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

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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.

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

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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.

Modeling mental spatial reasoning about cardinal directions.

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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.

A Pilot Study of Reasons and Risk Factors for "No-Shows" in a Pediatric Neurology Clinic.

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Guzek, Lindsay M; Fadel, William F; Golomb, Meredith R

2015-09-01

Missed clinic appointments lead to decreased patient access, worse patient outcomes, and increased healthcare costs. The goal of this pilot study was to identify reasons for and risk factors associated with missed pediatric neurology outpatient appointments ("no-shows"). This was a prospective cohort study of patients scheduled for 1 week of clinic. Data on patient clinical and demographic information were collected by record review; data on reasons for missed appointments were collected by phone interviews. Univariate and multivariate analyses were conducted using chi-square tests and multiple logistic regression to assess risk factors for missed appointments. Fifty-nine (25%) of 236 scheduled patients were no-shows. Scheduling conflicts (25.9%) and forgetting (20.4%) were the most common reasons for missed appointments. When controlling for confounding factors in the logistic regression, Medicaid (odds ratio 2.36), distance from clinic, and time since appointment was scheduled were associated with missed appointments. Further work in this area is needed. © The Author(s) 2014.

Stimulating Scientific Reasoning with Drawing-Based Modeling

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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.

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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

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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.

Cognitive Trait Modelling: The Case of Inductive Reasoning Ability

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Kinshuk, Taiyu Lin; McNab, Paul

2006-01-01

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

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

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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.

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...

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

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Develaki, Maria

2017-11-01

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

A Model-based Avionic Prognostic Reasoner (MAPR)

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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

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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…

A dynamic model of reasoning and memory.

Science.gov (United States)

Hawkins, Guy E; Hayes, Brett K; Heit, Evan

2016-02-01

Previous models of category-based induction have neglected how the process of induction unfolds over time. We conceive of induction as a dynamic process and provide the first fine-grained examination of the distribution of response times observed in inductive reasoning. We used these data to develop and empirically test the first major quantitative modeling scheme that simultaneously accounts for inductive decisions and their time course. The model assumes that knowledge of similarity relations among novel test probes and items stored in memory drive an accumulation-to-bound sequential sampling process: Test probes with high similarity to studied exemplars are more likely to trigger a generalization response, and more rapidly, than items with low exemplar similarity. We contrast data and model predictions for inductive decisions with a recognition memory task using a common stimulus set. Hierarchical Bayesian analyses across 2 experiments demonstrated that inductive reasoning and recognition memory primarily differ in the threshold to trigger a decision: Observers required less evidence to make a property generalization judgment (induction) than an identity statement about a previously studied item (recognition). Experiment 1 and a condition emphasizing decision speed in Experiment 2 also found evidence that inductive decisions use lower quality similarity-based information than recognition. The findings suggest that induction might represent a less cautious form of recognition. We conclude that sequential sampling models grounded in exemplar-based similarity, combined with hierarchical Bayesian analysis, provide a more fine-grained and informative analysis of the processes involved in inductive reasoning than is possible solely through examination of choice data. PsycINFO Database Record (c) 2016 APA, all rights reserved.

Paraconsistency, Pluralistic Models and Reasoning in Climate Science

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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. 

A quantum probability model of causal reasoning

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Jennifer S Trueblood

2012-05-01

Full Text Available People can often outperform statistical methods and machine learning algorithms in situations that involve making inferences about the relationship between causes and effects. While people are remarkably good at causal reasoning in many situations, there are several instances where they deviate from expected responses. This paper examines three situations where judgments related to causal inference problems produce unexpected results and describes a quantum inference model based on the axiomatic principles of quantum probability theory that can explain these effects. Two of the three phenomena arise from the comparison of predictive judgments (i.e., the conditional probability of an effect given a cause with diagnostic judgments (i.e., the conditional probability of a cause given an effect. The third phenomenon is a new finding examining order effects in predictive causal judgments. The quantum inference model uses the notion of incompatibility among different causes to account for all three phenomena. Psychologically, the model assumes that individuals adopt different points of view when thinking about different causes. The model provides good fits to the data and offers a coherent account for all three causal reasoning effects thus proving to be a viable new candidate for modeling human judgment.

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

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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.

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

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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.

Model of critical diagnostic reasoning: achieving expert clinician performance.

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Harjai, Prashant Kumar; Tiwari, Ruby

2009-01-01

Diagnostic reasoning refers to the analytical processes used to determine patient health problems. While the education curriculum and health care system focus on training nurse clinicians to accurately recognize and rescue clinical situations, assessments of non-expert nurses have yielded less than satisfactory data on diagnostic competency. The contrast between the expert and non-expert nurse clinician raises the important question of how differences in thinking may contribute to a large divergence in accurate diagnostic reasoning. This article recognizes superior organization of one's knowledge base, using prototypes, and quick retrieval of pertinent information, using similarity recognition as two reasons for the expert's superior diagnostic performance. A model of critical diagnostic reasoning, using prototypes and similarity recognition, is proposed and elucidated using case studies. This model serves as a starting point toward bridging the gap between clinical data and accurate problem identification, verification, and management while providing a structure for a knowledge exchange between expert and non-expert clinicians.

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 ...

MTK: An AI tool for model-based reasoning

Science.gov (United States)

Erickson, William K.; Schwartz, Mary R.

1987-01-01

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

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

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

Science.gov (United States)

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.

A public health decision support system model using reasoning methods.

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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 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...

Causal reasoning and models of cognitive tasks for naval nuclear power plant operators

International Nuclear Information System (INIS)

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

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...

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

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.

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.

Intuitionistic Fuzzy Time Series Forecasting Model Based on Intuitionistic Fuzzy Reasoning

Directory of Open Access Journals (Sweden)

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.

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.

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.

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.

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

An API for Integrating Spatial Context Models with Spatial Reasoning Algorithms

DEFF Research Database (Denmark)

Kjærgaard, Mikkel Baun

2006-01-01

The integration of context-aware applications with spatial context models is often done using a common query language. However, algorithms that estimate and reason about spatial context information can benefit from a tighter integration. An object-oriented API makes such integration possible...... and can help reduce the complexity of algorithms making them easier to maintain and develop. This paper propose an object-oriented API for context models of the physical environment and extensions to a location modeling approach called geometric space trees for it to provide adequate support for location...... modeling. The utility of the API is evaluated in several real-world cases from an indoor location system, and spans several types of spatial reasoning algorithms....

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.

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

Science.gov (United States)

McLean, Kate C.; Mansfield, Cade D.

2011-01-01

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

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.

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

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.

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.

Strategic reasoning and bargaining in catastrophic climate change games

Science.gov (United States)

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.

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.

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.

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

Science.gov (United States)

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.

#13ReasonsWhy Health Professionals and Educators are Tweeting: A Systematic Analysis of Uses and Perceptions of Show Content and Learning Outcomes.

Science.gov (United States)

Walker, Kimberly K; Burns, Kelli

2018-04-27

This study is a content analysis of health professionals' and educators' tweets about a popular Netflix show that depicts teen suicide: 13 Reasons Why. A content analysis of 740 tweets was conducted to determine the main themes associated with professionals' and educators' tweets about the show, as well as the valence of the tweets. Additionally, a thematic analysis of linked content in tweets (n = 178) was conducted to explore additional content shared about the show and modeling outcomes. Results indicated the largest percentage of tweets was related to social learning, particularly about outcomes that could occur from viewing the show. The valence of the tweets about outcomes was more positive than negative. However, linked materials commonly circulated in tweets signified greater concern with unintended learning outcomes. Some of the linked content included media guidelines for reporting on suicide with recommendations that entertainment producers follow the guidelines. This study emphasizes the importance of including social learning objectives in future typologies of Twitter uses and demonstrates the importance of examining linked content in Twitter studies.

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.

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…

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

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...

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.

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…

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.

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

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.

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.

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.

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.

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.

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

Science.gov (United States)

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.

A Hierarchal Risk Assessment Model Using the Evidential Reasoning Rule

Directory of Open Access Journals (Sweden)

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.

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

Science.gov (United States)

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…

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

An experimental investigation of emotional reasoning processes in depression.

Science.gov (United States)

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

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.

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...

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...

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....

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 ...

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

Directory of Open Access Journals (Sweden)

Abdul-Wahid Mohammed

2017-01-01

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

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

Time dependent patient no-show predictive modelling development.

Science.gov (United States)

Huang, Yu-Li; Hanauer, David A

2016-05-09

Purpose - The purpose of this paper is to develop evident-based predictive no-show models considering patients' each past appointment status, a time-dependent component, as an independent predictor to improve predictability. Design/methodology/approach - A ten-year retrospective data set was extracted from a pediatric clinic. It consisted of 7,291 distinct patients who had at least two visits along with their appointment characteristics, patient demographics, and insurance information. Logistic regression was adopted to develop no-show models using two-thirds of the data for training and the remaining data for validation. The no-show threshold was then determined based on minimizing the misclassification of show/no-show assignments. There were a total of 26 predictive model developed based on the number of available past appointments. Simulation was employed to test the effective of each model on costs of patient wait time, physician idle time, and overtime. Findings - The results demonstrated the misclassification rate and the area under the curve of the receiver operating characteristic gradually improved as more appointment history was included until around the 20th predictive model. The overbooking method with no-show predictive models suggested incorporating up to the 16th model and outperformed other overbooking methods by as much as 9.4 per cent in the cost per patient while allowing two additional patients in a clinic day. Research limitations/implications - The challenge now is to actually implement the no-show predictive model systematically to further demonstrate its robustness and simplicity in various scheduling systems. Originality/value - This paper provides examples of how to build the no-show predictive models with time-dependent components to improve the overbooking policy. Accurately identifying scheduled patients' show/no-show status allows clinics to proactively schedule patients to reduce the negative impact of patient no-shows.

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.

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

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.

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....

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

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

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....

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.

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.

Science.gov (United States)

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.

Science.gov (United States)

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...

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.

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.

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).

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.

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

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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.

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

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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

[Experimental analysis of some determinants of inductive reasoning].

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Ono, K

1989-02-01

Three experiments were conducted from a behavioral perspective to investigate the determinants of inductive reasoning and to compare some methodological differences. The dependent variable used in these experiments was the threshold of confident response (TCR), which was defined as "the minimal sample size required to establish generalization from instances." Experiment 1 examined the effects of population size on inductive reasoning, and the results from 35 college students showed that the TCR varied in proportion to the logarithm of population size. In Experiment 2, 30 subjects showed distinct sensitivity to both prior probability and base-rate. The results from 70 subjects who participated in Experiment 3 showed that the TCR was affected by its consequences (risk condition), and especially, that humans were sensitive to a loss situation. These results demonstrate the sensitivity of humans to statistical variables in inductive reasoning. Furthermore, methodological comparison indicated that the experimentally observed values of TCR were close to, but not as precise as the optimal values predicted by Bayes' model. On the other hand, the subjective TCR estimated by subjects was highly discrepant from the observed TCR. These findings suggest that various aspects of inductive reasoning can be fruitfully investigated not only from subjective estimations such as probability likelihood but also from an objective behavioral perspective.

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.

Mathematical reasoning in Elementary School and Higher Education

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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.

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

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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.

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

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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.

Analysis of students’ mathematical reasoning

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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.

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....

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

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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.

Inductive reasoning 2.0.

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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.

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.

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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.

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...

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

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

OpenAIRE

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

2014-01-01

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

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

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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.

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

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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.

Duchenne muscular dystrophy models show their age

OpenAIRE

Chamberlain, Jeffrey S.

2010-01-01

The lack of appropriate animal models has hampered efforts to develop therapies for Duchenne muscular dystrophy (DMD). A new mouse model lacking both dystrophin and telomerase (Sacco et al., 2010) closely mimics the pathological progression of human DMD and shows that muscle stem cell activity is a key determinant of disease severity.

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

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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.

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 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...

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.

Memory self-efficacy predicts responsiveness to inductive reasoning training in older adults.

Science.gov (United States)

Payne, Brennan R; Jackson, Joshua J; Hill, Patrick L; Gao, Xuefei; Roberts, Brent W; Stine-Morrow, Elizabeth A L

2012-01-01

In the current study, we assessed the relationship between memory self-efficacy at pretest and responsiveness to inductive reasoning training in a sample of older adults. Participants completed a measure of self-efficacy assessing beliefs about memory capacity. Participants were then randomly assigned to a waitlist control group or an inductive reasoning training intervention. Latent change score models were used to examine the moderators of change in inductive reasoning. Inductive reasoning showed clear improvements in the training group compared with the control. Within the training group, initial memory capacity beliefs significantly predicted change in inductive reasoning such that those with higher levels of capacity beliefs showed greater responsiveness to the intervention. Further analyses revealed that self-efficacy had effects on how trainees allocated time to the training materials over the course of the intervention. Results indicate that self-referential beliefs about cognitive potential may be an important factor contributing to plasticity in adulthood.

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.

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

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

Science.gov (United States)

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

Science.gov (United States)

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.

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

Science.gov (United States)

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).

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

Scientific reasoning during adolescence: The influence of instruction in science knowledge and reasoning strategies

Science.gov (United States)

Linn, M. C.; Clement, C.; Pulos, S.; Sullivan, P.

The mechanism linking instruction in scientific topics and instruction in logical reasoning strategies is not well understood. This study assesses the role of science topic instruction combined with logical reasoning strategy instruction in teaching adolescent students about blood pressure problems. Logical reasoning instruction for this study emphasizes the controlling-variables strategy. Science topic instruction emphasizes variables affecting blood pressure. Subjects receiving logical reasoning instruction link their knowledge of blood pressure variables to their knowledge of controlling variables more effectively than those receiving science topic instruction alone - their specific responses show how they attempt to integrate their understanding.Received: 15 April 1988

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...

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.

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.

