The psychology of learning and motivation. Volume 74 /

The Psychology of Learning and Motivation, Volume 74, the latest release in this ongoing series, features empirical and theoretical contributions in cognitive and experimental psychology, ranging from classical and instrumental conditioning, to complex learning and problem-solving.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Federmeier, Kara D. (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Amsterdam : Academic Press, 2021.
Colección:Psychology of learning and motivation ; v. 74.
Temas:
Learning, Psychology of.
Motivation (Psychology)
Motivation
Psychologie de l'apprentissage.
Motivation (Psychologie)
Learning, Psychology of
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Intro
  • The Psychology of Learning and Motivation
  • Copyright
  • Contents
  • Contributors
  • Chapter One: The role of working memory in long-term learning: Implications for childhood development
  • 1. Introduction
  • 2. Brief overview: Long-term learning
  • 2.1. Long-term learning is not an isolated cognitive skill
  • 2.2. The developmental trajectory of long-term learning has multiple influences
  • 3. Brief overview: Working memory
  • 3.1. What is working memory?
  • 3.2. Working memory training
  • 3.3. Theories of working memory
  • 4. The relationship between working and long-term memory
  • 4.1. Differences between typical working and long-term memory tests
  • 4.2. How are working and long-term memory related?
  • 5. The role of working memory and its limits in long-term learning
  • 5.1. Correlations between working memory performance and educational outcomes
  • 5.2. Does working memory act as a long-term memory bottleneck?
  • 5.3. Working memory, complexity and concept formation
  • 5.4. Working memory and task completion
  • 5.5. Does combining visual and non-visual materials improve long-term learning?
  • 5.6. Cognitive control and attention
  • 5.7. Working memory and strategic shifts
  • 6. How does long-term memory knowledge enhance working memory storage?
  • 6.1. Long-term memory knowledge enables working memory chunking
  • 6.2. The role of familiarity in working memory
  • 6.3. Diagnostic features
  • 6.4. Arbitrary associations
  • 7. Implications for practice
  • 8. Conclusions
  • References
  • Chapter Two: Learning to control tinnitus
  • 1. Introduction
  • 1.1. What is tinnitus?
  • 1.2. The tinnitus percept
  • 1.3. Assessing the impact of tinnitus
  • 2. Learning to habituate to tinnitus
  • 2.1. Personality factors
  • 3. Treatments to control tinnitus distress and facilitate habituation
  • 3.1. Placebo effect.
  • 3.2. Personality factors affecting habituation
  • 4. Neural correlates of tinnitus
  • 4.1. Impact of tinnitus on brain function
  • 4.2. Impact of tinnitus on neuroanatomy
  • 4.3. Interventions and brain imaging
  • 5. Models of tinnitus
  • 5.1. Tinnitus generation
  • 5.2. Modeling psychological impact
  • 5.3. Modulation of tinnitus by cognitive states-Predictions of the Husain model
  • 5.4. Comorbid psychological conditions exacerbate tinnitus severity
  • treating them reduces tinnitus severity
  • 6. Conclusion
  • Acknowledgments
  • References
  • Chapter Three: The attentional demands of combining comprehension and production in conversation
  • 1. Introduction
  • 2. Processes involved in turn-taking
  • 2.1. Content prediction
  • 2.2. Turn-end prediction
  • 2.3. Early response planning
  • 2.4. Articulation launching
  • 2.5. Interim summary
  • 3. Attention demands of conversation
  • 3.1. Attention demands of production
  • 3.2. Attention demands of comprehension
  • 3.3. Attention demands of combining production and comprehension
  • 4. Consequences of combining production and comprehension
  • 4.1. Associated costs
  • 4.2. Associated benefits
  • 5. Open questions
  • 6. Conclusion
  • References
  • Chapter Four: More than ``just a test��-Task-switching paradigms offer an early warning system for cognitive decline
  • 1. Cognitive control ability-An early warning system?
  • 2. Multidimensional structure of cognitive control processes
  • 3. Quantifying distinct components of cognitive control contributing to overt task performance
  • 4. Differentiating between proactive and reactive cognitive control processes
  • 5. Quantifying distinct components of cognitive control using task-switching paradigms
  • 6. EEG-based evidence for multiple proactive and reactive control processes contributing to task-switching performance
  • 6.1. Preparing to switch task.
  • 6.2. Implementing a prepared switch in task-set
  • 7. Using task-switching paradigms to assess cognitive control ability across the lifespan
  • 7.1. Middle childhood
  • 7.2. Adolescence
  • 7.3. Old age
  • 7.4. Increased prevalence of cardiovascular risk factors
  • 8. Using task-switching paradigms to assess cognitive control ability across clinical conditions
  • 9. Using task-switching paradigms to assess the effects of lifestyle on cognitive control ability
  • 10. What would an omnibus task-switching paradigm look like?
  • 11. What are the practicalities of rolling out such a testing protocol at scale?
  • 12. Conclusion: Is the task-switching paradigm a potential candidate for the ``canary in the coalmine��?
  • Acknowledgments
  • References
  • Chapter Five: Policy compression: An information bottleneck in action selection
  • 1. Introduction
  • 2. Action selection as a communication channel
  • 3. Compression as a trade-off between reward and complexity
  • 4. Behavioral signatures of policy compression
  • 4.1. Stochasticity
  • 4.2. Perseveration
  • 4.3. Response time
  • 4.4. Action chunking
  • 4.5. State chunking
  • 4.6. Navigation
  • 4.7. Psychiatry
  • 5. Neural signatures of policy compression
  • 6. Compression and learning
  • 7. Conclusion
  • Acknowledgments
  • Appendix
  • References
  • Chapter Six: Limited evidence for probability matching as a strategy in probability learning tasks
  • 1. Non-human animal probability learning
  • 1.1. Typical task design
  • 1.2. Findings
  • 1.3. Summary
  • 2. Human probability learning: Adults
  • 2.1. Typical task designs
  • 2.2. Findings
  • 2.3. Summary
  • 3. Human probability learning: Children
  • 3.1. Typical task design
  • 3.2. Findings
  • 3.3. Summary
  • 4. Implications of probability learning for other domains
  • 4.1. Probability learning and language development
  • 4.2. A note about generalization.
  • 4.3. Implications for other domains
  • 4.4. Implications for the process of science
  • 5. Conclusions
  • Acknowledgments
  • References
  • Chapter Seven: A review of uncertainty visualization errors: Working memory as an explanatory theory
  • 1. Introduction
  • 2. Visualization decision-making framework
  • 2.1. Visual array and attention
  • 2.2. Working memory
  • 2.3. Visual description
  • 2.4. Graph schemas
  • 2.5. Matching process
  • 2.6. Instantiated graph schema
  • 2.7. Message assembly
  • 2.8. Conceptual question
  • 2.9. Decision-making
  • 2.10. Behavior
  • 3. Uncertainty visualization errors
  • 3.1. Early-stage processing errors
  • 3.1.1. Boundaries=conceptual categories
  • 3.2. Middle-stage processing errors
  • 3.2.1. Schema errors in hurricane visualizations
  • 3.2.2. Deterministic construal errors
  • 3.3. Late-stage errors
  • 3.3.1. Framing errors: Probabilistic vs frequency
  • 4. Conclusions
  • References.

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