Sentence examples for reasoning identify from inspiring English sources

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It was essential for students to recognize the various connections in logical thinking so that they could identify faulty reasoning, identify reliable evidence and construct explanations before they could refute or support a hypothesis – these were essential science process skills that fostered scientific inquiry (Curriculum Planning and Development Division [CPDD], 2013).

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Scientific reasoning ability is defined as the ability to demonstrate the patterns of formal operations including proportional reasoning, identifying and controlling variables, probabilistic reasoning, correlational reasoning, combinatorial reasoning, and hypothetico-deductive reasoning (Lawson 1982).

Lawson's Classroom Test of Scientific Reasoning (LCTSR; Lawson 1978, version 2000): This is a measure of scientific reasoning abilities, including proportional reasoning, identifying and controlling variables, probabilistic reasoning, correlational reasoning, and hypothetico-deductive reasoning.

In this study, we used the LCTSR, a measure of formal operational reasoning skills including proportional reasoning, identifying and controlling variables, probabilistic reasoning, correlational reasoning, and hypothetico-deductive reasoning.

OWL reasoning identified CDS rules with overlapping target populations but differing treatment recommendations.

Although inductive frameworks are often used to provide a scientific understanding of complicated systems, once inductive reasoning identifies key features of a system, they help generate and then tend to be replaced by frameworks that build on fundamental organizing principles.

Theories of practical reasoning which identify reasons for action solely with desires and beliefs so characterized — so-called Humean theories — are directed towards choosing actions, yet incompatible with actions being chosen.

Uses AI reasoning to identify what meeting times would best accommodate attendees given time zones.

We show that our results can be seamlessly applied to ontological reasoning and identify two classes of non-Horn ontologies that admit Datalog rewritings of polynomial and exponential size, respectively.

They used the case-base reasoning to identify a channel preferred by the secondary user.

And though I am enthusiastic about Nordenfelt's reasoning, I identify three weaknesses.

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