Learning and Memory

ISBN-13: 9781108428613 / Angielski / Twarda / 2020 / 534 str.

David A. Lieberman

Opis

The first text to integrate behavioral and cognitive approaches to learning and memory, this engaging textbook emphasizes human research, reflecting the field's evolution. Learning and Memory also recognizes the vital contribution of animal research, covering all historically important studies. Written in a lively and conversational style, this second edition encourages students to think critically. One example is its exploration of the Rescorla-Wagner model, the most important theory of conditioning, now further streamlined to improve student comprehension. Another is the addition of critical-thinking questions, which encourage students to evaluate their reactions to the material they've read, and relate findings to their own lives. Research includes an emphasis on practical applications such as treatments for phobias, addictions, and autism; the arguments for and against corporal punishment; whether recovered memories and eyewitness testimony should be believed; and effective techniques for studying. The text concludes with an overview of neural networks and deep learning.

Recenzje

'Lieberman provides an excellent introduction to the psychological science of learning and memory, from historical developments to current research. He also shows how this knowledge can be used to understand behavior in the real world. The breadth of coverage is impressive; whereas most textbooks of this kind focus mostly on either learning or memory, Lieberman covers both in equal depth. His conversational style makes this a very accessible read.' John Green, University of Vermont

Spis treści

Part I. Learning: 1. Core Assumptions; 2. Classical Conditioning; 3. Conditioning Principles and Theories; 4. Conditioning Applications; 5 Reinforcement; 6. Reinforcement Applications; 7. Punishment; 8. Theories of Reinforcement; Part II. Memory: 9. Memory: An Introduction; 10. Working Memory; 11. Long-term Memory; 12. Retrieval; 13. Applications; Part III. Neural Foundations: 14. From Neurons to Neural Networks.