Stages of information processing. Humans process information in stable stages, inputting sensory information to working and long-term memory and response generation. In many ways, people are information-processing machines whose thinking and behavior can be modeled by computers input-process-output models.

Selective perception. Our goals, expectations, and current understandings color our perceptions. They serve as filters to the world, and help to organize our cognitive structure.

Working memory. We are only able to think about five to seven chunks of information at a time.

Kinds of knowledge. Two kinds of knowledge are fundamental:

--Declarative knowledge (knowing that). Stored as propositions in semantic networks.

--Procedural knowledge (knowing how). Stored as IF-THEN rules and pattern-recognition templates.

These are often referred to as knowledge and skill.

In addition to declarative and procedural knowledge, other knowledge types have been identified, including attitudes, metacognition, schemas, mental models, beliefs, values, etc. In fact, cognitive theorists have been unable to agree upon a fixed set of knowledge types. Advances in neuroscience have added new perspectives on knowledge, according to brain processes and capabilities.

Skill compilation. Through repeated practice, skills become compiled or routinized. Several procedural steps are combined into a single whole, making performance easier and leaving cognitive resources available for other parts of a complex task. Un-learning a routinized procedure can be difficult, because details of task components are lost and have to be reconstructed. Automaticity is achieved when a second, simultaneous task can be performed without noticable impairment.

Meaningful encoding. Information is stored in long-term memory in ways that make it accessible for convenient retrieval.

--Chunking. Information is chunked as it becomes organized into meaningful units, making it easier to remember. Chunked information fits together better and helps us overcome limits to working memory.

--Elaboration: People make links between material and their prior knowledge through active thought and reflection. The more connections, the more meaningful the item.

Metacognition. Problem solving involves declarative and procedural knowledge, and something more. That we call metacognitive knowledge, involving self-monitoring, self-regulation, and when-and-where conditional knowledge (knowing when and where to deploy your strategies and knowledge). Metacognitive knowledge is more difficult to analyze and understand, but it is key to adaptive use of knowledge.

Motivation. Motivation is what makes people do what they do. Traditional explanations refer to instincts, drives, arousal, reinforcement, etc. Cognitive theorists rely on models of cognitive processing and structure to provide insight into motivation. Key concepts include incentives, self-efficacy, expectancy x value, success/failure attributions, and intrinsic versus extrinsic motivation.

Experts versus novices. Experts differ from novices in a number of respects, including:

--more domain-specific information to draw upon;

--more domain-specific problem-solving routines;

--a commitment to steady periods of deliberate practice (reflective practice with the specific intent of skill improvement).

Human development. Children grow in their knowledge and skill, interpretable as a series of stages. Children's stage growth can also be interpreted in information-processing terms, as increasing accumulation of procedural and declarative knowledge about the world. Adults also grow in their epistemological understanding; this growth can also be characterized in terms of stages, moving from fixed, authoritarian views of knowledge toward views that acknowledge the important roles of interpretation and perspective.

Metaphors for learning. Learning can be construed in different ways, including:

--response acquisition;

--knowledge acquisition;

--knowledge construction;

Each of these perspectives contributes something to our understanding; however, current cognitive theorists emphasize the view that learners actively construct meaning through their experiences, thereby creating new knowledge.

OTHER KEY CONCEPTS

Behavioral associative learning. Traditional behavioral perspectives include operant and conditional learning. Neobehaviorists apply behavioral technology to cognition. Thus modeling and reinforcement mechanisms become internal cognitive processes that mediate behavior.

Conceptual change. People make sense of their worlds by reference to schemas, mental models, and other complex memory structures. Differences between our experience and our schemas can prompt further inquiry and reflection to resolve the conflict. Learning can be seen as continued assimilaton and accommodation of new information into our schemas and cognitive structures.

Authentic learning. New knowledge is best learned through authentic interaction with the world and with other people. Knowledge learned outside a problem-solving context can often be inert-meaning it's unavailable for use when needed. The more closely our learning environment resembles the world of practice, the more likely learned knowledge will be useful and available.