01

The advances of modern biotechnology provide teachers with a number of opportunities to explore socioscientific issues, and in doing so to enhance students' reasoning skills. Although some attempt has been made to understand cultural differences in students' informal reasoning across international and regional boundaries, there is limited research…

Pursuing Improvement in Clinical Reasoning: The Integrated Clinical Education Theory.

Science.gov (United States)

Jessee, Mary Ann

2018-01-01

The link between clinical education and development of clinical reasoning is not well supported by one theoretical perspective. Learning to reason during clinical education may be best achieved in a supportive sociocultural context of nursing practice that maximizes reasoning opportunities and facilitates discourse and meaningful feedback. Prelicensure clinical education seldom incorporates these critical components and thus may fail to directly promote clinical reasoning skill. Theoretical frameworks supporting the development of clinical reasoning during clinical education were evaluated. Analysis of strengths and gaps in each framework's support of clinical reasoning development was conducted. Commensurability of philosophical underpinnings was confirmed, and complex relationships among key concepts were elucidated. Six key concepts and three tenets comprise an explanatory predictive theory-the integrated clinical education theory (ICET). ICET provides critical theoretical support for inquiry and action to promote clinical education that improves development of clinical reasoning skill. [J Nurs Educ. 2018;57(1):7-13.]. Copyright 2018, SLACK Incorporated.

Prudential Versus Probative Arguments for Religious Faith: Descartes and Pascal on Reason and Faith

Directory of Open Access Journals (Sweden)

Dennis Sansom

2017-07-01

Full Text Available In this article, I show that Pascal’s prudential agenda, centered on the Wager, more successfully overcomes the restrictions of Pyrrhonic skepticism expressed by Montaigne than Descartes’ probative philosophy, which was based on his “ontological argument” for God’s existence. Descartes’ attempt to base natural science on the metaphysical certainty of a non-deceiving God fails because he cannot prove that a non-deceiving Perfect Being is a “clear and distinct” idea. Pascal’s attempt to base the knowledge of God upon the “reasons of the heart” accepts the epistemological restrictions of skepticism but provides a reason to develop passionate faith, thereby overcoming skepticism. I also show that Descartes and Pascal had different assumptions about the workings of the mind; Descartes relied on a model of the mind as a “theater,” which hindered his agenda, and Pascal upon a “holistic” model, which enabled him to make a prudential argument which was cognitively convincing.

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.

A Bayesian Framework for False Belief Reasoning in Children: A Rational Integration of Theory-Theory and Simulation Theory.

Science.gov (United States)

Asakura, Nobuhiko; Inui, Toshio

2016-01-01

Two apparently contrasting theories have been proposed to account for the development of children's theory of mind (ToM): theory-theory and simulation theory. We present a Bayesian framework that rationally integrates both theories for false belief reasoning. This framework exploits two internal models for predicting the belief states of others: one of self and one of others. These internal models are responsible for simulation-based and theory-based reasoning, respectively. The framework further takes into account empirical studies of a developmental ToM scale (e.g., Wellman and Liu, 2004): developmental progressions of various mental state understandings leading up to false belief understanding. By representing the internal models and their interactions as a causal Bayesian network, we formalize the model of children's false belief reasoning as probabilistic computations on the Bayesian network. This model probabilistically weighs and combines the two internal models and predicts children's false belief ability as a multiplicative effect of their early-developed abilities to understand the mental concepts of diverse beliefs and knowledge access. Specifically, the model predicts that children's proportion of correct responses on a false belief task can be closely approximated as the product of their proportions correct on the diverse belief and knowledge access tasks. To validate this prediction, we illustrate that our model provides good fits to a variety of ToM scale data for preschool children. We discuss the implications and extensions of our model for a deeper understanding of developmental progressions of children's ToM abilities.

Assessing Use of Cognitive Heuristic Representativeness in Clinical Reasoning

Science.gov (United States)

Payne, Velma L.; Crowley, Rebecca S.

2008-01-01

We performed a pilot study to investigate use of the cognitive heuristic Representativeness in clinical reasoning. We tested a set of tasks and assessments to determine whether subjects used the heuristics in reasoning, to obtain initial frequencies of heuristic use and related cognitive errors, and to collect cognitive process data using think-aloud techniques. The study investigates two aspects of the Representativeness heuristic - judging by perceived frequency and representativeness as causal beliefs. Results show that subjects apply both aspects of the heuristic during reasoning, and make errors related to misapplication of these heuristics. Subjects in this study rarely used base rates, showed significant variability in their recall of base rates, demonstrated limited ability to use provided base rates, and favored causal data in diagnosis. We conclude that the tasks and assessments we have developed provide a suitable test-bed to study the cognitive processes underlying heuristic errors. PMID:18999140

An Intuitionistic Fuzzy Stochastic Decision-Making Method Based on Case-Based Reasoning and Prospect Theory

Directory of Open Access Journals (Sweden)

Peng Li

2017-01-01

Full Text Available According to the case-based reasoning method and prospect theory, this paper mainly focuses on finding a way to obtain decision-makers’ preferences and the criterion weights for stochastic multicriteria decision-making problems and classify alternatives. Firstly, we construct a new score function for an intuitionistic fuzzy number (IFN considering the decision-making environment. Then, we aggregate the decision-making information in different natural states according to the prospect theory and test decision-making matrices. A mathematical programming model based on a case-based reasoning method is presented to obtain the criterion weights. Moreover, in the original decision-making problem, we integrate all the intuitionistic fuzzy decision-making matrices into an expectation matrix using the expected utility theory and classify or rank the alternatives by the case-based reasoning method. Finally, two illustrative examples are provided to illustrate the implementation process and applicability of the developed method.

Historical reasoning: towards a framework for analyzing students' reasoning about the past

NARCIS (Netherlands)

van Drie, J.; van Boxtel, C.

2008-01-01

This article explores historical reasoning, an important activity in history learning. Based upon an extensive review of empirical literature on students’ thinking and reasoning about history, a theoretical framework of historical reasoning is proposed. The framework consists of six components:

Clinical reasoning and population health: decision making for an emerging paradigm of health care.

