Sentence examples for constraints on learning from inspiring English sources

Sadtler, P.T. et al. Neural constraints on learning.

Though developments in technology have overcome the constraints on learning space, an inability to appropriately exploit the technology may make it an obstacle to learning instead.

Specific topics include the application of the theory of evolution to behavior, associative learning, biological constraints on learning, methods for studying the cognitive abilities of animals, levels of representation, ecological influences on cognition, and evidence of consciousness in animals.

Empiricists would expect that domain-specific priors are themselves learnable by Bayesian methods from experience plus domain-general constraints on learning.

Future research should establish the constraints on learning about other-race faces.

If done well, it could widely broaden participation in cheminformatics learning, removing most if not all of these constraints on learning, and enabling the wisdom gained over the long history of the field to impact a wide range of practitioners and disciplines.

The similarity of this constraint on learning in rats and pigeons suggests that it involves a fundamental attentional and incentive-motivational process with widespread species generality.

Given that previous studies showed a strong retinotopic constraint on learning [12], [13], we recorded gaze coordinates and provided observers feedback on their eye fixation, to avoid potentially diluting any learning due to eye movements and inconsistent retinal positioning of the stimuli (see Display).

Learn and keep on learning.

The analysis of the use of video as a mediating artefact drew on an interpretive approach framed as authentic participant-centered inquiry and employed multiple theoretical frameworks to generate perspectives on the affordances and constraints of learning from video.

Then binary codes can be learned by the minimization of an objective function defined over classification error, with additional constraints on the learning objective to make each hash bit carry as much information as possible.