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Psychology of learning and motivation. Volume 61.
Psychology of Learning and Motivation publishes empirical and theoretical contributions in cognitive and experimental psychology, ranging from classical and instrumental conditioning to complex learning and problem solving. Each chapter thoughtfully integrates the writings of leading contributors, w...
| Clasificación: | Libro Electrónico |
|---|---|
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Amsterdam :
Academic Press,
2014.
|
| Temas: | |
| Acceso en línea: | Texto completo Texto completo |
Tabla de Contenidos:
- Front Cover; The Psychology of Learning and Motivation; Copyright; Contents; Contributors; Chapter One: Descriptive and Inferential Problems of Induction: Toward a Common Framework; 1. Introduction; 2. Theory-Based and Similarity-Based Inductive Inference; 3. Induction as Statistical Inference: Descriptive and Inferential Problems; 4. Inductive and Transductive Inference: Sample and Population Statistics; 5. Using Transductive Inference; 6. Summary: Transductive and Evidential Theories of Inference; 7. Distinguishing Transductive and Evidential Inferences; 7.1. People and Statistics
- 8. Developing Solutions to Descriptive Problems8.1. Correlations and Associations; 8.2. Componential Analysis; 8.3. Transition Probabilities; 8.4. Absolute to Relational Statistics; 8.5. Global to Specific Relations; 8.6. Simple to Complex; 8.7. Summary of Solutions to Descriptive Problems; 9. Solutions to Inferential Problems; 9.1. Transductive Inference; 9.2. Bayesian Inference; 9.3. Between Transductive and Evidential Inference; 9.4. Communicative Bias; 9.5. Intentional Versus Incidental Learning; 9.6. Summary of Solutions to Inferential Problems; 10. Summary and Conclusions; References
- Chapter Two: What Does It Mean to be Biased: Motivated Reasoning and Rationality1. The Notion of Bias; 1.1. ``Bias� � in Psychology; 1.1.1. Origins; 1.1.2. The 1960s: Wason� s Confirmation Bias in Rule Induction; 1.1.3. The 1960s: Conservatism; 1.1.4. Heuristics and Biases; 1.1.5. Social Psychology; 1.1.6. Summary; 1.2. The Notion of Bias in Statistics; 1.2.1. Bias as Expected Deviation; 1.2.2. Signal Detection Theory; 1.3. Implications; 2. When is a Bias a Bias?; 2.1. Understanding Bias: Scope, Sources, and Systematicity; 2.1.1. The Pitfalls of Moderators
- 3. Measuring Bias: The Importance of Optimal Models3.1. Bayesian Belief Revision; 3.2. Divergence of Normative Predictions and Experimenter Intuition; 3.2.1. Unrealistic Comparative Optimism; 3.2.2. Optimistic Belief Updating; 3.3. Bayes and Experimental Demonstrations of Motivated Reasoning; 4. Conclusions; Acknowledgment; References; Chapter Three: Probability Matching, Fast and Slow; 1. Introduction; 2. Dumb Matching; 3. Smart Maximizing; 4. Smart Matching; 5. Dumb Maximizing; 6. Conclusion; Acknowledgments; References; Chapter Four: Cognition in the Attention Economy; 1. Introduction
- 1.1. The Current Problem1.2. Resources and Bottlenecks; 1.3. Automatic and Controlled Processing; 1.4. Information Processing and a Model of the Effect of the Attention Economy on Cognition; 2. What are the Consequences of an Attention Debt?; 2.1. Safety; 2.2. Aesthetics and Creativity; 2.2.1. Aesthetics; 2.2.2. Creativity; 2.3. The Experience and Regulation of Emotion; 3. Why do We Overspend our Attention Budget?; 3.1. Our Social Brain; 3.2. The Value of Immediate Information; 3.3. Self-Control and Willpower; 4. Can We Expand the Attention Economy?; 4.1. Mental and Behavioral Prosthetics