Science.gov (United States)

Edwards, Ian; Richardson, Barbara

2008-01-01

Chronic conditions now provide the major disease and disability burden facing humanity. This development has necessitated a reorientation in the practice skills of health care professions away from hospital-based inpatient and outpatient care toward community-based management of patients with chronic conditions. Part of this reorientation toward community-based management of chronic conditions involves practitioners' understanding and adoption of a concept of population health management based on appropriate theoretical models of health care. Drawing on recent studies of expertise in physiotherapy, this article proposes a clinical reasoning and decision-making framework to meet these challenges. The challenge of population and community-based management of chronic conditions also provides an opportunity for physiotherapists to further clarify a professional epistemology of practice that embraces the kinds of knowledge and clinical reasoning processes used in physiotherapy practice. Three case studies related to the management of chronic musculoskeletal pain in different populations are used to exemplify the range of epistemological perspectives that underpin community-based practice. They illustrate the link between conceptualizations of practice problems and knowledge sources that are used as a basis for clinical reasoning and decision making as practitioners are increasingly required to move between the clinic and the community.

Reasoning about Control Situations in Power Systems

DEFF Research Database (Denmark)

Saleem, Arshad; Lind, Morten

2009-01-01

Introduction of distributed generation, deregulation and distribution of control has brought new challenges for electric power system operation, control and automation. Traditional power system models used in reasoning tasks such as intelligent control are highly dependent on the task purpose. Thus......, a model for intelligent control must represent system features, so that information from measurements can be related to possible system states and to control actions. These general modeling requirements are well understood, but it is, in general, difficult to translate them into a model because...

Clinical reasoning in neurology: use of the repertory grid technique to investigate the reasoning of an experienced occupational therapist.

Science.gov (United States)

Kuipers, Kathy; Grice, James W

2009-08-01

The aim of this paper is to describe the use of a structured interview methodology, the repertory grid technique, for investigating the clinical reasoning of an experienced occupational therapist in the domain of upper limb hypertonia as a result of brain injury. Repertory grid interviews were completed before and after exposure to a protocol designed to guide clinical reasoning and decision-making in relation to upper limb neurological rehabilitation. Data were subjected to both qualitative and quantitative analyses. Qualitative analysis focussed on clinical reasoning content. Common themes across the pre- and post-exposure interviews were the use of theoretical frameworks and practice models, the significance of clinical expertise, and discrimination of 'broad' and 'specific' aspects, as well as differentiation between 'therapist and client-related' aspects of the clinical situation. Quantitative analysis indicated that for both pre- and post-exposure repertory grids, clinical reasoning was structured in terms of two main concepts. In the pre-exposure grid, these were related to the therapist's role, and to the 'scope' of practice tasks (either broad or specific). In the post-exposure grid the two main concepts were upper limb performance, and client-centred aspects of the therapy process. The repertory grid technique is proposed as an effective tool for exploring occupational therapy clinical reasoning, based on its capacity for accessing personal frames of reference, and elucidating both the meaning and the structure supporting clinical reasoning.

Metacognition and reasoning

Science.gov (United States)

Fletcher, Logan; Carruthers, Peter

2012-01-01

This article considers the cognitive architecture of human meta-reasoning: that is, metacognition concerning one's own reasoning and decision-making. The view we defend is that meta-reasoning is a cobbled-together skill comprising diverse self-management strategies acquired through individual and cultural learning. These approximate the monitoring-and-control functions of a postulated adaptive system for metacognition by recruiting mechanisms that were designed for quite other purposes. PMID:22492753

Relational Reasoning for Markov Chains in a Probabilistic Guarded Lambda Calculus

DEFF Research Database (Denmark)

Aguirre, Alejandro; Barthe, Gilles; Birkedal, Lars

2018-01-01

We extend the simply-typed guarded $\\lambda$-calculus with discrete probabilities and endow it with a program logic for reasoning about relational properties of guarded probabilistic computations. This provides a framework for programming and reasoning about infinite stochastic processes like...

Experiences with Aber-OWL, an Ontology Repository with OWL EL Reasoning

KAUST Repository

Slater, Luke; Rodriguez-Garcia, Miguel Angel; O’ Shea, Keiron; Schofield, Paul N.; Gkoutos, Georgios V.; Hoehndorf, Robert

2016-01-01

expressed in the Web Ontology Language (OWL). Computational access to the knowledge contained within them relies on the use of automated reasoning. We have developed Aber-OWL, an ontology repository that provides OWL EL reasoning to answer queries and verify

Does emotional reasoning change during cognitive behavioural therapy for anxiety?

Science.gov (United States)

Berle, David; Moulds, Michelle L; Starcevic, Vladan; Milicevic, Denise; Hannan, Anthony; Dale, Erin; Viswasam, Kirupamani; Brakoulias, Vlasios

2016-01-01

Emotional reasoning refers to the use of subjective emotions, rather than objective evidence, to form conclusions about oneself and the world. It is a key interpretative bias in cognitive models of anxiety disorders and appears to be especially evident in individuals with anxiety disorders. However, the amenability of emotional reasoning to change during treatment has not yet been investigated. We sought to determine whether emotional reasoning tendencies change during a course of routine cognitive-behavioural therapy (CBT). Emotional reasoning tendencies were assessed in 36 individuals with a primary anxiety disorder who were seeking treatment at an outpatient clinic. Changes in anxiety and depressive symptoms as well as emotional reasoning tendencies after 12 sessions of CBT were examined in 25 individuals for whom there was complete data. Emotional reasoning tendencies were evident at pretreatment assessment. Although anxiety and depressive symptoms decreased during CBT, only one of six emotional reasoning interpretative styles (pertaining to conclusions that one is incompetent) changed significantly during the course of therapy. Attrition rates were high and there was not enough information regarding the extent to which therapy specifically focused on addressing emotional reasoning tendencies. Individuals seeking treatment for anxiety disorders appear to engage in emotional reasoning, however routine individual CBT does not appear to result in changes in emotional reasoning tendencies.

Clinical reasoning of nursing students on clinical placement: Clinical educators' perceptions.