OWL Reasoning Framework over Big Biological Knowledge Network

Science.gov (United States)

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

Tracing Young Children's Scientific Reasoning

Science.gov (United States)

Tytler, Russell; Peterson, Suzanne

2003-08-01

This paper explores the scientific reasoning of 14 children across their first two years of primary school. Children's view of experimentation, their approach to exploration, and their negotiation of competing knowledge claims, are interpreted in terms of categories of epistemological reasoning. Children's epistemological reasoning is distinguished from their ability to control variables. While individual children differ substantially, they show a relatively steady growth in their reasoning, with some contextual variation. A number of these children are reasoning at a level well in advance of curriculum expectations, and it is argued that current recommended practice in primary science needs to be rethought. The data is used to explore the relationship between reasoning and knowledge, and to argue that the generation and exploration of ideas must be the key driver of scientific activity in the primary school.

Reasoning about Codata

Science.gov (United States)

Hinze, Ralf

Programmers happily use induction to prove properties of recursive programs. To show properties of corecursive programs they employ coinduction, but perhaps less enthusiastically. Coinduction is often considered a rather low-level proof method, in particular, as it departs quite radically from equational reasoning. Corecursive programs are conveniently defined using recursion equations. Suitably restricted, these equations possess unique solutions. Uniqueness gives rise to a simple and attractive proof technique, which essentially brings equational reasoning to the coworld. We illustrate the approach using two major examples: streams and infinite binary trees. Both coinductive types exhibit a rich structure: they are applicative functors or idioms, and they can be seen as memo-tables or tabulations. We show that definitions and calculations benefit immensely from this additional structure.

Reasoning with Causal Cycles

Science.gov (United States)

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…

Individual differences and reasoning: a study on personality traits.

Science.gov (United States)

Bensi, Luca; Giusberti, Fiorella; Nori, Raffaella; Gambetti, Elisa

2010-08-01

Personality can play a crucial role in how people reason and decide. Identifying individual differences related to how we actively gather information and use evidence could lead to a better comprehension and predictability of human reasoning. Recent findings have shown that some personality traits are related to similar decision-making patterns showed by people with mental disorders. We performed research with the aim to investigate delusion-proneness, obsessive-like personality, anxiety (trait and state), and reasoning styles in individuals from the general population. We introduced personality trait and state anxiety scores in a regression model to explore specific associations with: (1) amount of data-gathered prior to making a decision; and (2) the use of confirmatory and disconfirmatory evidence. Results showed that all our independent variables were positively or negatively associated with the amount of data collected in order to make simple probabilistic decisions. Anxiety and obsessiveness were the only predictors of the weight attributed to evidence in favour or against a hypothesis. Findings were discussed in relation to theoretical assumptions, predictions, and clinical implications. Personality traits can predict peculiar ways to reason and decide that, in turn, could be involved to some extent in the formation and/or maintenance of psychological disorders.

On the road toward formal reasoning: reasoning with factual causal and contrary-to-fact causal premises during early adolescence.

Science.gov (United States)

Markovits, Henry

2014-12-01

Understanding the development of conditional (if-then) reasoning is critical for theoretical and educational reasons. Here we examined the hypothesis that there is a developmental transition between reasoning with true and contrary-to-fact (CF) causal conditionals. A total of 535 students between 11 and 14 years of age received priming conditions designed to encourage use of either a true or CF alternatives generation strategy and reasoning problems with true causal and CF causal premises (with counterbalanced order). Results show that priming had no effect on reasoning with true causal premises. By contrast, priming with CF alternatives significantly improved logical reasoning with CF premises. Analysis of the effect of order showed that reasoning with CF premises reduced logical responding among younger students but had no effect among older students. Results support the idea that there is a transition in the reasoning processes in this age range associated with the nature of the alternatives generation process required for logical reasoning with true and CF causal conditionals. Copyright © 2014 Elsevier Inc. All rights reserved.

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....

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...

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

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

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.

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

Design for reasoning

DEFF Research Database (Denmark)

Christiansen, Ellen Tove

2009-01-01

The aim of this paper is to position interaction design and information architecture in relation to design of interfaces to ICT applications meant to serve the goal of supporting users’ reasoning, be it learning applications or self-service applications such as citizen self-service. Interaction...... with such applications comprises three forms of reasoning: deduction, induction and abduction. Based on the work of Gregory Bateson, it is suggested that the disciplines of interaction design and information architecture are complementary parts of information processes. To show that abduction, induction and deduction...

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...

Cultural Differences in Justificatory Reasoning

Science.gov (United States)

Soong, Hannah; Lee, Richard; John, George

2012-01-01

Justificatory reasoning, the ability to justify one's beliefs and actions, is an important goal of education. We develop a scale to measure the three forms of justificatory reasoning--absolutism, relativism, and evaluativism--before validating the scale across two cultures and domains. The results show that the scale possessed validity and…

Ability Of Mathematical Reasoning in SMK 10th Grade with LAPS- Heuristic using Performance Assessment

Directory of Open Access Journals (Sweden)

Aulia Nur Arivina

2017-11-01

Full Text Available The purposes of this research are: (1 Test the learning with LAPS-Heuristic model using performance assessment on 10th grade of Trigonometry material is complete, (2 to test the difference of students' mathematical reasoning ability on 10th grade of Trigonometry material between the learning model of LAPS-Heuristic using performance assessment, LAPS-Heuristic learning model with Expository learning model, (3 test the ability of mathematical reasoning with learning model of LAPS-Heuristik on Trigonometry material of SMK on 10th grade using performance assessment is increase. This is a quantitative research. The population is students of 10th grade of SMK 10 Semarang academic year 2016/2017 and the subject of research is selected by clustering random sampling. The results show that (1 Learning by model LAPS-Heuristic using performance assessment on 10th grade of Trigonometry material is complete (2 there are differences in students' mathematical reasoning ability on 10th grade of Trigonometry materials between LAPS-Heuristic learning model using performance assessment, LAPS-Heuristic learning model, and Expository learning model, (3 The ability of mathematical reasoning with learning model of LAPS-Heuristic on Trigonometry material of SMK class X using performance assessment increased.

Minimally inconsistent reasoning in Semantic Web.

Science.gov (United States)

Zhang, Xiaowang

2017-01-01

Reasoning with inconsistencies is an important issue for Semantic Web as imperfect information is unavoidable in real applications. For this, different paraconsistent approaches, due to their capacity to draw as nontrivial conclusions by tolerating inconsistencies, have been proposed to reason with inconsistent description logic knowledge bases. However, existing paraconsistent approaches are often criticized for being too skeptical. To this end, this paper presents a non-monotonic paraconsistent version of description logic reasoning, called minimally inconsistent reasoning, where inconsistencies tolerated in the reasoning are minimized so that more reasonable conclusions can be inferred. Some desirable properties are studied, which shows that the new semantics inherits advantages of both non-monotonic reasoning and paraconsistent reasoning. A complete and sound tableau-based algorithm, called multi-valued tableaux, is developed to capture the minimally inconsistent reasoning. In fact, the tableaux algorithm is designed, as a framework for multi-valued DL, to allow for different underlying paraconsistent semantics, with the mere difference in the clash conditions. Finally, the complexity of minimally inconsistent description logic reasoning is shown on the same level as the (classical) description logic reasoning.

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...

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.

Deductive way of reasoning about the internet AS level topology

International Nuclear Information System (INIS)

Szabó, Dávid; Kőrösi, Attila; Bíró, József; Gulyás, András

2015-01-01

Our current understanding about the AS level topology of the Internet is based on measurements and inductive-type models which set up rules describing the behavior (node and edge dynamics) of the individual ASes and generalize the consequences of these individual actions for the complete AS ecosystem using induction. In this paper we suggest a third, deductive approach in which we have premises for the whole AS system and the consequences of these premises are determined through deductive reasoning. We show that such a deductive approach can give complementary insights into the topological properties of the AS graph. While inductive models can mostly reflect high level statistics (e.g., degree distribution, clustering, diameter), deductive reasoning can identify omnipresent subgraphs and peering likelihood. We also propose a model, called YEAS, incorporating our deductive analytical findings that produces topologies contain both traditional and novel metrics for the AS level Internet. (paper)

Argumentation and Reasoning in Design: An Empirical Analysis of the Effects of Verbal Reasoning on Idea Value in Group Idea Generation

DEFF Research Database (Denmark)

Cramer-Petersen, Claus L.; Ahmed-Kristensen, Saeema

2016-01-01

Reasoning is argumentative and is at the core of design activity and thinking. Understanding the influence of reasoning on the value of ideas is key to support design practice. The paper aims to show the effect of verbal reasoning on the value of ideas. Protocol analyses of four industry cases...... doing idea generation shows that framing by certainty and deductive reasoning lead to useful incremental ideas while framing by uncertainty and abductive reasoning lead to radical ideas. The paper concludes that the way of framing ideas is indicative of how ideas add value to on-going design processes....

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...

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

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.

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.

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...

Minimally inconsistent reasoning in Semantic Web.

Directory of Open Access Journals (Sweden)

Xiaowang Zhang

Full Text Available Reasoning with inconsistencies is an important issue for Semantic Web as imperfect information is unavoidable in real applications. For this, different paraconsistent approaches, due to their capacity to draw as nontrivial conclusions by tolerating inconsistencies, have been proposed to reason with inconsistent description logic knowledge bases. However, existing paraconsistent approaches are often criticized for being too skeptical. To this end, this paper presents a non-monotonic paraconsistent version of description logic reasoning, called minimally inconsistent reasoning, where inconsistencies tolerated in the reasoning are minimized so that more reasonable conclusions can be inferred. Some desirable properties are studied, which shows that the new semantics inherits advantages of both non-monotonic reasoning and paraconsistent reasoning. A complete and sound tableau-based algorithm, called multi-valued tableaux, is developed to capture the minimally inconsistent reasoning. In fact, the tableaux algorithm is designed, as a framework for multi-valued DL, to allow for different underlying paraconsistent semantics, with the mere difference in the clash conditions. Finally, the complexity of minimally inconsistent description logic reasoning is shown on the same level as the (classical description logic reasoning.

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)

The cognition and neuroscience of relational reasoning.

Science.gov (United States)

Krawczyk, Daniel C

2012-01-05

There has been a growing interest in understanding the complex cognitive processes that give rise to human reasoning. This review focuses on the cognitive and neural characteristics of relational reasoning and analogy performance. Initially relational reasoning studies that have investigated the neural basis of abstract reasoning with an emphasis on the prefrontal cortex are described. Next studies of analogical reasoning are reviewed with insights from neuropsychological and neuroimaging studies. Additionally, studies of cognitive components in analogical reasoning are described. This review draws together insights from numerous studies and concludes that prefrontal areas exhibit domain independence in relational reasoning, while posterior areas within the temporal, parietal, and occipital lobes show evidence of domain dependence in reasoning. Lastly, future directions in the study of relational reasoning are discussed. Copyright © 2010 Elsevier B.V. All rights reserved.

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

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...

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 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...

One-reason decision making in risky choice? A closer look at the priority heuristic

Directory of Open Access Journals (Sweden)

Benjamin E. Hilbig

2008-08-01

Full Text Available Although many models for risky choices between gambles assume that information is somehow integrated, the recently proposed priority heuristic (PH claims that choices are based on one piece of information only. That is, although the current reason for a choice according to the PH can vary, all other reasons are claimed to be ignored. However, the choices predicted by the PH and other pieces of information are often confounded, thus rendering critical tests of whether decisions are actually based on one reason only, impossible. The current study aims to remedy this problem by manipulating the number of reasons additionally in line with the choice implied by the PH. The results show that participants' choices and decision times depend heavily on the number of reasons in line with the PH --- thus contradicting the notion of non-compensatory, one-reason decision making.

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.

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…

Expert system reasoning techniques applicable to the electric power industry

International Nuclear Information System (INIS)

Touchton, R.A.

1987-01-01

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

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.

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, ...

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

Analogical Matrices in Young Children and Students with Intellectual Disability: Reasoning by Analogy or Reasoning by Association?

Science.gov (United States)

Denaes, Caroline

2012-01-01

Background: Analogical reasoning (AR) is renowned for being a complex activity. Young children tend to reason by association, rather by analogy, and people with intellectual disability present problems of memorization. Both these populations usually show low performances in AR. The present author investigated whether familiar material and external…

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.…

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.

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

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...

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.

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

Esophageal cancer prediction based on qualitative features using adaptive fuzzy reasoning method

Directory of Open Access Journals (Sweden)

Raed I. Hamed

2015-04-01

Full Text Available Esophageal cancer is one of the most common cancers world-wide and also the most common cause of cancer death. In this paper, we present an adaptive fuzzy reasoning algorithm for rule-based systems using fuzzy Petri nets (FPNs, where the fuzzy production rules are represented by FPN. We developed an adaptive fuzzy Petri net (AFPN reasoning algorithm as a prognostic system to predict the outcome for esophageal cancer based on the serum concentrations of C-reactive protein and albumin as a set of input variables. The system can perform fuzzy reasoning automatically to evaluate the degree of truth of the proposition representing the risk degree value with a weight value to be optimally tuned based on the observed data. In addition, the implementation process for esophageal cancer prediction is fuzzily deducted by the AFPN algorithm. Performance of the composite model is evaluated through a set of experiments. Simulations and experimental results demonstrate the effectiveness and performance of the proposed algorithms. A comparison of the predictive performance of AFPN models with other methods and the analysis of the curve showed the same results with an intuitive behavior of AFPN models.

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.

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.

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.

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

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.

No-show at a forensic psychiatric outpatient clinic : risk factors and reasons

NARCIS (Netherlands)

Feitsma, W. Nathalie; Popping, Roel; Jansen, Danielle E. M. C.

Nonattendance for and late cancellations of scheduled appointments, that is no-show, is a well-known phenomenon in psychiatric outpatient clinics. Research on the topic of no-show for initial and consecutive appointments in the field of forensic psychiatry is scarce. This study therefore aims to

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

2005-01-01

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

Science.gov (United States)

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.…

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

Theoretical and practical significance of formal reasoning

Science.gov (United States)

Linn, Marcia C.

