Search results for "Deductive reasoning"

Robotics and Virtual Worlds: An Experiential Learning Lab

2013

Aim of the study was to investigate the cognitive processes involved and stimulated by educational robotics (LEGO® robots and Kodu Game Lab) in lower secondary school students. Results showed that LEGO® and KGL artifacts involve specific cognitive and academic skills. In particular the use of LEGO® is related to deductive reasoning, speed of processing visual targets, reading comprehension and geometrical problem solving; the use of KGL is related to visual-spatial working memory, updating skills and reading comprehension. Both technologies, moreover, are effective in the improvement of visual-spatial working memory. Implications for Human-Robot Interaction and BICA challenge are discussed.

Registered nurses' clinical reasoning in home healthcare clinical practice: A think-aloud study with protocol analysis.

2016

Abstract Background The home healthcare context can be unpredictable and complex, and requires registered nurses with a high level of clinical reasoning skills and professional autonomy. Thus, additional knowledge about registered nurses' clinical reasoning performance during patient home care is required. Objectives The aim of this study is to describe the cognitive processes and thinking strategies used by recently graduated registered nurses while caring for patients in home healthcare clinical practice. Design An exploratory qualitative think-aloud design with protocol analysis was used. Settings Home healthcare visits to patients with stroke, diabetes, and chronic obstructive pulmonary…

The Development of Conditional Reasoning: A Mental Model Account

2002

Abstract Conditional (if-then) reasoning is one of the key components of logical reasoning. Studies examining the way that children and adults make conditional inferences have shown that while there are some clear developmental patterns, there is also a great deal of variation in performance due to factors such as problem content. Such variation is difficult to model without an explicit process model. In the following we propose a variant of mental model theory (Johnson-Laird, 1983) that can explain much of the empirical data. This model suggests that the development of conditional reasoning can be explained, at least partly, by such factors as the capacity of working memory, the range of k…

Probabilistic Logic under Coherence‚ Model−Theoretic Probabilistic Logic‚ and Default Reasoning in System P

2016

We study probabilistic logic under the viewpoint of the coherence principle of de Finetti. In detail, we explore how probabilistic reasoning under coherence is related to model-theoretic probabilistic reasoning and to default reasoning in System P. In particular, we show that the notions of g-coherence and of g-coherent entailment can be expressed by combining notions in model-theoretic probabilistic logic with concepts from default reasoning. Moreover, we show that probabilistic reasoning under coherence is a generalization of default reasoning in System P. That is, we provide a new probabilistic semantics for System P, which neither uses infinitesimal probabilities nor atomic bound (or bi…

The complexity of finite model reasoning in description logics

2005

AbstractWe analyse the complexity of finite model reasoning in the description logic ALCQI, i.e., ALC augmented with qualifying number restrictions, inverse roles, and general TBoxes. It turns out that all relevant reasoning tasks such as concept satisfiability and ABox consistency are ExpTime-complete, regardless of whether the numbers in number restrictions are coded unarily or binarily. Thus, finite model reasoning with ALCQI is not harder than standard reasoning with ALCQI.

Developmental and content effects in reasoning with causal conditionals.

2002

Abstract Two predictions derived from Markovits and Barrouillet's (2001) developmental model of conditional reasoning were tested in a study in which 72 twelve-year-olds, 80 fifteen-year-olds, and 104 adults received a paper-and-pencil test of conditional reasoning with causal premises (“if cause P then effect Q”). First, we predicted that conditional premises would induce more correct uncertainty responses to the Affirmation of the consequent and Denial of the antecedent forms when the antecedent term is weakly associated to the consequent than when the two are strongly associated and that this effect would decrease with age. Second, uncertainty responding to the Denial of the antecedent f…

Explanatory Reasoning: A Probabilistic Interpretation

2016

This paper deals with inference guided by explanatory considerations –specifically with the prospects for a probabilistic interpretation of it. After pointing out some differences between two sorts of explanatory reasoning – i.e.: abduction and “inference to the best explanation” – in the first section I distinguish two tasks: (a) to discern which explanation is the best one; (b) to assess whether the best explanation deserves to be legitimately believed. In Sect. 20.2 I discuss some recent definitions of explanatory power based on “reduction of uncertainty” (Schupbach and Sprenger 2011; Crupi and Tentori 2012). Even though a probabilistic framework is a promising option here, I will argue …

Integrating resolution—like procedures with Lukasiewicz implication

1993

We discuss some conceptual and technical problems raised by the attempt of integrating resolution-like procedures with the use of Lukukasiewicz implication Min{1, 1 – [a] + [b]} in an environment of approximate reasoning modelled by fuzzy logics.

Abductive Reasoning and Linguistic Meaning

2006

Probabilistic Logic under Coherence, Model-Theoretic Probabilistic Logic, and Default Reasoning

2001

We study probabilistic logic under the viewpoint of the coherence principle of de Finetti. In detail, we explore the relationship between coherence-based and model-theoretic probabilistic logic. Interestingly, we show that the notions of g-coherence and of g-coherent entailment can be expressed by combining notions in model-theoretic probabilistic logic with concepts from default reasoning. Crucially, we even show that probabilistic reasoning under coherence is a probabilistic generalization of default reasoning in system P. That is, we provide a new probabilistic semantics for system P, which is neither based on infinitesimal probabilities nor on atomic-bound (or also big-stepped) probabil…