Science.gov (United States)

Hunter, Sharyn; Arthur, Carol

2016-05-01

Graduate nurses may have knowledge and adequate clinical psychomotor skills however they have been identified as lacking the clinical reasoning skills to deliver safe, effective care suggesting contemporary educational approaches do not always facilitate the development of nursing students' clinical reasoning. While nursing literature explicates the concept of clinical reasoning and develops models that demonstrate clinical reasoning, there is very little published about nursing students and clinical reasoning during clinical placements. Semi-structured interviews were conducted with ten clinical educators to gain an understanding of how they recognised, developed and appraised nursing students' clinical reasoning while on clinical placement. This study found variability in the clinical educators' conceptualisation, recognition, and facilitation of students' clinical reasoning. Although most of the clinical educators conceptualised clinical reasoning as a process those who did not demonstrated the greatest variability in the recognition and facilitation of students' clinical reasoning. The clinical educators in this study also described being unable to adequately appraise a student's clinical reasoning during clinical placement with the use of the current performance assessment tool. Copyright © 2016 Elsevier Ltd. All rights reserved.

Primary care: constipation and encopresis treatment strategies and reasons to refer.

Science.gov (United States)

Philichi, Lisa; Yuwono, Melawati

2010-01-01

The purpose of the study was to assess constipation and encopresis treatment strategies of primary care providers and determine reasons to refer to a pediatric gastroenterology specialist. A closed-ended questionnaire was mailed to a convenience sampling of 237 pediatric primary care providers. Ninety-one questionnaires were returned with a 38% response rate: 74 (81%) pediatricians and 17 (19%) nurse practitioners. The majority of responders recommended pharmacologic treatment and diet changes. Many providers (73%) estimated a 75%-100% success rate when managing constipation, whereas 19% providers estimated a greater than 80% success rate with encopresis patients. The number one reason to refer was unresponsiveness to treatment (71%), followed by parents want a second opinion (15%), rule out organic cause (9%), and management is too time-consuming (5%). Both primary care providers and pediatric gastroenterologists use medication strategies, but diet recommendations are not the same. Unresponsiveness to treatment is the main reason for referral. If better management can occur in the primary care setting, costly specialty services may be avoided and possibly reduce healthcare costs.

Modelling metal-humic substances-surface systems: reasons for success, failure and possible routes for peace of mind

International Nuclear Information System (INIS)

Reiller, P.E.

2012-01-01

Iron oxides and oxy-hydroxides are commonly of considerable importance in the sorption of ions onto rocks, soils and sediments. They can be the controlling sorptive phases even if they are present in relatively small quantities. In common with other oxides and clay minerals, the sorption pH-edge of metals is directly linked to their hydrolysis: the higher the residual charge on the metal ion, the lower the pH-edge. Modelling of this process has been successfully carried out using different microscopic or macroscopic definitions of the interface (e.g. surface complexation or ion exchange models that may or may not include mineralogical descriptions). The influence of organic material on the sorption of many metals is of significant. This organic material includes simple organic molecules and more complex exo-polymeric substances (e.g. humic substances) produced by the decay of natural organic matter. Sorption of this organic material to mineral surfaces has been the subject of a large body of work. The various types of organic substances do not share the same affinities for mineral surfaces in general, and for iron oxides and oxy-hydroxides in particular. In those cases in which successful models of the component binary systems (i.e. metal-surface, metal-organic, organic-surface) have been developed, the formation of mixed surface complexes, the evolution of the surface itself, the addition order in laboratory systems, and the evolution of natural organic matter fractions during sorption, have often precluded a satisfactory description of metal-surface-organic ternary systems over a sufficiently wide range of parameter values (i.e. pH, ionic strength, concentration of humic substances). This manuscript describes the reasons for some successes and failures in the modelling of the ternary systems. Promising recent advances and possible methods of providing more complete descriptions of these intricate systems are also discussed. (author)

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...

Conceptual Models of the Individual Public Service Provider

DEFF Research Database (Denmark)

Andersen, Lotte Bøgh; Pedersen, Lene Holm; Bhatti, Yosef

are used to gain insight on the motivation of public service providers; namely principal-agent theory, self-determination theory and public service motivation theory. We situate the theoretical discussions in the context of public service providers being transferred to private organizations......Individual public service providers’ motivation can be conceptualized as either extrinsic, autonomous or prosocial, and the question is how we can best theoretically understand this complexity without losing too much coherence and parsimony. Drawing on Allison’s approach (1969), three perspectives...... theoretical – to develop a coherent model of individual public service providers – but the empirical illustration also contributes to our understanding of motivation in the context of public sector outsourcing....

An integrated decision making model for the selection of sustainable forward and reverse logistic providers

DEFF Research Database (Denmark)

Govindan, Kannan; Agarwal, Vernika; Darbari, Jyoti Dhingra

2017-01-01

Due to rising concerns for environmental sustainability, the Indian electronic industry faces immense pressure to incorporate effective sustainable practices into the supply chain (SC) planning. Consequently, manufacturing enterprises (ME) are exploring the option of re-examining their SC...... strategies and taking a formalized approach towards a sustainable partnership with logistics providers. To begin with, it is imperative to associate with sustainable forward and reverse logistics providers to manage effectively the upward and downstream flows simultaneously. In this context, this paper...... improve the sustainable performance value of the SC network and secure reasonable profits. The managerial implications drawn from the result analysis provide a sustainable framework to the ME for enhancing its corporate image....

The nature of advanced reasoning and science instruction

Science.gov (United States)

Lawson, Anton E.