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

Causal reasoning in physics

CERN Document Server

Frisch, Mathias

2014-01-01

Much has been written on the role of causal notions and causal reasoning in the so-called 'special sciences' and in common sense. But does causal reasoning also play a role in physics? Mathias Frisch argues that, contrary to what influential philosophical arguments purport to show, the answer is yes. Time-asymmetric causal structures are as integral a part of the representational toolkit of physics as a theory's dynamical equations. Frisch develops his argument partly through a critique of anti-causal arguments and partly through a detailed examination of actual examples of causal notions in physics, including causal principles invoked in linear response theory and in representations of radiation phenomena. Offering a new perspective on the nature of scientific theories and causal reasoning, this book will be of interest to professional philosophers, graduate students, and anyone interested in the role of causal thinking in science.

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...

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...

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....

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

Science.gov (United States)

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

Analogical reasoning and aging: the processing speed and inhibition hypothesis.

Science.gov (United States)

Bugaiska, Aurélia; Thibaut, Jean-Pierre

2015-01-01

This study was designed to investigate the effect of aging on analogical reasoning by manipulating the strength of semantic association (LowAssoc or HighAssoc) and the number of distracters' semantic analogies of the A:B::C:D type and to determine which factors might be responsible for the age-related differences on analogical reasoning by testing two different theoretical frameworks: the inhibition hypothesis and the speed mediation hypothesis. We compared young adults and two groups of aging people (old and old-old) with word analogies of the A:B::C:D format. Results indicate an age-related effect on analogical reasoning, this effect being greatest with LowAssoc analogies. It was not associated with the presence of semantic distractors. Moreover, the results show that the variance part of the analogy task due to age was mainly explained by processing speed (rather than by inhibition) in the case of old participants and by both processing speed and inhibition in the old-old group. These results are discussed in relation to current models of aging and their interaction with the processes involved in analogical reasoning.

Reasoning about Magnetism at the Microscopic Level

Science.gov (United States)

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…

Using Relational Reasoning Strategies to Help Improve Clinical Reasoning Practice.

Science.gov (United States)

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

2018-05-01

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

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.

How similar are recognition memory and inductive reasoning?

Science.gov (United States)

Hayes, Brett K; Heit, Evan

2013-07-01

Conventionally, memory and reasoning are seen as different types of cognitive activities driven by different processes. In two experiments, we challenged this view by examining the relationship between recognition memory and inductive reasoning involving multiple forms of similarity. A common study set (members of a conjunctive category) was followed by a test set containing old and new category members, as well as items that matched the study set on only one dimension. The study and test sets were presented under recognition or induction instructions. In Experiments 1 and 2, the inductive property being generalized was varied in order to direct attention to different dimensions of similarity. When there was no time pressure on decisions, patterns of positive responding were strongly affected by property type, indicating that different types of similarity were driving recognition and induction. By comparison, speeded judgments showed weaker property effects and could be explained by generalization based on overall similarity. An exemplar model, GEN-EX (GENeralization from EXamples), could account for both the induction and recognition data. These findings show that induction and recognition share core component processes, even when the tasks involve flexible forms of similarity.

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.

A decision network account of reasoning about other people's choices

Science.gov (United States)

Jern, Alan; Kemp, Charles

2015-01-01

The ability to predict and reason about other people's choices is fundamental to social interaction. We propose that people reason about other people's choices using mental models that are similar to decision networks. Decision networks are extensions of Bayesian networks that incorporate the idea that choices are made in order to achieve goals. In our first experiment, we explore how people predict the choices of others. Our remaining three experiments explore how people infer the goals and knowledge of others by observing the choices that they make. We show that decision networks account for our data better than alternative computational accounts that do not incorporate the notion of goal-directed choice or that do not rely on probabilistic inference. PMID:26010559

Research of Uncertainty Reasoning in Pineapple Disease Identification System

Science.gov (United States)

Liu, Liqun; Fan, Haifeng

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

Documenting the use of expert scientific reasoning processes by high school physics students

Directory of Open Access Journals (Sweden)

A. Lynn Stephens

2010-11-01

Full Text Available We describe a methodology for identifying evidence for the use of three types of scientific reasoning. In two case studies of high school physics classes, we used this methodology to identify multiple instances of students using analogies, extreme cases, and Gedanken experiments. Previous case studies of expert scientists have indicated that these processes can be central during scientific model construction; here we code for their spontaneous use by students. We document evidence for numerous instances of these forms of reasoning in these classes. Most of these instances were associated with motion- and force-indicating depictive gestures, which we take as one kind of evidence for the use of animated mental imagery. Altogether, this methodology shows promise for use in highlighting the role of nonformal reasoning in student learning and for investigating the possible association of animated mental imagery with scientific reasoning processes.

Attending to the reasons for attribute non-attendance in choice experiments

DEFF Research Database (Denmark)

Alemu, Mohammed Hussen; Mørkbak, Morten Raun; Olsen, Søren Bøye

. Excluding these genuine zero preferences, as the standard approach essentially does, might bias results. Other respondents claim to have ignored attributes to simplify choices. However, we find that these respondents have actually not completely ignored attributes. We argue along the rationally adaptive...... behavioural model that preferences are indeed elicited in these cases, and we show how using a scaling approach can appropriately weight these observations in the econometric model. Finally, we find that some respondents ignore attributes for protest-like reasons which essentially convey no information about...

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

Directory of Open Access Journals (Sweden)

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.

Science.gov (United States)

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.

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…

Assessment of Abductive Reasoning in Strategy

DEFF Research Database (Denmark)

Guenther, Agnes; Garbuio, Massimo; Eisenbart, Boris

Strategic tools and frameworks mostly analyse past developments to predict future potentials and rely primarily on deductive/inductive logics. While these logics help decision-makers, they limit the pool of strategic options; resulting strategies often lack novelty. Building on the idea that ‘good......’ and ‘bad’ strategies can be differentiated and that out-of-the-boxthinking creates novel strategies, we analyse differences in strategies’ underlying logics. We develop and test a coding scheme to assess reasoning, in particular abductive reasoning. Furthermore, we introduce the notion of observation set...... and show how analogies, anomalies and paradoxes prompt abductive reasoning and create strategic options....

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

Science.gov (United States)

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

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

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 ...

Icon arrays help younger children's proportional reasoning.

Science.gov (United States)

Ruggeri, Azzurra; Vagharchakian, Laurianne; Xu, Fei

2018-06-01

We investigated the effects of two context variables, presentation format (icon arrays or numerical frequencies) and time limitation (limited or unlimited time), on the proportional reasoning abilities of children aged 7 and 10 years, as well as adults. Participants had to select, between two sets of tokens, the one that offered the highest likelihood of drawing a gold token, that is, the set of elements with the greater proportion of gold tokens. Results show that participants performed better in the unlimited time condition. Moreover, besides a general developmental improvement in accuracy, our results show that younger children performed better when proportions were presented as icon arrays, whereas older children and adults were similarly accurate in the two presentation format conditions. Statement of contribution What is already known on this subject? There is a developmental improvement in proportional reasoning accuracy. Icon arrays facilitate reasoning in adults with low numeracy. What does this study add? Participants were more accurate when they were given more time to make the proportional judgement. Younger children's proportional reasoning was more accurate when they were presented with icon arrays. Proportional reasoning abilities correlate with working memory, approximate number system, and subitizing skills. © 2018 The British Psychological Society.

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

Science.gov (United States)

Schmidt, Rainer; Gierl, Lothar

2005-03-01

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

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.

Partial logics with two kinds of negation as a foundation for knowledge-based reasoning

NARCIS (Netherlands)

H. Herre; J.O.M. Jaspars; G. Wagner

1995-01-01

textabstractWe show how to use model classes of partial logic to define semantics of general knowledge-based reasoning. Its essential benefit is that partial logics allow us to distinguish two sorts of negative information: the absence of information and the explicit rejection or falsification of

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.

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

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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.

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

Science.gov (United States)

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.

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.

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)

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.

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…

Reasoning in people with obsessive-compulsive disorder.

Science.gov (United States)

Simpson, Jane; Cove, Jennifer; Fineberg, Naomi; Msetfi, Rachel M; J Ball, Linden

2007-11-01

The aim of this study was to investigate the inductive and deductive reasoning abilities of people with obsessive-compulsive disorder (OCD). Following previous research, it was predicted that people with OCD would show different abilities on inductive reasoning tasks but similar abilities to controls on deductive reasoning tasks. A two-group comparison was used with both groups matched on a range of demographic variables. Where appropriate, unmatched variables were entered into the analyses as covariates. Twenty-three people with OCD and 25 control participants were assessed on two tasks: an inductive reasoning task (the 20-questions task) and a deductive reasoning task (a syllogistic reasoning task with a content-neutral and content-emotional manipulation). While no group differences emerged on several of the parameters of the inductive reasoning task, the OCD group did differ on one, and arguably the most important, parameter by asking fewer correct direct-hypothesis questions. The syllogistic reasoning task results were analysed using both correct response and conclusion acceptance data. While no main effects of group were evident, significant interactions indicated important differences in the way the OCD group reasoned with content neutral and emotional syllogisms. It was argued that the OCD group's patterns of response on both tasks were characterized by the need for more information, states of uncertainty, and doubt and postponement of a final decision.

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.

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.

A mediation model to explain decision making under conditions of risk among adolescents: the role of fluid intelligence and probabilistic reasoning.

Science.gov (United States)

Donati, Maria Anna; Panno, Angelo; Chiesi, Francesca; Primi, Caterina

2014-01-01

This study tested the mediating role of probabilistic reasoning ability in the relationship between fluid intelligence and advantageous decision making among adolescents in explicit situations of risk--that is, in contexts in which information on the choice options (gains, losses, and probabilities) were explicitly presented at the beginning of the task. Participants were 282 adolescents attending high school (77% males, mean age = 17.3 years). We first measured fluid intelligence and probabilistic reasoning ability. Then, to measure decision making under explicit conditions of risk, participants performed the Game of Dice Task, in which they have to decide among different alternatives that are explicitly linked to a specific amount of gain or loss and have obvious winning probabilities that are stable over time. Analyses showed a significant positive indirect effect of fluid intelligence on advantageous decision making through probabilistic reasoning ability that acted as a mediator. Specifically, fluid intelligence may enhance ability to reason in probabilistic terms, which in turn increases the likelihood of advantageous choices when adolescents are confronted with an explicit decisional context. Findings show that in experimental paradigm settings, adolescents are able to make advantageous decisions using cognitive abilities when faced with decisions under explicit risky conditions. This study suggests that interventions designed to promote probabilistic reasoning, for example by incrementing the mathematical prerequisites necessary to reason in probabilistic terms, may have a positive effect on adolescents' decision-making abilities.

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.

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.

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.

Elements Explaining Learning Clinical Reasoning Using Simulation Games

Directory of Open Access Journals (Sweden)

Jaana-Maija Koivisto

2016-12-01

Full Text Available This article presents the findings on which elements in a game-based simulation affect learning clinical reasoning in nursing education. By using engaging gaming elements in virtual simulations and integrating the clinical reasoning process into game mechanics, games can enhance learning clinical reasoning and offer meaningful learning experiences. The study was designed to explore how nursing students experience gaming and learning when playing a simulation game, as well as which gaming elements explain learning clinical reasoning. The data was collected by questionnaire from nursing students (N = 166 in autumn 2014 over thirteen gaming sessions. The findings showed that usability, application of nursing knowledge, and exploration have the most impact on learning clinical reasoning when playing simulation games. Findings also revealed that authentic patient-related experiences, feedback, and reflection have an indirect effect on learning clinical reasoning. Based on these results, more efficient simulation games to improve clinical reasoning may be developed.   

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.

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...

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

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...

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…

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...

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 ...

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).

Deductive and inductive reasoning in obsessive-compulsive disorder.

Science.gov (United States)

Pélissier, Marie-Claude; O'Connor, Kieron P

2002-03-01

This study tested the hypothesis that people with obsessive-compulsive disorder (OCD) show an inductive reasoning style distinct from people with generalized anxiety disorder (GAD) and from participants in a non-anxious (NA) control group. The experimental procedure consisted of administering a range of six deductive and inductive tasks and a probabilistic task in order to compare reasoning processes between groups. Recruitment was in the Montreal area within a French-speaking population. The participants were 12 people with OCD, 12 NA controls and 10 people with GAD. Participants completed a series of written and oral reasoning tasks including the Wason Selection Task, a Bayesian probability task and other inductive tasks, designed by the authors. There were no differences between groups in deductive reasoning. On an inductive "bridging task", the participants with OCD always took longer than the NA control and GAD groups to infer a link between two statements and to elaborate on this possible link. The OCD group alone showed a significant decrease in their degree of conviction about an arbitrary statement after inductively generating reasons to support this statement. Differences in probabilistic reasoning replicated those of previous authors. The results pinpoint the importance of examining inference processes in people with OCD in order to further refine the clinical applications of behavioural-cognitive therapy for this disorder.

Model shows future cut in U.S. ozone levels

International Nuclear Information System (INIS)

Anon.

1991-01-01

A joint U.S. auto-oil industry research program says modeling shows that changing gasoline composition can reduce ozone levels for Los Angeles in 2010 and for New York City and Dallas-Fort Worth in 2005. The air quality modeling was based on vehicle emissions research data released late last year (OGJ, Dec. 24, 1990, p. 20). The effort is sponsored by the big three auto manufacturers and 14 oil companies. Sponsors the cars and small trucks account for about one third of ozone generated in the three cities studied but by 2005-10 will account for only 5-9%

Case-based reasoning combined with statistics for diagnostics and prognosis

International Nuclear Information System (INIS)

Olsson, T; Funk, P

2012-01-01

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

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.

Individual differences in conflict detection during reasoning.

