Sentence examples for calculation learning from inspiring English sources

"Dementia" is defined as a "clinical syndrome due to disease of the brain, usually of a progressive nature, which leads to disturbances of multiple higher cortical functions, including memory, thinking, orientation, comprehension, calculation, learning capacity, language, and judgment".

In the current study dementia was defined as a syndrome caused by disease of the brain, usually of a chronic or progressive nature, in which there is disturbance of multiple higher cortical functions, including memory, thinking, orientation, comprehension, calculation, learning capacity, language and judgment [ 13].

Calculation learning is characterized by the manipulation of numbers according to set procedures or algorithms involving one or several mathematical operations (e.g., 32 − 17 + 5 = 20).

This operator was not blinded to the measurements but the calculation of learning curve was a post hoc analysis and not the initial intention of the original study.

Integrated neuro-fuzzy systems can unite with the human-like knowledge representation and clarification abilities of fuzzy systems with the parallel calculation and learning abilities of neural networks (Jang and Sun 1995).

No calculation of learning gains is without problems, so we also repeated the analyses described in Data Analysis, using each of the four calculations of learning gains.

TV programs with fast changing pictures and complicated issues such as calculation or learning new things triggered fatigue: "The brain becomes worse from all the concentration, whether it's watching TV or reading.

AD is a degenerative brain syndrome characterized by a progressive decline in memory, thinking, comprehension, calculation, language, learning capacity, and judgment sufficient to impair personal activities of daily living.

The calculations of learning gains were highly intercorrelated (see the Supplemental Material), with Pearson's r ranging from 0.79 0.99 (all p values < 0.001; p was calculated using the Holm-Bonferonni method to account for error associated with multiple comparisons).

To decide how best to calculate how much students learned about natural selection, we examined the intercorrelations among pre- and posttest scores and four possible calculations of learning gains: effect size (Cohen's d), average normalized gain, percent change, and raw change (Table 1).

Additionally, we examined linear regression models using other calculations of learning gains, as well as a model that replaced the continuous weekly frequency of specific active-learning exercises with the more general categorical use of any active learning, to see if results remained the same.