Although the development of reasoning is recognized as an important goal of science instruction, its nature remains somewhat of a mystery. This article discusses two key questions: Does formal thought constitute a structured whole? And what role does propositional logic play in advanced reasoning? Aspects of a model of advanced reasoning are presented in which hypothesis generation and testing are viewed as central processes in intellectual development. It is argued that a number of important advanced reasoning schemata are linked by these processes and should be made a part of science instruction designed to improve students' reasoning abilities.Concerning students' development and use of formal reasoning, Linn (1982) calls for research into practical issues such as the roles of task-specific knowledge and individual differences in performance, roles not emphasized by Piaget in his theory and research. From a science teacher's point of view, this is good advice. Accordingly, this article will expand upon some of the issues raised by Linn in a discussion of the nature of advanced reasoning which attempts to reconcile the apparent contradiction between students' differential use of advanced reasoning schemata in varying contexts with the notion of a general stage of formal thought. Two key questions will be discussed: Does formal thought constitute a structured whole? And what role does propositional logic play in advanced reasoning? The underlying assumption of the present discussion is that, among other things, science instruction should concern itself with the improvement of students' reasoning abilities (cf. Arons, 1976; Arons & Karplus, 1976; Bady, 1979; Bauman, 1976; Educational Policies Commission, 1966; Herron, 1978; Karplus, 1979; Kohlberg & Mayer, 1972; Moshman & Thompson, 1981; Lawson, 1979; Levine & linn, 1977; Pallrand, 1977; Renner & Lawson, 1973; Sayre & Ball, 1975; Schneider & Renner, 1980; Wollman, 1978). The questions are of interest because to

Education and the Limits of Reason: Reading Dostoevsky

Science.gov (United States)

Roberts, Peter

2012-01-01

Philosophers of education have had a longstanding interest in the nature and value of reason. Literature can provide an important source of insight in addressing questions in this area. One writer who is especially helpful in this regard is Fyodor Dostoevsky. In this essay Peter Roberts provides an educational reading of Dostoevsky's highly…

Automated Reasoning Across Tactical Stories to Derive Lessons Learned

Directory of Open Access Journals (Sweden)

J. Wesley Regian

2008-06-01

Full Text Available The Military Analogical Reasoning System (MARS is a performance support system and decision aid for commanders in Tactical Operations Centers. MARS enhances and supports the innate human ability for using stories to reason about tactical goals, plans, situations, and outcomes. The system operates by comparing many instances of stored tactical stories, determining which have analogous situations and lessons learned, and then returning a description of the lessons learned. The description of the lessons learned is at a level of abstraction that can be generalized to an appropriate range of tactical situations. The machine-understandable story representation is based on a military operations data model and associated tactical situation ontology. Thus each story can be thought of, and reasoned about, as an instance of an unfolding tactical situation. The analogical reasoning algorithm is based on Gentner's Structure Mapping Theory. Consider the following two stories. In the first, a U.S. platoon in Viet Nam diverts around a minefield and subsequently comes under ambush from a large hill overlooking their new position. In the second, a U.S. task force in Iraq diverts around a biochemical hazard and subsequently comes under ambush from the roof of an abandoned building. MARS recognizes these stories as analogical, and derives the following abstraction: When enemy-placed obstacles force us into an unplanned route, beware of ambush from elevation or concealment. In this paper we describe the MARS interface, military operations data model, tactical situation ontology, and analogical reasoning algorithm.

Deconstructing climate misinformation to identify reasoning errors

Science.gov (United States)

Cook, John; Ellerton, Peter; Kinkead, David

2018-02-01

Misinformation can have significant societal consequences. For example, misinformation about climate change has confused the public and stalled support for mitigation policies. When people lack the expertise and skill to evaluate the science behind a claim, they typically rely on heuristics such as substituting judgment about something complex (i.e. climate science) with judgment about something simple (i.e. the character of people who speak about climate science) and are therefore vulnerable to misleading information. Inoculation theory offers one approach to effectively neutralize the influence of misinformation. Typically, inoculations convey resistance by providing people with information that counters misinformation. In contrast, we propose inoculating against misinformation by explaining the fallacious reasoning within misleading denialist claims. We offer a strategy based on critical thinking methods to analyse and detect poor reasoning within denialist claims. This strategy includes detailing argument structure, determining the truth of the premises, and checking for validity, hidden premises, or ambiguous language. Focusing on argument structure also facilitates the identification of reasoning fallacies by locating them in the reasoning process. Because this reason-based form of inoculation is based on general critical thinking methods, it offers the distinct advantage of being accessible to those who lack expertise in climate science. We applied this approach to 42 common denialist claims and find that they all demonstrate fallacious reasoning and fail to refute the scientific consensus regarding anthropogenic global warming. This comprehensive deconstruction and refutation of the most common denialist claims about climate change is designed to act as a resource for communicators and educators who teach climate science and/or critical thinking.

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.

Reasons for change - Today's material management

International Nuclear Information System (INIS)

Guilbeault, B.D.; Bargerstock, S.B.

1992-01-01

The current generation of nuclear power plants is approaching middle age. The industry continues to stabilize and mature as this occurs, which creates new areas of focus. This evolution is placing a much greater emphases on the business aspects of the operation and maintenance functions. One area that can provide a reasonable return to the operating organizations is materials management. Florida Power and Light Company has experienced these reasons for change. A new department was formed as part of the Nuclear Division in 1990. Performance improvement tasks were established using goals and objectives consistent with plant support and business requirements. Two of the primary processes within the materials management area control the largest portion of costs to operating budgets: the procurement process and inventory management

Case-Based FCTF Reasoning System

Directory of Open Access Journals (Sweden)

Jing Lu

2015-10-01

Full Text Available Case-based reasoning uses old information to infer the answer of new problems. In case-based reasoning, a reasoner firstly records the previous cases, then searches the previous case list that is similar to the current one and uses that to solve the new case. Case-based reasoning means adapting old solving solutions to new situations. This paper proposes a reasoning system based on the case-based reasoning method. To begin, we show the theoretical structure and algorithm of from coarse to fine (FCTF reasoning system, and then demonstrate that it is possible to successfully learn and reason new information. Finally, we use our system to predict practical weather conditions based on previous ones and experiments show that the prediction accuracy increases with further learning of the FCTF reasoning system.

Data Representations, Transformations, and Statistics for Visual Reasoning

CERN Document Server

Maciejewski, Ross

2011-01-01

Analytical reasoning techniques are methods by which users explore their data to obtain insight and knowledge that can directly support situational awareness and decision making. Recently, the analytical reasoning process has been augmented through the use of interactive visual representations and tools which utilize cognitive, design and perceptual principles. These tools are commonly referred to as visual analytics tools, and the underlying methods and principles have roots in a variety of disciplines. This chapter provides an introduction to young researchers as an overview of common visual

Reasons to temper enthusiasm about open access nursing journals.