Science.gov (United States)

Frey, Darren; Johnson, Eric D; De Neys, Wim

2018-05-01

Decades of reasoning and decision-making research have established that human judgment is often biased by intuitive heuristics. Recent "error" or bias detection studies have focused on reasoners' abilities to detect whether their heuristic answer conflicts with logical or probabilistic principles. A key open question is whether there are individual differences in this bias detection efficiency. Here we present three studies in which co-registration of different error detection measures (confidence, response time and confidence response time) allowed us to assess bias detection sensitivity at the individual participant level in a range of reasoning tasks. The results indicate that although most individuals show robust bias detection, as indexed by increased latencies and decreased confidence, there is a subgroup of reasoners who consistently fail to do so. We discuss theoretical and practical implications for the field.

Why Friedman's Non-monotonic Reasoning Defies Hempel's Covering Law Model

NARCIS (Netherlands)

M.C.W. Janssen (Maarten); Y-H. Tan (Yao-Hua)

1991-01-01

textabstractIn this paper we will show that Hempel's covering law model can't deal very well with explanations that are based on incomplete knowledge. In particular the symmetry thesis, which is an important aspect of the covering law model, turns out to be problematic for these explanations. We

Why Friedman's non-monotonic reasoning defies Hempel's covering law model

NARCIS (Netherlands)

M.C.W. Janssen (Maarten); Y.H. Tan (Yao Hua)

1991-01-01

textabstractIn this paper we will show that Hempel's covering law model can't deal very well with explanations that are based on incomplete knowledge. In particular the symmetry thesis, which is an important aspect of the covering law model, turns out to be problematic for these explanations. We

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.

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.

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…

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

[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.

Reasoning by analogy: rational foundation of natural analogue studies

International Nuclear Information System (INIS)

Petit, J.-C.

1992-01-01

Long-term extrapolations concerning the safety of a nuclear waste repository cannot be satisfactorily made on the sole basis of short-term laboratory investigations. Most nuclear countries have hence developed an approach relying on the following research directions: 1. laboratory experiments; 2. in situ testing; 3. modeling; and 4. natural analogues, which are the only means by which very slow mechanisms can be identified and by which long-term predictions of models can be tested for pertinence (if not truly validated). Although the field of natural analogues has grown very rapidly in recent years, receiving support from varied specialists and institutions involved in radioactive waste disposal, there is not yet a full consensus on their actual usefulness. More problematic is the criticism sometimes made that analogical reasoning is not ''true science'' and that information retrieved from the study of natural analogues will always remain questionable. The present paper gives some clues about the exact status of reasoning by analogy, compared to more ''scientific'' ways of deriving information from investigated systems. It is not a thorough discussion of this very complex, and by far too philosophical issue but we hope, at least, to present to readers of papers devoted to natural analogue studies arguments showing that this approach has some sound foundation. (author)

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 ...

An Approximate Reasoning-Based Method for Screening High-Level-Waste Tanks for Flammable Gas

International Nuclear Information System (INIS)

Eisenhawer, Stephen W.; Bott, Terry F.; Smith, Ronald E.

2000-01-01

The in situ retention of flammable gas produced by radiolysis and thermal decomposition in high-level waste can pose a safety problem if the gases are released episodically into the dome space of a storage tank. Screening efforts at the Hanford site have been directed at identifying tanks in which this situation could exist. Problems encountered in screening motivated an effort to develop an improved screening methodology. Approximate reasoning (AR) is a formalism designed to emulate the kinds of complex judgments made by subject matter experts. It uses inductive logic structures to build a sequence of forward-chaining inferences about a subject. Approximate-reasoning models incorporate natural language expressions known as linguistic variables to represent evidence. The use of fuzzy sets to represent these variables mathematically makes it practical to evaluate quantitative and qualitative information consistently. In a pilot study to investigate the utility of AR for flammable gas screening, the effort to implement such a model was found to be acceptable, and computational requirements were found to be reasonable. The preliminary results showed that important judgments about the validity of observational data and the predictive power of models could be made. These results give new insights into the problems observed in previous screening efforts

An approximate reasoning-based method for screening high-level-waste tanks for flammable gas

International Nuclear Information System (INIS)

Eisenhawer, S.W.; Bott, T.F.; Smith, R.E.

2000-01-01

The in situ retention of flammable gas produced by radiolysis and thermal decomposition in high-level waste can pose a safety problem if the gases are released episodically into the dome space of a storage tank. Screening efforts at the Hanford site have been directed at identifying tanks in which this situation could exist. Problems encountered in screening motivated an effort to develop and improved screening methodology. Approximate reasoning (AR) is a formalism designed to emulate the kinds of complex judgments made by subject matter experts. It uses inductive logic structures to build a sequence of forward-chaining inferences about a subject. Approximate-reasoning models incorporate natural language expressions known as linguistic variables to represent evidence. The use of fuzzy sets to represent these variables mathematically makes it practical to evaluate quantitative and qualitative information consistently. In a pilot study to investigate the utility of AR for flammable gas screening, the effort to implement such a model was found to be acceptable, and computational requirements were found to be reasonable. The preliminary results showed that important judgments about the validity of observational data and the predictive power of models could be made. These results give new insights into the problems observed in previous screening efforts

An approximate reasoning-based method for screening high-level-waste tanks for flammable gas

Energy Technology Data Exchange (ETDEWEB)

Eisenhawer, S.W.; Bott, T.F.; Smith, R.E.

2000-06-01

The in situ retention of flammable gas produced by radiolysis and thermal decomposition in high-level waste can pose a safety problem if the gases are released episodically into the dome space of a storage tank. Screening efforts at the Hanford site have been directed at identifying tanks in which this situation could exist. Problems encountered in screening motivated an effort to develop and improved screening methodology. Approximate reasoning (AR) is a formalism designed to emulate the kinds of complex judgments made by subject matter experts. It uses inductive logic structures to build a sequence of forward-chaining inferences about a subject. Approximate-reasoning models incorporate natural language expressions known as linguistic variables to represent evidence. The use of fuzzy sets to represent these variables mathematically makes it practical to evaluate quantitative and qualitative information consistently. In a pilot study to investigate the utility of AR for flammable gas screening, the effort to implement such a model was found to be acceptable, and computational requirements were found to be reasonable. The preliminary results showed that important judgments about the validity of observational data and the predictive power of models could be made. These results give new insights into the problems observed in previous screening efforts.

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

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...

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.

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.

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....

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).

University mathematics teachers' views on the required reasoning in calculus exams

OpenAIRE

Bergqvist, Ewa

2012-01-01

Students often use imitative reasoning, i.e. copy algorithms or recall facts, when solving mathematical tasks. Research show that this type of imitative reasoning might weaken the students' understanding of the underlying mathematical concepts. In a previous study, the author classified tasks from 16 final exams from introductory calculus courses at Swedish universities. The results showed that it was possible to pass 15 of the exams, and solve most of the tasks, using imitative reasoning. Th...

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

Heuristic and analytic processes in reasoning: an event-related potential study of belief bias.

Science.gov (United States)

Banks, Adrian P; Hope, Christopher

2014-03-01

Human reasoning involves both heuristic and analytic processes. This study of belief bias in relational reasoning investigated whether the two processes occur serially or in parallel. Participants evaluated the validity of problems in which the conclusions were either logically valid or invalid and either believable or unbelievable. Problems in which the conclusions presented a conflict between the logically valid response and the believable response elicited a more positive P3 than problems in which there was no conflict. This shows that P3 is influenced by the interaction of belief and logic rather than either of these factors on its own. These findings indicate that belief and logic influence reasoning at the same time, supporting models in which belief-based and logical evaluations occur in parallel but not theories in which belief-based heuristic evaluations precede logical analysis.

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.

Application of Theory Reasoned Action in Intention to Use Islamic Banking in Indonesia

OpenAIRE

Reni, Andi; Ahmad, Nor Hayati

2016-01-01

This paper investigates the constructs of Theory of Reasoned Action (TRA), and Theory of Planned Behavior (TPB) (attitude, subjective norm, religion, knowledge, pricing, and government support) on customer behavioral intention and Islamic banking selection. This research using Partial Least Square Structural Equation Modeling with variables such as: attitude, subject norm, religion, knowledge and government support, and pricing. The result shows that attitude, subject norm, religion, knowledg...

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

Electrophysiological difference between mental state decoding and mental state reasoning.

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Cao, Bihua; Li, Yiyuan; Li, Fuhong; Li, Hong

2012-06-29

Previous studies have explored the neural mechanism of Theory of Mind (ToM), but the neural correlates of its two components, mental state decoding and mental state reasoning, remain unclear. In the present study, participants were presented with various photographs, showing an actor looking at 1 of 2 objects, either with a happy or an unhappy expression. They were asked to either decode the emotion of the actor (mental state decoding task), predict which object would be chosen by the actor (mental state reasoning task), or judge at which object the actor was gazing (physical task), while scalp potentials were recorded. Results showed that (1) the reasoning task elicited an earlier N2 peak than the decoding task did over the prefrontal scalp sites; and (2) during the late positive component (240-440 ms), the reasoning task elicited a more positive deflection than the other two tasks did at the prefrontal scalp sites. In addition, neither the decoding task nor the reasoning task has no left/right hemisphere difference. These findings imply that mental state reasoning differs from mental state decoding early (210 ms) after stimulus onset, and that the prefrontal lobe is the neural basis of mental state reasoning. Copyright © 2012 Elsevier B.V. All rights reserved.

Reasons for dropout in swimmers, differences between gender and age and intentions to return to competition.

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Monteiro, Diogo M; Marinho, Daniel A; Moutão, João M; Vitorino, Anabela P; Antunes, Raúl N; Cid, Luís

2018-01-01

This study's main purpose was to analyze reasons for dropout in competitive swimmers and differences between gender and age groups. The influence of dropout on swimmers intentions to return to competition, invariance across gender and validation of Questionnaire of Reasons for Attrition were also analyzed. Study 1 - 366 athletes participated (N.=366; mean age 15.96, SD 5.99) and the data gathered was used for the exploratory analysis, and data gathered on 1008 athletes were used for the confirmatory analysis and the structural equations (N.=1008; mean age 16.26, SD 6.12); Study 2: 1008 athletes participated (N.=1008; mean age 16.26, SD 6.12) on the descriptive and inferential analysis of the reasons behind the practice dropout. The Questionnaire of Reasons Attrition was used in both studies to assess the reasons associated with the practice dropout. In study 1, the results showed an acceptable fit of the measurement model and invariance across gender and also predictive validity regarding swimmers intentions to return to competition (e.g., "demands/pressure" negatively predict intentions). In study 2, the main results showed that the most significant reason for dropout in both genders and all age groups was "dissatisfaction/other priorities"; the study also showed there to be differences between gender and age groups (e.g., female and younger athletes valued "demands/ pressure "more). This study offers useful guidelines for the training process and to support decisions on sports politics to be implemented to overcome the dropout rate. However, it is important to broaden the evidence to other sports and implement programs on identified priority areas based on longitudinal perspectives.

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

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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.

Effects of cognitive training on change in accuracy in inductive reasoning ability.

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Boron, Julie Blaskewicz; Turiano, Nicholas A; Willis, Sherry L; Schaie, K Warner

2007-05-01

We investigated cognitive training effects on accuracy and number of items attempted in inductive reasoning performance in a sample of 335 older participants (M = 72.78 years) from the Seattle Longitudinal Study. We assessed the impact of individual characteristics, including chronic disease. The reasoning training group showed significantly greater gain in accuracy and number of attempted items than did the comparison group; gain was primarily due to enhanced accuracy. Reasoning training effects involved a complex interaction of gender, prior cognitive status, and chronic disease. Women with prior decline on reasoning but no heart disease showed the greatest accuracy increase. In addition, stable reasoning-trained women with heart disease demonstrated significant accuracy gain. Comorbidity was associated with less change in accuracy. The results support the effectiveness of cognitive training on improving the accuracy of reasoning performance.

Nudges to reason: not guilty

OpenAIRE

Levy, N

2017-01-01

I am to grateful to Geoff Keeling for his perceptive response to my paper. In this brief reply, I will argue that he does not succeed in his goal of showing that nudges to reason do not respect autonomy. At most, he establishes only that such nudges may threaten autonomy when used in certain ways and in certain circumstances. As I will show, this is not a conclusion that should give us grounds for particular concerns about nudges.

Children's reasons for living, self-esteem, and violence.

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Merwin, Rhonda M; Ellis, Jon B

2004-01-01

Attitudes toward violence and reasons for living in young adolescents with high, moderate, and low self-esteem were examined. The authors devised an Attitudes Toward Violence questionnaire; the Rosenberg's Self-esteem Scale (RSE) and the Brief Reasons for Living in Adolescents (BRFL-A) was used to assess adaptive characteristics. The independent variables were gender and self-esteem. The dependent variables were total Reasons for Living score and Attitudes Toward Violence score. Participants included 138 boys and 95 girls, ages 11 to 15 years (M = 13.3) from a city middle school. The results showed that for the dependent variable attitudes toward violence, main effects were found for both gender and self-esteem. For the dependent variable reasons for living, a main effect was found for self-esteem but not for gender. An inverse relationship was found between violence and reasons for living. Being male and low self-esteem emerged as predictors of more accepting attitudes toward violence. Low self-esteem was significantly related to fewer reasons for living.

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

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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

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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…

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

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

2017-07-01

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

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

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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.

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

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Fitria Habsah

2017-05-01

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

Adult Gesture in Collaborative Mathematics Reasoning in Different Ages

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

2017-09-01

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

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

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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.

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

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

2017-02-01

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

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

Rational Thinking and Reasonable Thinking in Physics

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Isaeva E. A.

