Toward a Science of Effective Cognitive Training

By C. Smid, J. Karbach, Nikolaus Steinbeis. Current Directions in Psychological Science, 2020

89 citations recorded by the source corpus.

A long-standing question in the behavioral sciences is whether cognitive functions can be improved through dedicated training. It is uncontested that training programs can lead to near transfer, meaning increased performance on untrained tasks involving similar cognitive functions. However, whether training also leads to far transfer, meaning increased performance on loosely related untrained tasks or even activities of daily living, is still hotly debated. Here, we review the extant literature and, in particular, the most recent meta-analytic evidence and argue that the ongoing crisis in the field of cognitive-training research may benefit from taking a more mechanistic approach to studying the effectiveness of training. We propose that (a) adopting a more rigorous theoretical framework that builds on a process-based account of training and transfer, (b) considering the role of individual differences in the responsiveness to training, and (c) drawing on Bayesian models of development may help to solve controversial issues in the field and lead the way to designing and implementing more effective training protocols.

Subfields: Artificial Intelligence, Developmental and Educational Psychology, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/3328df78711dd078cf72b82a0b687d360a5573f5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

  1. Torkel Klingberg
  2. Julia Ericson
  3. S. Palva
  4. Matias J. Palva

In Experimental and Cognitive Psychology

  1. Torkel Klingberg
  2. A. Diamond
  3. R. Engle
  4. Zach Shipstead

Citations in the corpus