Science.gov (United States)

de Jong, Gideon

2017-04-01

Open access is a relatively new phenomenon within nursing science. Several papers from various nursing journals have been published recently on the disadvantages of the traditional model of purchasing proprietary fee-based databases to access scholarly information. Just few nursing scholars are less optimistic about the possible benefits of open access nursing journals. A critical reflection on the merits and pitfalls of open access journals along insights from the literature and personal opinion. Two arguments are discussed, providing justification for tempering enthusiasm about open access journals. First, only research groups with sufficient financial resources can publish in open access journals. Second, open access has conflicting incentives, where the aim is to expand production at the expense of publishing quality articles; a business model that fits well into a neoliberal discourse. There are valid reasons to criticise the traditional publishers for the excessive costs of a single article, therefore preventing the dissemination of scholarly nursing information. On the contrary, the business model of open access publishers is no less imbued with the neoliberal tendency of lining the pockets.

Human Papillomavirus Vaccination: What Are the Reasons for Nonvaccination Among U.S. Adolescents?

Science.gov (United States)

Thompson, Erika L; Rosen, Brittany L; Vamos, Cheryl A; Kadono, Mika; Daley, Ellen M

2017-09-01

Human papillomavirus (HPV) vaccination is recommended for 11- to 12-year-old U.S. adolescents. Unfortunately, HPV vaccine rates have been suboptimal. Parents are key decision agents regarding their adolescents' health; thus, it is necessary to understand their reasons for not vaccinating their adolescents. The purpose of this study was to compare parents' primary reasons for non-HPV vaccination by calendar year, sex of the child, and level of vaccine hesitancy. The National Immunization Survey-Teen 2012-2015 was subset to parents who did not intend for their adolescent to receive the HPV vaccine in the next 12 months (N = 59,897). Survey-weighted logistic regression models assessed the impact of year, sex, and level of hesitancy on main reasons for nonvaccination. Not receiving a recommendation and lack of knowledge were significantly more likely to be the reasons for nonvaccination in 2012 and 2013 compared with 2015. The following reasons were significantly less likely to be reported for females compared with males: not recommended (odds ratio [OR] = .63, 95% confidence interval [CI], .58-.69) and lack of knowledge (OR = .86, 95% CI, .79-.94). In contrast, parents of females were more likely to state they were concerned about safety and side effects (OR = 2.19, 95% CI, 1.98-2.41). Differences in reasons for nonvaccination were observed between those who were unlikely and unsure regarding receiving the HPV vaccine. Findings indicate that U.S. parental attitudes about HPV vaccination have changed over time and reasons for nonvaccination vary based on the sex of the adolescent and the level of hesitancy of the parent. This information can shape how providers respond to parental concerns and HPV vaccine hesitancy. Copyright © 2017 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

A Linguistic Truth-Valued Temporal Reasoning Formalism and Its Implementation

Science.gov (United States)

Lu, Zhirui; Liu, Jun; Augusto, Juan C.; Wang, Hui

Temporality and uncertainty are important features of many real world systems. Solving problems in such systems requires the use of formal mechanism such as logic systems, statistical methods or other reasoning and decision-making methods. In this paper, we propose a linguistic truth-valued temporal reasoning formalism to enable the management of both features concurrently using a linguistic truth valued logic and a temporal logic. We also provide a backward reasoning algorithm which allows the answering of user queries. A simple but realistic scenario in a smart home application is used to illustrate our work.

Step-Indexed Relational Reasoning for Countable Nondeterminism

DEFF Research Database (Denmark)

Birkedal, Lars; Bizjak, Aleš; Schwinghamme, Jan

2013-01-01

for programming languages with countable nondeterminism is challenging. We present a step-indexed logical relations model of a higher-order functional programming language with countable nondeterminism and demonstrate how it can be used to reason about contextually defined may- and must-equivalence. In earlier...

Local Reasoning about a Copying Garbage Collector

DEFF Research Database (Denmark)

Torp-Smith, Noah; Birkedal, Lars; Reynolds, John C.

2008-01-01

We present a programming language, model, and logic appropriate for implementing and reasoning about a memory management system. We state semantically what is meant by correctness of a copying garbage collector, and employ a variant of the novel separation logics to formally specify partial corre...

Children's patterns of reasoning about reading and addition concepts.

Science.gov (United States)

Farrington-Flint, Lee; Canobi, Katherine H; Wood, Clare; Faulkner, Dorothy

2010-06-01

Children's reasoning was examined within two educational contexts (word reading and addition) so as to understand the factors that contribute to relational reasoning in the two domains. Sixty-seven 5- to 7-year-olds were given a series of related words to read or single-digit addition items to solve (interspersed with unrelated items). The frequency, accuracy, and response times of children's self-reports on the conceptually related items provided a measure of relational reasoning, while performance on the unrelated addition and reading items provided a measure of procedural skill. The results indicated that the children's ability to use conceptual relations to solve both reading and addition problems enhanced speed and accuracy levels, increased with age, and was related to procedural skill. However, regression analyses revealed that domain-specific competencies can best explain the use of conceptual relations in both reading and addition. Moreover, a cluster analysis revealed that children differ according to the academic domain in which they first apply conceptual relations and these differences are related to individual variation in their procedural skills within these particular domains. These results highlight the developmental significance of relational reasoning in the context of reading and addition and underscore the importance of concept-procedure links in explaining children's literacy and arithmetical development.

Reasons for withdrawing belief in vivid autobiographical memories.

Science.gov (United States)

Scoboria, Alan; Boucher, Chantal; Mazzoni, Giuliana

2015-01-01

Previous studies have shown that many people hold personal memories for events that they no longer believe occurred. This study examines the reasons that people provide for choosing to reduce autobiographical belief in vividly recollected autobiographical memories. A body of non-believed memories provided by 374 individuals was reviewed to develop a qualitatively derived categorisation system. The final scheme consisted of 8 major categories (in descending order of mention): social feedback, event plausibility, alternative attributions, general memory beliefs, internal event features, consistency with external evidence, views of self/others, personal motivation and numerous sub-categories. Independent raters coded the reports and judged the primary reason that each person provided for withdrawing belief. The nature of each category, frequency of category endorsement, category overlap and phenomenological ratings are presented, following which links to related literature and implications are discussed. This study documents that a wide variety of recollective and non-recollective sources of information influence decision-making about the occurrence of autobiographical events.