2008-04-01

Full Text Available The usual concept of space and time, based on Aristotle's principle of contemplation of the world and of the absoluteness of time, is a product of rational thinking. At the same time, in philosophy, rational thinking differs from reasonable thinking; the aim of logic is to distinguish finite forms from infinite forms. Agreeing that space and time are things of infinity in this work, we shall show that, with regard to these two things, it is necessary to apply reasonable thinking. Spaces with non-Euclidean geometry, for example Riemannian and Finslerian spaces, in particular, the space of the General Theory of the Relativity (four-dimensional pseudo-Riemannian geometry and also the concept of multi-dimensional space-time are products of reasonable thinking. Consequently, modern physical experiment not dealing with daily occurrences (greater speeds than a low speed to the velocity of light, strong fields, singularities, etc. can be covered only by reasonable thinking.

Rational Thinking and Reasonable Thinking in Physics

Directory of Open Access Journals (Sweden)

Isaeva E. A.

2008-04-01

Full Text Available The usual concept of space and time, based on Aristotle’s principle of contemplation of the world and of the absoluteness of time, is a product of rational thinking. At the same time, in philosophy, rational thinking differs from reasonable thinking; the aim of logic is to distinguish finite forms from infinite forms. Agreeing that space and time are things of infinity in this work, we shall show that, with regard to these two things, it is necessary to apply reasonable thinking. Spaces with non-Euclidean geometry, for example Riemannian and Finslerian spaces, in particular, the space of the General Theory of the Relativity (four-dimensional pseudo-Riemannian geometry and also the concept of multi-dimensional space-time are products of reasonable thinking. Consequently, modern physical experiment not dealing with daily occurrences (greater speeds than a low speed to the velocity of light, strong fields, singularities, etc. can be covered only by reasonable thinking.

Varieties of noise: analogical reasoning in synthetic biology.

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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.

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

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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.

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

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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

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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…

Visualizing Three-dimensional Slab Geometries with ShowEarthModel

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Chang, B.; Jadamec, M. A.; Fischer, K. M.; Kreylos, O.; Yikilmaz, M. B.

2017-12-01

Seismic data that characterize the morphology of modern subducted slabs on Earth suggest that a two-dimensional paradigm is no longer adequate to describe the subduction process. Here we demonstrate the effect of data exploration of three-dimensional (3D) global slab geometries with the open source program ShowEarthModel. ShowEarthModel was designed specifically to support data exploration, by focusing on interactivity and real-time response using the Vrui toolkit. Sixteen movies are presented that explore the 3D complexity of modern subduction zones on Earth. The first movie provides a guided tour through the Earth's major subduction zones, comparing the global slab geometry data sets of Gudmundsson and Sambridge (1998), Syracuse and Abers (2006), and Hayes et al. (2012). Fifteen regional movies explore the individual subduction zones and regions intersecting slabs, using the Hayes et al. (2012) slab geometry models where available and the Engdahl and Villasenor (2002) global earthquake data set. Viewing the subduction zones in this way provides an improved conceptualization of the 3D morphology within a given subduction zone as well as the 3D spatial relations between the intersecting slabs. This approach provides a powerful tool for rendering earth properties and broadening capabilities in both Earth Science research and education by allowing for whole earth visualization. The 3D characterization of global slab geometries is placed in the context of 3D slab-driven mantle flow and observations of shear wave splitting in subduction zones. These visualizations contribute to the paradigm shift from a 2D to 3D subduction framework by facilitating the conceptualization of the modern subduction system on Earth in 3D space.

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.

The Effect of Cooperative Learning with DSLM on Conceptual Understanding and Scientific Reasoning among Form Four Physics Students with Different Motivation Levels

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M.S. Hamzah

2010-11-01

Full Text Available The purpose of this study was to investigate the effect of Cooperative Learning with a Dual Situated Learning Model (CLDSLM and a Dual Situated Learning Model (DSLM on (a conceptual understanding (CU and (b scientific reasoning (SR among Form Four students. The study further investigated the effect of the CLDSLM and DSLM methods on performance in conceptual understanding and scientific reasoning among students with different motivation levels. A quasi-experimental method with the 3 x 2 Factorial Design was applied in the study. The sample consisted of 240 stu¬dents in six (form four classes selected from three different schools, i.e. two classes from each school, with students randomly selected and assigned to the treatment groups. The results showed that students in the CLDSLM group outperformed their counterparts in the DSLM group—who, in turn, significantly outperformed other students in the traditional instructional method (T group in scientific reasoning and conceptual understanding. Also, high-motivation (HM students in the CLDSLM group significantly outperformed their counterparts in the T groups in conceptual understanding and scientific reasoning. Furthermore, HM students in the CLDSLM group significantly outperformed their counterparts in the DSLM group in scientific reasoning but did not significantly outperform their counterparts on conceptual understanding. Also, the DSLM instructional method has significant positive effects on highly motivated students’ (a conceptual understanding and (b scientific reason¬ing. The results also showed that LM students in the CLDSLM group significantly outperformed their counterparts in the DSLM group and (T method group in scientific reasoning and conceptual understanding. However, the low-motivation students taught via the DSLM instructional method significantly performed higher than the low-motivation students taught via the T method in scientific reasoning. Nevertheless, they did not

Reasoning and dyslexia: is visual memory a compensatory resource?

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Bacon, Alison M; Handley, Simon J

2014-11-01

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

EMOTIONS AND REASONING IN MORAL DECISION MAKING

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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.

Sociomoral Reasoning in Adults with ADHD: A Pilot Study

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Kate E. Thomason

2014-08-01

Full Text Available Attention Deficit Hyperactivity Disorder (ADHD is frequently linked with antisocial behaviour, yet less is known about its relationship with sociomoral reasoning, and the possible mediating effect of intelligence. A pilot study was designed to investigate the relationship between antisocial personality traits, intelligence and sociomoral reasoning in adults with ADHD. Twenty two adults with ADHD and 21 healthy controls, matched for age, gender and IQ completed a battery of measures including the National Adult Reading Test, Gough Socialisation Scale and Sociomoral Reflection Measure-Short Form. There was no difference between the groups and levels of sociomoral reasoning, despite the ADHD group reporting greater antisocial personality traits. Sociomoral reasoning was positively correlated with intelligence. Results from a hierarchical multiple regressions indicated that both antisocial traits and IQ were significant predictors of sociomoral reasoning, with IQ proving the most powerful predictor. Whilst antisocial personality traits may explain some of the variance in levels of sociomoral reasoning, a diagnosis of ADHD does not appear to hinder the development of mature moral reasoning. Intellectual functioning appears to facilitate the development of sociomoral reasoning. A further analysis showed that both ADHD and low sociomoral reasoning were significant predictors of antisocial traits. The current findings have important treatment implications.

In two minds: dual-process accounts of reasoning.

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Evans, Jonathan St B T

2003-10-01

Researchers in thinking and reasoning have proposed recently that there are two distinct cognitive systems underlying reasoning. System 1 is old in evolutionary terms and shared with other animals: it comprises a set of autonomous subsystems that include both innate input modules and domain-specific knowledge acquired by a domain-general learning mechanism. System 2 is evolutionarily recent and distinctively human: it permits abstract reasoning and hypothetical thinking, but is constrained by working memory capacity and correlated with measures of general intelligence. These theories essentially posit two minds in one brain with a range of experimental psychological evidence showing that the two systems compete for control of our inferences and actions.

Automated Assume-Guarantee Reasoning for Omega-Regular Systems and Specifications

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Chaki, Sagar; Gurfinkel, Arie

2010-01-01

We develop a learning-based automated Assume-Guarantee (AG) reasoning framework for verifying omega-regular properties of concurrent systems. We study the applicability of non-circular (AGNC) and circular (AG-C) AG proof rules in the context of systems with infinite behaviors. In particular, we show that AG-NC is incomplete when assumptions are restricted to strictly infinite behaviors, while AG-C remains complete. We present a general formalization, called LAG, of the learning based automated AG paradigm. We show how existing approaches for automated AG reasoning are special instances of LAG.We develop two learning algorithms for a class of systems, called infinite regular systems, that combine finite and infinite behaviors. We show that for infinity-regular systems, both AG-NC and AG-C are sound and complete. Finally, we show how to instantiate LAG to do automated AG reasoning for infinite regular, and omega-regular, systems using both AG-NC and AG-C as proof rules

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

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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.

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:

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...

Inductive Reasoning About Effectful Data Types

DEFF Research Database (Denmark)

Filinski, Andrzej; Støvring, Kristian

2007-01-01

We present a pair of reasoning principles, definition and proof by rigid induction, which can be seen as proper generalizations of lazy-datatype induction to monadic effects other than partiality. We further show how these principles can be integrated into logical-relations arguments, and obtain...

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

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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

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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

Does emotional reasoning change during cognitive behavioural therapy for anxiety?

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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.

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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.

Reasons for Implementing Movement in Kinetic Architecture

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Cudzik, Jan; Nyka, Lucyna

2017-10-01

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

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.

A population-based investigation into the self-reported reasons for sleep problems.

Directory of Open Access Journals (Sweden)

David Armstrong

Full Text Available Typologies of sleep problems have usually relied on identifying underlying causes or symptom clusters. In this study the value of using the patient's own reasons for sleep disturbance are explored. Using secondary data analysis of a nationally representative psychiatric survey the patterning of the various reasons respondents provided for self-reported sleep problems were examined. Over two thirds (69.3% of respondents could identify a specific reason for their sleep problem with worry (37.9% and illness (20.1% representing the most commonly reported reasons. And while women reported more sleep problems for almost every reason compared with men, the patterning of reasons by age showed marked variability. Sleep problem symptoms such as difficulty getting to sleep or waking early also showed variability by different reasons as did the association with major correlates such as worry, depression, anxiety and poor health. While prevalence surveys of 'insomnia' or 'poor sleep' often assume the identification of an underlying homogeneous construct there may be grounds for recognising the existence of different sleep problem types particularly in the context of the patient's perceived reason for the problem.

The Effect of Psychological Distance on Children's Reasoning about Future Preferences.

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Lee, Wendy S C; Atance, Cristina M

2016-01-01

Young preschool-aged children often have difficulty thinking about the future, but tend to reason better about another person's future than their own. This benefit may reflect psychological distance from one's own emotions, beliefs, and states that may bias thinking. In adults, reasoning for others who are more socially distant (i.e., dissimilar, unfamiliar other) is associated with wiser and more adaptive reasoning. The current studies examined whether this effect of social distance could be demonstrated in young children's future thinking. In a future preferences task, 3- and 4-year-olds were shown 5 pairs of child and adult items and selected which ones they would prefer when grown-up. Children answered for themselves, a socially close peer, or a socially distant peer. Social distance was manipulated by varying similarity in Study 1 and familiarity in Study 2. In Study 1, reasoning for similar and dissimilar peers was significantly more accurate than reasoning for the self, but reasoning for similar and dissimilar peers did not differ. In Study 2, scores showed a step-wise increase from self, familiar peer, to unfamiliar peer, but only reasoning for an unfamiliar peer was significantly better more accurate than reasoning for the self. Reasoning for a familiar peer did not differ from reasoning for the self or for an unfamiliar peer. These results suggest that, like adults, children benefit from psychological distance when reasoning for others, but are less sensitive to degrees of social distance, showing no graded effects on performance in Study 1 and weak effects in Study 2. Stronger adult-like effects may only emerge with increasing age and development of other socio-cognitive skills.

False belief reasoning in the brain: An ERP study

Institute of Scientific and Technical Information of China (English)

2008-01-01

Understanding others mind and interpersonal interaction are the cognitive basis of successful social interactions. People’s mental states and behaviors rely on their holding beliefs for self and others. To investigate the neural substrates of false belief reasoning, the 32 channels event-related potentials (ERP) of 14 normal adults were measured while they understood false-belief and true belief used de-ceptive appearance task. After onset of the false-belief or true-belief questions, N100, P200 and late negative component (LNC) were elicited at centro-frontal sites. Compared with true belief, false belief reasoning elicited significant declined LNC in the time window from 400 to 800 ms. The source analysis of difference wave (False minus True) showed a dipole located in the middle cingulated cortex. These findings show that false belief reasoning probably included inhibitive process.

False belief reasoning in the brain: An ERP study

Institute of Scientific and Technical Information of China (English)

无

2008-01-01

Understanding others mind and interpersonal interaction are the cognitive basis of successful social interactions. People's mental states and behaviors rely on their holding beliefs for self and others. To investigate the neural substrates of false belief reasoning, the 32 channels event-related potentials (ERP) of 14 normal adults were measured while they understood false-belief and true belief used deceptive appearance task. After onset of the false-belief or true-belief questions, N100, P200 and late negative component (LNC) were elicited at centro-frontal sites. Compared with true belief, false belief reasoning elicited significant declined LNC in the time window from 400 to 800 ms. The source analysis of difference wave (False minus True) showed a dipole located in the middle cingulated cortex. These findings show that false belief reasoning probably included inhibitive process.

Sex Differences in Fluid Reasoning: Manifest and Latent Estimates from the Cognitive Abilities Test

Directory of Open Access Journals (Sweden)

Joni M. Lakin

2014-06-01

Full Text Available The size and nature of sex differences in cognitive ability continues to be a source of controversy. Conflicting findings result from the selection of measures, samples, and methods used to estimate sex differences. Existing sex differences work on the Cognitive Abilities Test (CogAT has analyzed manifest variables, leaving open questions about sex differences in latent narrow cognitive abilities and the underlying broad ability of fluid reasoning (Gf. This study attempted to address these questions. A confirmatory bifactor model was used to estimate Gf and three residual narrow ability factors (verbal, quantitative, and figural. We found that latent mean differences were larger than manifest estimates for all three narrow abilities. However, mean differences in Gf were trivial, consistent with previous research. In estimating group variances, the Gf factor showed substantially greater male variability (around 20% greater. The narrow abilities varied: verbal reasoning showed small variability differences while quantitative and figural showed substantial differences in variance (up to 60% greater. These results add precision and nuance to the study of the variability and masking hypothesis.

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

Teacher Pedagogical Content Knowledge (PCK) and Students’ Reasoning and Wellbeing

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Widodo, A.