EUROCONTROL-Systemic Occurrence Analysis Methodology (SOAM)-A 'Reason'-based organisational methodology for analysing incidents and accidents

International Nuclear Information System (INIS)

Licu, Tony; Cioran, Florin; Hayward, Brent; Lowe, Andrew

2007-01-01

The Safety Occurrence Analysis Methodology (SOAM) developed for EUROCONTROL is an accident investigation methodology based on the Reason Model of organisational accidents. The purpose of a SOAM is to broaden the focus of an investigation from human involvement issues, also known as 'active failures of operational personnel' under Reason's original model, to include analysis of the latent conditions deeper within the organisation that set the context for the event. Such an approach is consistent with the tenets of Just Culture in which people are encouraged to provide full and open information about how incidents occurred, and are not penalised for errors. A truly systemic approach is not simply a means of transferring responsibility for a safety occurrence from front-line employees to senior managers. A consistent philosophy must be applied, where the investigation process seeks to correct deficiencies wherever they may be found, without attempting to apportion blame or liability

Strong Stackelberg reasoning in symmetric games: An experimental replication and extension

Science.gov (United States)

Colman, Andrew M.; Lawrence, Catherine L.

2014-01-01

In common interest games in which players are motivated to coordinate their strategies to achieve a jointly optimal outcome, orthodox game theory provides no general reason or justification for choosing the required strategies. In the simplest cases, where the optimal strategies are intuitively obvious, human decision makers generally coordinate without difficulty, but how they achieve this is poorly understood. Most theories seeking to explain strategic coordination have limited applicability, or require changes to the game specification, or introduce implausible assumptions or radical departures from fundamental game-theoretic assumptions. The theory of strong Stackelberg reasoning, according to which players choose strategies that would maximize their own payoffs if their co-players could invariably anticipate any strategy and respond with a best reply to it, avoids these problems and explains strategic coordination in all dyadic common interest games. Previous experimental evidence has provided evidence for strong Stackelberg reasoning in asymmetric games. Here we report evidence from two experiments consistent with players being influenced by strong Stackelberg reasoning in a wide variety of symmetric 3 × 3 games but tending to revert to other choice criteria when strong Stackelberg reasoning generates small payoffs. PMID:24688846

Strong Stackelberg reasoning in symmetric games: An experimental replication and extension.

Science.gov (United States)

Pulford, Briony D; Colman, Andrew M; Lawrence, Catherine L

2014-01-01

In common interest games in which players are motivated to coordinate their strategies to achieve a jointly optimal outcome, orthodox game theory provides no general reason or justification for choosing the required strategies. In the simplest cases, where the optimal strategies are intuitively obvious, human decision makers generally coordinate without difficulty, but how they achieve this is poorly understood. Most theories seeking to explain strategic coordination have limited applicability, or require changes to the game specification, or introduce implausible assumptions or radical departures from fundamental game-theoretic assumptions. The theory of strong Stackelberg reasoning, according to which players choose strategies that would maximize their own payoffs if their co-players could invariably anticipate any strategy and respond with a best reply to it, avoids these problems and explains strategic coordination in all dyadic common interest games. Previous experimental evidence has provided evidence for strong Stackelberg reasoning in asymmetric games. Here we report evidence from two experiments consistent with players being influenced by strong Stackelberg reasoning in a wide variety of symmetric 3 × 3 games but tending to revert to other choice criteria when strong Stackelberg reasoning generates small payoffs.

Strong Stackelberg reasoning in symmetric games: An experimental replication and extension

Directory of Open Access Journals (Sweden)

Briony D. Pulford

2014-02-01

Full Text Available In common interest games in which players are motivated to coordinate their strategies to achieve a jointly optimal outcome, orthodox game theory provides no general reason or justification for choosing the required strategies. In the simplest cases, where the optimal strategies are intuitively obvious, human decision makers generally coordinate without difficulty, but how they achieve this is poorly understood. Most theories seeking to explain strategic coordination have limited applicability, or require changes to the game specification, or introduce implausible assumptions or radical departures from fundamental game-theoretic assumptions. The theory of strong Stackelberg reasoning, according to which players choose strategies that would maximize their own payoffs if their co-players could invariably anticipate any strategy and respond with a best reply to it, avoids these problems and explains strategic coordination in all dyadic common interest games. Previous experimental evidence has provided evidence for strong Stackelberg reasoning in asymmetric games. Here we report evidence from two experiments consistent with players being influenced by strong Stackelberg reasoning in a wide variety of symmetric 3 × 3 games but tending to revert to other choice criteria when strong Stackelberg reasoning generates small payoffs.

New Provider Models for Sweden and Spain: Public, Private or Non-profit? Comment on "Governance, Government, and the Search for New Provider Models".

Science.gov (United States)

Jeurissen, Patrick P T; Maarse, Hans

2016-06-29

Sweden and Spain experiment with different provider models to reform healthcare provision. Both models have in common that they extend the role of the for-profit sector in healthcare. As the analysis of Saltman and Duran demonstrates, privatisation is an ambiguous and contested strategy that is used for quite different purposes. In our comment, we emphasize that their analysis leaves questions open on the consequences of privatisation for the performance of healthcare and the role of the public sector in healthcare provision. Furthermore, we briefly address the absence of the option of healthcare provision by not-for-profit providers in the privatisation strategy of Sweden and Spain. © 2016 The Author(s); Published by Kerman University of Medical Sciences. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

A reasoned action approach to health promotion.

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Fishbein, Martin

2008-01-01

This article describes the integrative model of behavioral prediction (IM), the latest formulation of a reasoned action approach. The IM attempts to identify a limited set of variables that can account for a considerable proportion of the variance in any given behavior. More specifically, consistent with the original theory of reasoned action, the IM assumes that intentions are the immediate antecedents of behavior, but in addition, the IM recognizes that environmental factors and skills and abilities can moderate the intention-behavior relationship. Similar to the theory of planned behavior, the IM also assumes that intentions are a function of attitudes, perceived normative pressure and self-efficacy, but it views perceived normative pressure as a function of descriptive as well as of injunctive (i.e., subjective) norms. After describing the theory and addressing some of the criticisms directed at a reasoned action approach, the paper illustrates how the theory can be applied to understanding and changing health related behaviors.

Mind-sets of functional reasoning in engineering design

DEFF Research Database (Denmark)

Howard, Thomas J.; Andreasen, Mogens Myrup

2013-01-01

The concept of a function is of great importance in design. This paper describes from theory how designers should reason about functions when designing. This paper introduces the link model, showing how functions and properties link the product and its use, to the perceived value of the product...... that not only is a product's behavior or mode of action designed but also the use activity of the end user. Based on the theoretical perspective unfolded, the authors offer nine mind-sets for both design practitioners and researchers to consider when reasoning about functions....

Productivity of "collisions generate heat" for reconciling an energy model with mechanistic reasoning: A case study

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Scherr, Rachel E.; Robertson, Amy D.

2015-06-01

We observe teachers in professional development courses about energy constructing mechanistic accounts of energy transformations. We analyze a case in which teachers investigating adiabatic compression develop a model of the transformation of kinetic energy to thermal energy. Among their ideas is the idea that thermal energy is generated as a byproduct of individual particle collisions, which is represented in science education research literature as an obstacle to learning. We demonstrate that in this instructional context, the idea that individual particle collisions generate thermal energy is not an obstacle to learning, but instead is productive: it initiates intellectual progress. Specifically, this idea initiates the reconciliation of the teachers' energy model with mechanistic reasoning about adiabatic compression, and leads to a canonically correct model of the transformation of kinetic energy into thermal energy. We claim that the idea's productivity is influenced by features of our particular instructional context, including the instructional goals of the course, the culture of collaborative sense making, and the use of certain representations of energy.

Causal role for inverse reasoning on obsessive-compulsive symptoms: Preliminary evidence from a cognitive bias modification for interpretation bias study.

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Wong, Shiu F; Grisham, Jessica R

2017-12-01

The inference-based approach (IBA) is a cognitive account of the genesis and maintenance of obsessive-compulsive disorder (OCD). According to the IBA, individuals with OCD are prone to using inverse reasoning, in which hypothetical causes form the basis of conclusions about reality. Several studies have provided preliminary support for an association between features of the IBA and OCD symptoms. However, there are currently no studies that have investigated the proposed causal relationship of inverse reasoning in OCD. In a non-clinical sample (N = 187), we used an interpretive cognitive bias procedure to train a bias towards using inverse reasoning (n = 64), healthy sensory-based reasoning (n = 65), or a control condition (n = 58). Participants were randomly allocated to these training conditions. This manipulation allowed us to assess whether, consistent with the IBA, inverse reasoning training increased compulsive-like behaviours and self-reported OCD symptoms. Results indicated that compared to a control condition, participants trained in inverse reasoning reported more OCD symptoms and were more avoidant of potentially contaminated objects. Moreover, change in inverse reasoning bias was a small but significant mediator of the relationship between training condition and behavioural avoidance. Conversely, training in a healthy (non-inverse) reasoning style did not have any effect on symptoms or behaviour relative to the control condition. As this study was conducted in a non-clinical sample, we were unable to generalise our findings to a clinical population. Findings generally support the IBA model by providing preliminary evidence of a causal role for inverse reasoning in OCD. Copyright © 2017 Elsevier Ltd. All rights reserved.

Reasoning about modular datatypes with Mendler induction

Directory of Open Access Journals (Sweden)

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.

Modular Knowledge Representation and Reasoning in the Semantic Web

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Serafini, Luciano; Homola, Martin

Construction of modular ontologies by combining different modules is becoming a necessity in ontology engineering in order to cope with the increasing complexity of the ontologies and the domains they represent. The modular ontology approach takes inspiration from software engineering, where modularization is a widely acknowledged feature. Distributed reasoning is the other side of the coin of modular ontologies: given an ontology comprising of a set of modules, it is desired to perform reasoning by combination of multiple reasoning processes performed locally on each of the modules. In the last ten years, a number of approaches for combining logics has been developed in order to formalize modular ontologies. In this chapter, we survey and compare the main formalisms for modular ontologies and distributed reasoning in the Semantic Web. We select four formalisms build on formal logical grounds of Description Logics: Distributed Description Logics, ℰ-connections, Package-based Description Logics and Integrated Distributed Description Logics. We concentrate on expressivity and distinctive modeling features of each framework. We also discuss reasoning capabilities of each framework.

Detaching reasons from aims: fair play and well-being in soccer as a function of pursuing performance-approach goals for autonomous or controlling reasons.

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Vansteenkiste, Maarten; Mouratidis, Athanasios; Lens, Willy

2010-04-01

In two cross-sectional studies we investigated whether soccer players' well-being (Study 1) and moral functioning (Studies 1 and 2) is related to performance-approach goals and to the autonomous and controlling reasons underlying their pursuit. In support of our hypotheses, we found in Study 1 that autonomous reasons were positively associated with vitality and positive affect, whereas controlling reasons were positively related to negative affect and mostly unrelated to indicators of morality. To investigate the lack of systematic association with moral outcomes, we explored in Study 2 whether performance-approach goals or their underlying reasons would yield an indirect relation to moral outcomes through their association with players' objectifying attitude-their tendency to depersonalize their opponents. Structural equation modeling showed that controlling reasons for performance-approach goals were positively associated with an objectifying attitude, which in turn was positively associated to unfair functioning. Results are discussed within the achievement goal perspective (Elliot, 2005) and self-determination theory (Deci & Ryan, 2000).

[Schizophrenia and modern culture: reasons for insanity].