2017-02-01

This paper summarizes findings of a study on efforts to improve teachers Pedagogical Content Knowledge and how it affects students’ reasoning and wellbeing. It was found that improvement of teachers’ PCK was not very strong but we managed to develop strategies to facilitate their developments. In the second year, the research was focused on identifying students’ reasoning skills both informal reasoning and formal reasoning. Data showed that students reasoning is relatively low (level 2 of five levels) and they could not construct highly coherence arguments. In addition alternative strategies to promote students’ reasoning were explored. Attempts to support teachers to conduct lessons that facilitate students’ reasoning found that teachers need intensive and continuous support. The study also identifies students’ wellbeing as the impact of improvement of lessons and other activities designed to improve students’ wellbeing. Research on students’ wellbeing is not yet given attention in Indonesian schools although it plays very important roles in students’ academic and nonacademic achievements.

Automated Reasoning Across Tactical Stories to Derive Lessons Learned

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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.

Theory of Reasoned Action predicts milk consumption in women.

Science.gov (United States)

Brewer, J L; Blake, A J; Rankin, S A; Douglass, L W

1999-01-01

To determine the factors influencing the consumption or avoidance of milk in women. One hundred women completed food frequency questionnaires and a milk attitudes questionnaire framed within the Theory of Reasoned Action and performed sensory evaluations of different milk samples. Differences among milk types were assessed using 2-way analysis of variance and least-significant-difference mean comparison procedures. Correlation and multiple regression analyses, and standardized partial regression coefficients, were used to determine the contribution of each component of the model in predicting behavior. Mean age of the 100 subjects was 39 years (range = 20-70 years). Milk consumption among subjects was low; 23 subjects indicated that they seldom or never drank milk. Data from the dairy frequency questionnaire showed that the primary milk for 42%, 36%, 27%, and 18% of the milk drinkers was skim, 2%, 1%, and whole, respectively (subjects could indicate more than 1 type of milk consumed). The Theory of Reasoned Action indicated that health and familiarity belief items were most associated with attitudes toward milk consumption. Skim milk had significantly lower scores for taste and texture belief items than 1%, 2%, and whole milk (P reasons other than beliefs about taste and texture or actual sensory preference. This study identifies important factors contributing to milk consumption such as beliefs, attitudes, and sensory evaluation, which can be used to develop a specific framework in which to examine other components of milk consumption behavior.

Differential involvement of left prefrontal cortex in inductive and deductive reasoning.

Science.gov (United States)

Goel, Vinod; Dolan, Raymond J

2004-10-01

While inductive and deductive reasoning are considered distinct logical and psychological processes, little is known about their respective neural basis. To address this issue we scanned 16 subjects with fMRI, using an event-related design, while they engaged in inductive and deductive reasoning tasks. Both types of reasoning were characterized by activation of left lateral prefrontal and bilateral dorsal frontal, parietal, and occipital cortices. Neural responses unique to each type of reasoning determined from the Reasoning Type (deduction and induction) by Task (reasoning and baseline) interaction indicated greater involvement of left inferior frontal gyrus (BA 44) in deduction than induction, while left dorsolateral (BA 8/9) prefrontal gyrus showed greater activity during induction than deduction. This pattern suggests a dissociation within prefrontal cortex for deductive and inductive reasoning.

"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

Farmers’ reasons for deregistering from organic farming

DEFF Research Database (Denmark)

Koesling, Matthias; Løes, Anne-Kristin; Flaten, Ola

2012-01-01

Every year since 2002, 150 to 200 farmers in Norway have deregistered from certified organic production. The aim of this study was to get behind these figures and improve our understanding of the reasoning leading to decisions to opt out. Four cases of deregistered organic farmers with grain, sheep......, dairy or vegetable production were selected for in-depth studies. The cases were analysed from the perspective of individual competencies and the competencies available in the networks of the selected organic farmers. Besides the conspicuous reasons to opt out of certified organic farming......, such as regulations getting stricter over time and low income, personal reasons such as disappointment and need for acceptance were also important. This shows that hard mechanisms, such as economic support and premium prices, are not sufficient to motivate farmers for sustained organic management. Support...

Causal knowledge and the development of inductive reasoning.

Science.gov (United States)

Bright, Aimée K; Feeney, Aidan

2014-06-01

We explored the development of sensitivity to causal relations in children's inductive reasoning. Children (5-, 8-, and 12-year-olds) and adults were given trials in which they decided whether a property known to be possessed by members of one category was also possessed by members of (a) a taxonomically related category or (b) a causally related category. The direction of the causal link was either predictive (prey→predator) or diagnostic (predator→prey), and the property that participants reasoned about established either a taxonomic or causal context. There was a causal asymmetry effect across all age groups, with more causal choices when the causal link was predictive than when it was diagnostic. Furthermore, context-sensitive causal reasoning showed a curvilinear development, with causal choices being most frequent for 8-year-olds regardless of context. Causal inductions decreased thereafter because 12-year-olds and adults made more taxonomic choices when reasoning in the taxonomic context. These findings suggest that simple causal relations may often be the default knowledge structure in young children's inductive reasoning, that sensitivity to causal direction is present early on, and that children over-generalize their causal knowledge when reasoning. Copyright © 2013 Elsevier Inc. All rights reserved.

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...

Paraconsistent Reasoning for OWL 2

Science.gov (United States)

Ma, Yue; Hitzler, Pascal

A four-valued description logic has been proposed to reason with description logic based inconsistent knowledge bases. This approach has a distinct advantage that it can be implemented by invoking classical reasoners to keep the same complexity as under the classical semantics. However, this approach has so far only been studied for the basic description logic mathcal{ALC}. In this paper, we further study how to extend the four-valued semantics to the more expressive description logic mathcal{SROIQ} which underlies the forthcoming revision of the Web Ontology Language, OWL 2, and also investigate how it fares when adapted to tractable description logics including mathcal{EL++}, DL-Lite, and Horn-DLs. We define the four-valued semantics along the same lines as for mathcal{ALC} and show that we can retain most of the desired properties.

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

Psychopaths are impaired in social exchange and precautionary reasoning.

Science.gov (United States)

Ermer, Elsa; Kiehl, Kent A

2010-10-01

Psychopaths show a profound lack of morality and behavioral controls in the presence of intact general intellectual functioning. Two hallmarks of psychopathy are the persistent violation of social contracts (i.e., cheating) and chronic, impulsive risky behavior. These behaviors present a puzzle: Can psychopaths understand and reason about what counts as cheating or risky behavior in a particular situation? We tested incarcerated psychopaths' and incarcerated nonpsychopaths' reasoning about social contract rules, precautionary rules, and descriptive rules using the Wason selection task. Results were consistent with our hypotheses: Psychopaths (compared with matched nonpsychopaths) showed significant impairment on social contract rules and precautionary rules, but not on descriptive rules. These results cannot be accounted for by differences in intelligence, motivation, or general antisocial tendency. These findings suggest that examination of evolutionarily identified reasoning processes can be a fruitful research approach for identifying which specific mechanisms are impaired in psychopathy.

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.

The canon of pure reason: Kant on the non-dependent establishment of the practical use and the unity of reason

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Adriano Perin

2010-12-01

Full Text Available http://dx.doi.org/10.5007/1677-2954.2008v7n2p137This paper systematically discusses Kant´s argumentation in the Canon of the Critique of pure reason on the matter of the establishment of the practical use and its outcomes for the problem of the unity of reason. Bearing in mind that there is much disagreement in the literature, not only as to the specificity and function of the chapter of the Canon wi thin the various moments of Kant´s philosophy, but also as to its critical importance, the approach centers essentially on Kant´s own argumentation. The aim of this paper is to show that the Canon anticipates an important thesis of the Critique of Practical Reason, i.e., the self-sufficient legitimation of the practical use of reason in relation to its theoretical use, Moreover, is demonstrated that there are important systenatic differences between Kant´s argumentation in the Canon and in the second Critique, which lead to the uniqueness of the treatment of the problem of the unity of reason in the former text. The first part of the paper briefly presents Kant´s position in the pre-critical period on the legitimation of the practical use of reason. Thereafter, it is sustained that Kant´s search in the Canon for a "source of positive cognition" is particularly connected with his critical thesis of a self-sufficient establishment in the Canon. It is argued that, notwithstanding the anticipation of the refered critical thesis, the establishment of the practical use of reason in the Canon requires a theological consideration of morality. The third part of the paper deals with the problem of the unity of theorical and practical uses of reason in position on the establishment of the practical use reason. I come to the conclusion that the Canon guaranteed by means of a transition from the practical to the theoretical use of reason.

Differences in autonomic physiological responses between good and poor inductive reasoners.

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Melis, C; van Boxtel, A

2001-11-01

We investigated individual- and task-related differences in autonomic physiological responses induced by time limited figural and verbal inductive reasoning tasks. In a group of 52 participants, the percentage of correctly responded task items was evaluated together with nine different autonomic physiological response measures and respiration rate (RR). Weighted multidimensional scaling analyses of the physiological responses revealed three underlying dimensions, primarily characterized by RR, parasympathetic, and sympathetic activity. RR and sympathetic activity appeared to be relatively more important response dimensions for poor reasoners, whereas parasympathetic responsivity was relatively more important for good reasoners. These results suggest that poor reasoners showed higher levels of cognitive processing intensity than good reasoners. Furthermore, for the good reasoners, the dimension of sympathetic activity was relatively more important during the figural than during the verbal reasoning task, which was explained in terms of hemispheric lateralization in autonomic function.

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.

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.

3D Reasoning from Blocks to Stability.

Science.gov (United States)

Zhaoyin Jia; Gallagher, Andrew C; Saxena, Ashutosh; Chen, Tsuhan

2015-05-01

Objects occupy physical space and obey physical laws. To truly understand a scene, we must reason about the space that objects in it occupy, and how each objects is supported stably by each other. In other words, we seek to understand which objects would, if moved, cause other objects to fall. This 3D volumetric reasoning is important for many scene understanding tasks, ranging from segmentation of objects to perception of a rich 3D, physically well-founded, interpretations of the scene. In this paper, we propose a new algorithm to parse a single RGB-D image with 3D block units while jointly reasoning about the segments, volumes, supporting relationships, and object stability. Our algorithm is based on the intuition that a good 3D representation of the scene is one that fits the depth data well, and is a stable, self-supporting arrangement of objects (i.e., one that does not topple). We design an energy function for representing the quality of the block representation based on these properties. Our algorithm fits 3D blocks to the depth values corresponding to image segments, and iteratively optimizes the energy function. Our proposed algorithm is the first to consider stability of objects in complex arrangements for reasoning about the underlying structure of the scene. Experimental results show that our stability-reasoning framework improves RGB-D segmentation and scene volumetric representation.

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

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.

Students' reasons for preferring teleological explanations

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Trommler, Friederike; Gresch, Helge; Hammann, Marcus

2018-01-01

The teleological bias, a major learning obstacle, involves explaining biological phenomena in terms of purposes and goals. To probe the teleological bias, researchers have used acceptance judgement tasks and preference judgement tasks. In the present study, such tasks were used with German high school students (N = 353) for 10 phenomena from human biology, that were explained both teleologically and causally. A sub-sample (n = 26) was interviewed about the reasons for their preferences. The results showed that the students favoured teleological explanations over causal explanations. Although the students explained their preference judgements etiologically (i.e. teleologically and causally), they also referred to a wide range of non-etiological criteria (i.e. familiarity, complexity, relevance and five more criteria). When elaborating on their preference for causal explanations, the students often focused not on the causality of the phenomenon, but on mechanisms whose complexity they found attractive. When explaining their preference for teleological explanations, they often focused not teleologically on purposes and goals, but rather on functions, which they found familiar and relevant. Generally, students' preference judgements rarely allowed for making inferences about causal reasoning and teleological reasoning, an issue that is controversial in the literature. Given that students were largely unaware of causality and teleology, their attention must be directed towards distinguishing between etiological and non-etiological reasoning. Implications for educational practice as well as for future research are discussed.

[Schizophrenia and modern culture: reasons for insanity].

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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 knowledge-based system for prototypical reasoning

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

2015-04-01

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

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...

How can we study reasoning in the brain?

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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.

Teaching Quantitative Reasoning: A Better Context for Algebra

Directory of Open Access Journals (Sweden)

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.

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.

Clinical reasoning: concept analysis.

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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.

Prospective elementary and secondary school mathematics teachers’ statistical reasoning

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Rabia KARATOPRAK

2015-04-01

Full Text Available This study investigated prospective elementary (PEMTs and secondary (PSMTs school mathematics teachers’ statistical reasoning. The study began with the adaptation of the Statistical Reasoning Assessment (Garfield, 2003 test. Then, the test was administered to 82 PEMTs and 91 PSMTs in a metropolitan city of Turkey. Results showed that both groups were equally successful in understanding independence, and understanding importance of large samples. However, results from selecting appropriate measures of center together with the misconceptions assessing the same subscales showed that both groups selected mode rather than mean as an appropriate average. This suggested their lack of attention to the categorical and interval/ratio variables while examining data. Similarly, both groups were successful in interpreting and computing probability; however, they had equiprobability bias, law of small numbers and representativeness misconceptions. The results imply a change in some questions in the Statistical Reasoning Assessment test and that teacher training programs should include statistics courses focusing on studying characteristics of samples.

Accounting for dropout reason in longitudinal studies with nonignorable dropout.

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Moore, Camille M; MaWhinney, Samantha; Forster, Jeri E; Carlson, Nichole E; Allshouse, Amanda; Wang, Xinshuo; Routy, Jean-Pierre; Conway, Brian; Connick, Elizabeth

2017-08-01

Dropout is a common problem in longitudinal cohort studies and clinical trials, often raising concerns of nonignorable dropout. Selection, frailty, and mixture models have been proposed to account for potentially nonignorable missingness by relating the longitudinal outcome to time of dropout. In addition, many longitudinal studies encounter multiple types of missing data or reasons for dropout, such as loss to follow-up, disease progression, treatment modifications and death. When clinically distinct dropout reasons are present, it may be preferable to control for both dropout reason and time to gain additional clinical insights. This may be especially interesting when the dropout reason and dropout times differ by the primary exposure variable. We extend a semi-parametric varying-coefficient method for nonignorable dropout to accommodate dropout reason. We apply our method to untreated HIV-infected subjects recruited to the Acute Infection and Early Disease Research Program HIV cohort and compare longitudinal CD4 + T cell count in injection drug users to nonusers with two dropout reasons: anti-retroviral treatment initiation and loss to follow-up.

Predicting and understanding undergraduate students' intentions to gamble in a casino using an extended model of the theory of reasoned action and the theory of planned behavior.

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Lee, Hyung-Seok

2013-06-01

Given that current television programming contains numerous gambling portrayals, it is imperative to understand whether and to what extent these gambling behaviors in media influence individuals' beliefs, attitudes, and intentions. This study explores an extended model of the theory of reasoned action (TRA) by including gambling media exposure as a distal, mediating and mediated factor in predicting undergraduate students' intentions to gamble in a casino. Findings show that the extended model of TRA clearly indicates that the constructs of gambling media exposure, prior gambling experience, and level of gambling addiction contribute to the prediction of undergraduate students' casino gambling intentions. Theoretical implications of gambling media effects and practical implications for public policy are discussed, and future research directions are outlined.

Student reasoning while investigating plant material

Directory of Open Access Journals (Sweden)

Helena Näs

2008-11-01

Full Text Available In this project, 10-12 year old students in three classes, investigated plant material to learn more about plants and photosynthesis. The research study was conducted to reveal the students’ scientific reasoning during their work. The eleven different tasks helped students investigate plant anatomy, plant physiology, and the gases involved in photosynthesis and respiration. The study was carried out in three ordinary classrooms. The collected data consisted of audio-taped discussions, students’ notebooks, and field notes. Students’ discussions and written work, during the different plant tasks, were analysed to see how the students’ learning and understanding processes developed. The analysis is descriptive and uses categories from a modified general typology of student’s epistemological reasoning. The study shows students’ level of interest in doing the tasks, their struggle with new words and concepts, and how they develop their knowledge about plant physiology. The study confirms thatstudents, in this age group, develop understanding and show an interest in complicated processes in natural science, e.g. photosynthesis.

Heuristic reasoning and relative incompleteness

OpenAIRE

Treur, J.

1993-01-01

In this paper an approach is presented in which heuristic reasoning is interpreted as strategic reasoning. This type of reasoning enables one to derive which hypothesis to investigate, and which observable information to acquire next (to be able to verify the chosen hypothesis). A compositional architecture for reasoning systems that perform such heuristic reasoning is introduced, called SIX (for Strategic Interactive eXpert systems). This compositional architecture enables user interaction a...

Emotional reasoning processes and dysphoric mood: cross-sectional and prospective relationships.

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David Berle

Full Text Available Emotional reasoning refers to the use of subjective emotions, rather than objective evidence, to form conclusions about oneself and the world. Emotional reasoning appears to characterise anxiety disorders. We aimed to determine whether elevated levels of emotional reasoning also characterise dysphoria. In Study 1, low dysphoric (BDI-II≤4; n = 28 and high dysphoric (BDI-II ≥14; n = 42 university students were administered an emotional reasoning task relevant for dysphoria. In Study 2, a larger university sample were administered the same task, with additional self-referent ratings, and were followed up 8 weeks later. In Study 1, both the low and high dysphoric participants demonstrated emotional reasoning and there were no significant differences in scores on the emotional reasoning task between the low and high dysphoric groups. In Study 2, self-referent emotional reasoning interpretations showed small-sized positive correlations with depression symptoms. Emotional reasoning tendencies were stable across an 8-week interval although not predictive of subsequent depressive symptoms. Further, anxiety symptoms were independently associated with emotional reasoning and emotional reasoning was not associated with anxiety sensitivity, alexithymia, or deductive reasoning tendencies. The implications of these findings are discussed, including the possibility that while all individuals may engage in emotional reasoning, self-referent emotional reasoning may be associated with increased levels of depressive symptoms.

Emotional reasoning processes and dysphoric mood: cross-sectional and prospective relationships.

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Berle, David; Moulds, Michelle L

2013-01-01

Emotional reasoning refers to the use of subjective emotions, rather than objective evidence, to form conclusions about oneself and the world. Emotional reasoning appears to characterise anxiety disorders. We aimed to determine whether elevated levels of emotional reasoning also characterise dysphoria. In Study 1, low dysphoric (BDI-II≤4; n = 28) and high dysphoric (BDI-II ≥14; n = 42) university students were administered an emotional reasoning task relevant for dysphoria. In Study 2, a larger university sample were administered the same task, with additional self-referent ratings, and were followed up 8 weeks later. In Study 1, both the low and high dysphoric participants demonstrated emotional reasoning and there were no significant differences in scores on the emotional reasoning task between the low and high dysphoric groups. In Study 2, self-referent emotional reasoning interpretations showed small-sized positive correlations with depression symptoms. Emotional reasoning tendencies were stable across an 8-week interval although not predictive of subsequent depressive symptoms. Further, anxiety symptoms were independently associated with emotional reasoning and emotional reasoning was not associated with anxiety sensitivity, alexithymia, or deductive reasoning tendencies. The implications of these findings are discussed, including the possibility that while all individuals may engage in emotional reasoning, self-referent emotional reasoning may be associated with increased levels of depressive symptoms.

Emotional Reasoning Processes and Dysphoric Mood: Cross-Sectional and Prospective Relationships

Science.gov (United States)

Berle, David; Moulds, Michelle L.

2013-01-01

Emotional reasoning refers to the use of subjective emotions, rather than objective evidence, to form conclusions about oneself and the world [1]. Emotional reasoning appears to characterise anxiety disorders. We aimed to determine whether elevated levels of emotional reasoning also characterise dysphoria. In Study 1, low dysphoric (BDI-II≤4; n = 28) and high dysphoric (BDI-II ≥14; n = 42) university students were administered an emotional reasoning task relevant for dysphoria. In Study 2, a larger university sample were administered the same task, with additional self-referent ratings, and were followed up 8 weeks later. In Study 1, both the low and high dysphoric participants demonstrated emotional reasoning and there were no significant differences in scores on the emotional reasoning task between the low and high dysphoric groups. In Study 2, self-referent emotional reasoning interpretations showed small-sized positive correlations with depression symptoms. Emotional reasoning tendencies were stable across an 8-week interval although not predictive of subsequent depressive symptoms. Further, anxiety symptoms were independently associated with emotional reasoning and emotional reasoning was not associated with anxiety sensitivity, alexithymia, or deductive reasoning tendencies. The implications of these findings are discussed, including the possibility that while all individuals may engage in emotional reasoning, self-referent emotional reasoning may be associated with increased levels of depressive symptoms. PMID:23826276

Inductive Reasoning and Writing

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Rooks, Clay; Boyd, Robert

2003-01-01

Induction, properly understood, is not merely a game, nor is it a gimmick, nor is it an artificial way of explaining an element of reasoning. Proper understanding of inductive reasoning--and the various types of reasoning that the authors term inductive--enables the student to evaluate critically other people's writing and enhances the composition…

Major Accidents (Gray Swans) Likelihood Modeling Using Accident Precursors and Approximate Reasoning.

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Khakzad, Nima; Khan, Faisal; Amyotte, Paul

2015-07-01

Compared to the remarkable progress in risk analysis of normal accidents, the risk analysis of major accidents has not been so well-established, partly due to the complexity of such accidents and partly due to low probabilities involved. The issue of low probabilities normally arises from the scarcity of major accidents' relevant data since such accidents are few and far between. In this work, knowing that major accidents are frequently preceded by accident precursors, a novel precursor-based methodology has been developed for likelihood modeling of major accidents in critical infrastructures based on a unique combination of accident precursor data, information theory, and approximate reasoning. For this purpose, we have introduced an innovative application of information analysis to identify the most informative near accident of a major accident. The observed data of the near accident were then used to establish predictive scenarios to foresee the occurrence of the major accident. We verified the methodology using offshore blowouts in the Gulf of Mexico, and then demonstrated its application to dam breaches in the United Sates. © 2015 Society for Risk Analysis.

Negative emotions can attenuate the influence of beliefs on logical reasoning.

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Goel, Vinod; Vartanian, Oshin

2011-01-01

Although the influence of beliefs on logical reasoning is well documented, how emotions modulate the effect of beliefs during reasoning remains unexamined. We instructed participants to reason about syllogisms involving neutral or emotionally charged content. We also manipulated the consistency of beliefs with logical validity. When content was neutral, participants exhibited the belief-bias effect observed in previous studies of reasoning. In contrast, when confronted with emotionally charged content participants were less likely to be influenced by their beliefs. Our results suggest that under certain conditions negative emotions can attenuate the influence of beliefs during logical reasoning. Drawing on the affect infusion model, we attribute this effect to a more vigilant, systematic scrutiny of beliefs in the presence of negative emotions. © 2010 Psychology Press, an imprint of the Taylor & Francis Group, an Informa business

Measuring Relational Reasoning

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

2016-01-01

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

Addressing Challenges in Urban Teaching, Learning and Math Using Model-Strategy-Application with Reasoning Approach in Lingustically and Culturally Diverse Classrooms

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Wu, Zhonghe; An, Shuhua

2016-01-01

This study examined the effects of using the Model-Strategy-Application with Reasoning Approach (MSAR) in teaching and learning mathematics in linguistically and culturally diverse elementary classrooms. Through learning mathematics via the MSAR, students from different language ability groups gained an understanding of mathematics from creating…

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.

Attitudes and exercise adherence: test of the Theories of Reasoned Action and Planned Behaviour.

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Smith, R A; Biddle, S J

1999-04-01

Three studies of exercise adherence and attitudes are reported that tested the Theory of Reasoned Action and the Theory of Planned Behaviour. In a prospective study of adherence to a private fitness club, structural equation modelling path analysis showed that attitudinal and social normative components of the Theory of Reasoned Action accounted for 13.1% of the variance in adherence 4 months later, although only social norm significantly predicted intention. In a second study, the Theory of Planned Behaviour was used to predict both physical activity and sedentary behaviour. Path analyses showed that attitude and perceived control, but not social norm, predicted total physical activity. Physical activity was predicted from intentions and control over sedentary behaviour. Finally, an intervention study with previously sedentary adults showed that intentions to be active measured at the start and end of a 10-week intervention were associated with the planned behaviour variables. A multivariate analysis of variance revealed no significant multivariate effects for time on the planned behaviour variables measured before and after intervention. Qualitative data provided evidence that participants had a positive experience on the intervention programme and supported the role of social normative factors in the adherence process.

The Christological Ontology of Reason

DEFF Research Database (Denmark)

Nissen, Ulrik Becker

2006-01-01

Taking the startingpoint in an assertion of an ambiguity in the Lutheran tradition’s assessment of reason, the essay argues that the Kantian unreserved confidence in reason is criticised in Bonhoeffer. Based upon a Christological understanding of reason, Bonhoeffer endorses a view of reason which...... is treated in the essay. Here it is argued that Bonhoeffer may be appropriated in attempting to outline a Christological ontology of reason holding essential implications for the sources and conditions of public discourse....

Exploring students’ adaptive reasoning skills and van Hiele levels of geometric thinking: a case study in geometry

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Rizki, H. T. N.; Frentika, D.; Wijaya, A.

2018-03-01

This study aims to explore junior high school students’ adaptive reasoning and the Van Hiele level of geometric thinking. The present study was a quasi-experiment with the non-equivalent control group design. The participants of the study were 34 seventh graders and 35 eighth graders in the experiment classes and 34 seventh graders and 34 eighth graders in the control classes. The students in the experiment classes learned geometry under the circumstances of a Knisley mathematical learning. The data were analyzed quantitatively by using inferential statistics. The results of data analysis show an improvement of adaptive reasoning skills both in the grade seven and grade eight. An improvement was also found for the Van Hiele level of geometric thinking. These results indicate the positive impact of Knisley learning model on students’ adaptive reasoning skills and Van Hiele level of geometric thinking.

Real Objects Can Impede Conditional Reasoning but Augmented Objects Do Not.

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Sato, Yuri; Sugimoto, Yutaro; Ueda, Kazuhiro

2018-03-01

In this study, Knauff and Johnson-Laird's (2002) visual impedance hypothesis (i.e., mental representations with irrelevant visual detail can impede reasoning) is applied to the domain of external representations and diagrammatic reasoning. We show that the use of real objects and augmented real (AR) objects can control human interpretation and reasoning about conditionals. As participants made inferences (e.g., an invalid one from "if P then Q" to "P"), they also moved objects corresponding to premises. Participants who moved real objects made more invalid inferences than those who moved AR objects and those who did not manipulate objects (there was no significant difference between the last two groups). Our results showed that real objects impeded conditional reasoning, but AR objects did not. These findings are explained by the fact that real objects may over-specify a single state that exists, while AR objects suggest multiple possibilities. Copyright © 2017 Cognitive Science Society, Inc.

Designing to support reasoned imagination through embodied metaphor

NARCIS (Netherlands)

Antle, A.N. (Alissa); Corness, G.; Bakker, S.; Droumeva, M.; Hoven, van den E.A.W.H.; Bevans, A.; Bryan-Kinns, N.

2009-01-01

Supporting users' reasoned imagination in sense making during interaction with tangible and embedded computation involves supporting the application of their existing mental schemata in understanding new forms of interaction. Recent studies that include an embodied metaphor in the interaction model,

Human Commercial Models' Eye Colour Shows Negative Frequency-Dependent Selection.