Science.gov (United States)

Pérez-Álvarez, Marino

2012-02-01

After pointing out the uncertainty and confusion to which neurobiological research has led schizophrenia, as shown and acknowledged in recent reviews, we offer seven reasons for reconsidering schizophrenia a disorder of the self, rather than of the brain. The first reason starts out conceiving schizophrenia as a disorder of the self, in the perspective of current phenomenology. The second relates the fact of its recent origin (as of 1750) with the particular configuration of the modern self and with the great transformation of the community into a society of individuals (industrialization, urbanization). The third reason emphasizes the affinity between schizophrenia and adolescence, a critical age in the formation of the self, which started to be problematic at the end of the 18th century. The fourth is the better prognosis of schizophrenia in developing countries, in comparison to developed countries, which probably has to do with the process of modernization (which still maintains community structures in less developed countries). The fifth is the high incidence of schizophrenia among immigrants, as a fact to be explained in terms of a socio-evolutionary model. The sixth reason reviews the genetic legend of schizophrenia, and how epigenetics gives protagonism back to the environment. The seventh and last reason refers to the reconsideration of psychological therapy as the possible treatment of choice and not merely an adjunct to medication, as it is known that, for patients, interpersonal chemistry is more important than neurochemistry.

A Reasoning Architecture for Expert Troubleshooting of Complex Processes

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National Aeronautics and Space Administration — This paper introduces a novel reasoning methodology, in combination with appropriate models and measurements (data) to perform accurately and expeditiously expert...

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

OpenAIRE

Shamima Islam Nipa; Mohammad Mustafa Kamal Rahat Khan; Mohammad Sohrab Hossain; Mohammad Habibur Rahman; Md. Shofiqul Islam

2015-01-01

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. M...

How can we study reasoning in the brain?

Science.gov (United States)

Papo, David

2015-01-01

The brain did not develop a dedicated device for reasoning. This fact bears dramatic consequences. While for perceptuo-motor functions neural activity is shaped by the input's statistical properties, and processing is carried out at high speed in hardwired spatially segregated modules, in reasoning, neural activity is driven by internal dynamics and processing times, stages, and functional brain geometry are largely unconstrained a priori. Here, it is shown that the complex properties of spontaneous activity, which can be ignored in a short-lived event-related world, become prominent at the long time scales of certain forms of reasoning. It is argued that the neural correlates of reasoning should in fact be defined in terms of non-trivial generic properties of spontaneous brain activity, and that this implies resorting to concepts, analytical tools, and ways of designing experiments that are as yet non-standard in cognitive neuroscience. The implications in terms of models of brain activity, shape of the neural correlates, methods of data analysis, observability of the phenomenon, and experimental designs are discussed.

The new AP Physics exams: Integrating qualitative and quantitative reasoning

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Elby, Andrew

2015-04-01

When physics instructors and education researchers emphasize the importance of integrating qualitative and quantitative reasoning in problem solving, they usually mean using those types of reasoning serially and separately: first students should analyze the physical situation qualitatively/conceptually to figure out the relevant equations, then they should process those equations quantitatively to generate a solution, and finally they should use qualitative reasoning to check that answer for plausibility (Heller, Keith, & Anderson, 1992). The new AP Physics 1 and 2 exams will, of course, reward this approach to problem solving. But one kind of free response question will demand and reward a further integration of qualitative and quantitative reasoning, namely mathematical modeling and sense-making--inventing new equations to capture a physical situation and focusing on proportionalities, inverse proportionalities, and other functional relations to infer what the equation ``says'' about the physical world. In this talk, I discuss examples of these qualitative-quantitative translation questions, highlighting how they differ from both standard quantitative and standard qualitative questions. I then discuss the kinds of modeling activities that can help AP and college students develop these skills and habits of mind.

The barriers to and enablers of providing reasonably adjusted health services to people with intellectual disabilities in acute hospitals: evidence from a mixed-methods study.

Science.gov (United States)

Tuffrey-Wijne, Irene; Goulding, Lucy; Giatras, Nikoletta; Abraham, Elisabeth; Gillard, Steve; White, Sarah; Edwards, Christine; Hollins, Sheila

2014-04-16

To identify the factors that promote and compromise the implementation of reasonably adjusted healthcare services for patients with intellectual disabilities in acute National Health Service (NHS) hospitals. A mixed-methods study involving interviews, questionnaires and participant observation (July 2011-March 2013). Six acute NHS hospital trusts in England. Reasonable adjustments for people with intellectual disabilities were identified through the literature. Data were collected on implementation and staff understanding of these adjustments. Data collected included staff questionnaires (n=990), staff interviews (n=68), interviews with adults with intellectual disabilities (n=33), questionnaires (n=88) and interviews (n=37) with carers of patients with intellectual disabilities, and expert panel discussions (n=42). Hospital strategies that supported implementation of reasonable adjustments did not reliably translate into consistent provision of such adjustments. Good practice often depended on the knowledge, understanding and flexibility of individual staff and teams, leading to the delivery of reasonable adjustments being haphazard throughout the organisation. Major barriers included: lack of effective systems for identifying and flagging patients with intellectual disabilities, lack of staff understanding of the reasonable adjustments that may be needed, lack of clear lines of responsibility and accountability for implementing reasonable adjustments, and lack of allocation of additional funding and resources. Key enablers were the Intellectual Disability Liaison Nurse and the ward manager. The evidence suggests that ward culture, staff attitudes and staff knowledge are crucial in ensuring that hospital services are accessible to vulnerable patients. The authors suggest that flagging the need for specific reasonable adjustments, rather than the vulnerable condition itself, may address some of the barriers. Further research is recommended that describes and

Assessing the use of cognitive heuristic representativeness in clinical reasoning.

Science.gov (United States)

Payne, Velma L; Crowley, Rebecca S; Crowley, Rebecca

2008-11-06

We performed a pilot study to investigate use of the cognitive heuristic Representativeness in clinical reasoning. We tested a set of tasks and assessments to determine whether subjects used the heuristics in reasoning, to obtain initial frequencies of heuristic use and related cognitive errors, and to collect cognitive process data using think-aloud techniques. The study investigates two aspects of the Representativeness heuristic - judging by perceived frequency and representativeness as causal beliefs. Results show that subjects apply both aspects of the heuristic during reasoning, and make errors related to misapplication of these heuristics. Subjects in this study rarely used base rates, showed significant variability in their recall of base rates, demonstrated limited ability to use provided base rates, and favored causal data in diagnosis. We conclude that the tasks and assessments we have developed provide a suitable test-bed to study the cognitive processes underlying heuristic errors.