Directory of Open Access Journals (Sweden)

Isabela Rodrigues Nogueira Forti

Full Text Available In this study we investigated the eye colour of human commercial models registered in the UK (400 female and 400 male and Brazil (400 female and 400 male to test the hypothesis that model eye colour frequency was the result of negative frequency-dependent selection. The eye colours of the models were classified as: blue, brown or intermediate. Chi-square analyses of data for countries separated by sex showed that in the United Kingdom brown eyes and intermediate colours were significantly more frequent than expected in comparison to the general United Kingdom population (P<0.001. In Brazil, the most frequent eye colour brown was significantly less frequent than expected in comparison to the general Brazilian population. These results support the hypothesis that model eye colour is the result of negative frequency-dependent selection. This could be the result of people using eye colour as a marker of genetic diversity and finding rarer eye colours more attractive because of the potential advantage more genetically diverse offspring that could result from such a choice. Eye colour may be important because in comparison to many other physical traits (e.g., hair colour it is hard to modify, hide or disguise, and it is highly polymorphic.

Teaching for Ethical Reasoning

Science.gov (United States)

Sternberg, Robert J.

2012-01-01

This article argues for the importance of teaching for ethical reasoning. Much of our teaching is in vain if it is not applied to life in an ethical manner. The article reviews lapses in ethical reasoning and the great costs they have had for society. It proposes that ethical reasoning can be taught across the curriculum. It presents an eight-step…

Reasons to Use Virtual Reality in Education and Training Courses and a Model to Determine When to Use Virtual Reality

Science.gov (United States)

Pantelidis, Veronica S.

2009-01-01

Many studies have been conducted on the use of virtual reality in education and training. This article lists examples of such research. Reasons to use virtual reality are discussed. Advantages and disadvantages of using virtual reality are presented, as well as suggestions on when to use and when not to use virtual reality. A model that can be…

Perception of Risk and Terrorism-Related Behavior Change: Dual Influences of Probabilistic Reasoning and Reality Testing

Science.gov (United States)

Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew; Clough, Peter

2017-01-01

The present study assessed the degree to which probabilistic reasoning performance and thinking style influenced perception of risk and self-reported levels of terrorism-related behavior change. A sample of 263 respondents, recruited via convenience sampling, completed a series of measures comprising probabilistic reasoning tasks (perception of randomness, base rate, probability, and conjunction fallacy), the Reality Testing subscale of the Inventory of Personality Organization (IPO-RT), the Domain-Specific Risk-Taking Scale, and a terrorism-related behavior change scale. Structural equation modeling examined three progressive models. Firstly, the Independence Model assumed that probabilistic reasoning, perception of risk and reality testing independently predicted terrorism-related behavior change. Secondly, the Mediation Model supposed that probabilistic reasoning and reality testing correlated, and indirectly predicted terrorism-related behavior change through perception of risk. Lastly, the Dual-Influence Model proposed that probabilistic reasoning indirectly predicted terrorism-related behavior change via perception of risk, independent of reality testing. Results indicated that performance on probabilistic reasoning tasks most strongly predicted perception of risk, and preference for an intuitive thinking style (measured by the IPO-RT) best explained terrorism-related behavior change. The combination of perception of risk with probabilistic reasoning ability in the Dual-Influence Model enhanced the predictive power of the analytical-rational route, with conjunction fallacy having a significant indirect effect on terrorism-related behavior change via perception of risk. The Dual-Influence Model possessed superior fit and reported similar predictive relations between intuitive-experiential and analytical-rational routes and terrorism-related behavior change. The discussion critically examines these findings in relation to dual-processing frameworks. This

Perception of Risk and Terrorism-Related Behavior Change: Dual Influences of Probabilistic Reasoning and Reality Testing.

Science.gov (United States)

Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew; Clough, Peter

2017-01-01

The present study assessed the degree to which probabilistic reasoning performance and thinking style influenced perception of risk and self-reported levels of terrorism-related behavior change. A sample of 263 respondents, recruited via convenience sampling, completed a series of measures comprising probabilistic reasoning tasks (perception of randomness, base rate, probability, and conjunction fallacy), the Reality Testing subscale of the Inventory of Personality Organization (IPO-RT), the Domain-Specific Risk-Taking Scale, and a terrorism-related behavior change scale. Structural equation modeling examined three progressive models. Firstly, the Independence Model assumed that probabilistic reasoning, perception of risk and reality testing independently predicted terrorism-related behavior change. Secondly, the Mediation Model supposed that probabilistic reasoning and reality testing correlated, and indirectly predicted terrorism-related behavior change through perception of risk. Lastly, the Dual-Influence Model proposed that probabilistic reasoning indirectly predicted terrorism-related behavior change via perception of risk, independent of reality testing. Results indicated that performance on probabilistic reasoning tasks most strongly predicted perception of risk, and preference for an intuitive thinking style (measured by the IPO-RT) best explained terrorism-related behavior change. The combination of perception of risk with probabilistic reasoning ability in the Dual-Influence Model enhanced the predictive power of the analytical-rational route, with conjunction fallacy having a significant indirect effect on terrorism-related behavior change via perception of risk. The Dual-Influence Model possessed superior fit and reported similar predictive relations between intuitive-experiential and analytical-rational routes and terrorism-related behavior change. The discussion critically examines these findings in relation to dual-processing frameworks. This

Perception of Risk and Terrorism-Related Behavior Change: Dual Influences of Probabilistic Reasoning and Reality Testing

Directory of Open Access Journals (Sweden)

Andrew Denovan

2017-10-01

Full Text Available The present study assessed the degree to which probabilistic reasoning performance and thinking style influenced perception of risk and self-reported levels of terrorism-related behavior change. A sample of 263 respondents, recruited via convenience sampling, completed a series of measures comprising probabilistic reasoning tasks (perception of randomness, base rate, probability, and conjunction fallacy, the Reality Testing subscale of the Inventory of Personality Organization (IPO-RT, the Domain-Specific Risk-Taking Scale, and a terrorism-related behavior change scale. Structural equation modeling examined three progressive models. Firstly, the Independence Model assumed that probabilistic reasoning, perception of risk and reality testing independently predicted terrorism-related behavior change. Secondly, the Mediation Model supposed that probabilistic reasoning and reality testing correlated, and indirectly predicted terrorism-related behavior change through perception of risk. Lastly, the Dual-Influence Model proposed that probabilistic reasoning indirectly predicted terrorism-related behavior change via perception of risk, independent of reality testing. Results indicated that performance on probabilistic reasoning tasks most strongly predicted perception of risk, and preference for an intuitive thinking style (measured by the IPO-RT best explained terrorism-related behavior change. The combination of perception of risk with probabilistic reasoning ability in the Dual-Influence Model enhanced the predictive power of the analytical-rational route, with conjunction fallacy having a significant indirect effect on terrorism-related behavior change via perception of risk. The Dual-Influence Model possessed superior fit and reported similar predictive relations between intuitive-experiential and analytical-rational routes and terrorism-related behavior change. The discussion critically examines these findings in relation to dual

Ability Of Mathematical Reasoning in SMK 10th Grade with LAPS- Heuristic using Performance Assessment

OpenAIRE

Aulia Nur Arivina; Masrukan Masrukan; Ardhi Prabowo

2017-01-01

The purposes of this research are: (1) Test the learning with LAPS-Heuristic model using performance assessment on 10th grade of Trigonometry material is complete, (2) to test the difference of students' mathematical reasoning ability on 10th grade of Trigonometry material between the learning model of LAPS-Heuristic using performance assessment, LAPS-Heuristic learning model with Expository learning model, (3) test the ability of mathematical reasoning with learning model of LAPS-Heuristik o...

Temporal dimension in cognitive models

International Nuclear Information System (INIS)

Decortis, F.; Cacciabue, P.C.

1988-01-01

Increased attention has been given to the role of humans in nuclear power plant safety, but one aspect seldom considered is the temporal dimension of human reasoning. Time is recognized as crucial in human reasoning and has been the subject of empirical studies where cognitive mechanisms and strategies to face the temporal dimension have been studied. The present study shows why temporal reasoning is essential in Human Reliability Analysis and how it could be introduced in a human model. Accounting for the time dimension in human behaviour is discussed first, with reference to proven field studies. Then, theoretical modelling of the temporal dimension in human reasoning and its relevance in simulation of cognitive activities of plant operator is discussed. Finally a Time Experience Model is presented

Case-Based Reasoning on E-Community Knowledge

OpenAIRE

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

2013-01-01

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

MENUMBUHKAN DAYA NALAR ( POWER OF REASON SISWA MELALUI PEMBELAJARAN ANALOGI MATEMATIKA

Directory of Open Access Journals (Sweden)

Rahayu Kariadinata

2012-02-01

Full Text Available Learning mathematical analogy is one alternative learning that can be applied in order to cultivate the power of reason (power of reason students. Through mathematical analogy students are required to be able to look for similarities or relationship nature of the two concepts are the same or different by comparison, then draw a conclusion from the similitude. Thus the analogy can be used as an explanation or as the basis of reasoning. Before starting the analogy of learning mathematics, teachers should examine the ability of understanding mathematical concepts of students, because of the level of understanding of students will affect the power of reason. Tasks (problems mathematical analogy included non-routine matter, therefore the required readiness of teachers to make it. In each question contained mathematical analogy same or different concepts, so it takes quite a lot of material. Steps to make about the mathematical analogy, are: a assemble all the concepts in mathematics student has learned; b Similarly stacking properties / relationships contained in any concept, and c select materials that have a nature / relationship analogous. In this paper is given two forms of matter of mathematical analogy is the analogy of mathematical models and mathematical analogy 1 models 2. Learning mathematical analogy should be carried out after a number of concepts learned. It is better to be given in classes end for many of the concepts that have been learned by the students. Reasoning power (power of reason the student becomes an important part in the process of learning to drive them toward their future as citizens are intelligent, which will be led by the power of reason (the brain and not by the strength (muscle only. As noted by former US President Thomas Jefferson (in Copi, 1978: vii, which states: "In a republican nation, Whose citizens are to be led by reason and persuasion and not by force, the art of reasoning Becomes of first importance"

Political rationality: Young Danish and Norwegian immigrant citizens and their political reasoning

DEFF Research Database (Denmark)

Solhaug, Trond; Kristensen, Niels Nørgaard

2012-01-01

combining identities, emotions, and information is suggested and examined empirically. In a qualitative study the reflectivity of the students and their willingness to act as rational and responsible citizens is evaluated. Based on a selection of young Danish and Norwegian immigrant students, the dynamics......This article aims to uncover the dynamics of political reasoning among young immigrants. How do they people reason about the larger social and political world around them and what rationalities are in play? A dynamic approach is used to analyze cognitive functioning. A model of political reasoning...... between the elements of the model are explored. In the analysis, some identities play a decisive role, while emotions seem fairly often to be the trigger and the mechanism of political action....

Cognitive and Metacognitive Aspects of Proportional Reasoning

Science.gov (United States)

Modestou, Modestina; Gagatsis, Athanasios

2010-01-01

In this study we attempt to propose a new model of proportional reasoning based both on bibliographical and research data. This is impelled with the help of three written tests involving analogical, proportional, and non-proportional situations that were administered to pupils from grade 7 to 9. The results suggest the existence of a…

Using a Model to Describe Students' Inductive Reasoning in Problem Solving

Science.gov (United States)

Canadas, Maria C.; Castro, Encarnacion; Castro, Enrique

2009-01-01

Introduction: We present some aspects of a wider investigation (Canadas, 2007), whose main objective is to describe and characterize inductive reasoning used by Spanish students in years 9 and 10 when they work on problems that involved linear and quadratic sequences. Method: We produced a test composed of six problems with different…

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

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

International Nuclear Information System (INIS)

Far, B.H.

1992-04-01

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

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.

Causal Reasoning with Mental Models

Science.gov (United States)

2014-08-08

The initial rubric is equivalent to an exclusive disjunction between the two causal assertions. It 488 yields the following two mental models: 489...are 575 important, whereas the functions of artifacts are important (Ahn, 1998). A genetic code is 576 accordingly more critical to being a goat than

OWL-based reasoning methods for validating archetypes.

Science.gov (United States)

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

2013-04-01

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

Social reasons for transport volume growth; Miksi autoliikenne kasvaa?

Energy Technology Data Exchange (ETDEWEB)

Tapio, P [Helsinki Univ., Helsinki (Finland)

1995-07-01

The carbon dioxide emission trend of transport may have bought the transport sector to a point where technical `end of pipe` solutions no longer reduce emissions enough. The growth of transport volume has been questioned. Growth has usually been explained by mathematical models, with trends of population and the Gross National Product as main explanatory factors. This article makes a case for a broader social perspective that the deterministic models. Social factors for transport volume growth can be divided into two categories - the `soft` individual and the `hard` societal. Societal reasons affect the alternatives from which individuals are able to choose. Individual reasons for behavior are knowledge, values, feelings, aesthetic aspects, routines and courage to change previous behavior. Societal reasons are the institutions of policy making, public administration, science, economy, media and citizen organizations. Some common sense `facts` about the private car friendly society are argued. Also some prospects of the European Union are discussed. The basic ideology of the EU of free transport of people, capital, goods and services may indeed grow the traffic volume in Finland. On the other hand the EU has planned to subvent more rail than road transport

Geometric Reasoning for Automated Planning

Science.gov (United States)

Clement, Bradley J.; Knight, Russell L.; Broderick, Daniel

2012-01-01

An important aspect of mission planning for NASA s operation of the International Space Station is the allocation and management of space for supplies and equipment. The Stowage, Configuration Analysis, and Operations Planning teams collaborate to perform the bulk of that planning. A Geometric Reasoning Engine is developed in a way that can be shared by the teams to optimize item placement in the context of crew planning. The ISS crew spends (at the time of this writing) a third or more of their time moving supplies and equipment around. Better logistical support and optimized packing could make a significant impact on operational efficiency of the ISS. Currently, computational geometry and motion planning do not focus specifically on the optimized orientation and placement of 3D objects based on multiple distance and containment preferences and constraints. The software performs reasoning about the manipulation of 3D solid models in order to maximize an objective function based on distance. It optimizes for 3D orientation and placement. Spatial placement optimization is a general problem and can be applied to object packing or asset relocation.