Cognition Psychology Lesson 7 PDF

THE ORGANIZATION OF KNOWLEDGE IN THE MIND Lesson 7 - COGNITIVE PSYCHOLOGY By: Krisette E. Romero, MPsy, RPm  LEARNING OBJECTIVES Distinguish between declarative knowledge and non- declarative knowledge. Describe integrative models for representing declarative and non-declarative knowledge. Kn...

THE ORGANIZATION OF KNOWLEDGE IN THE MIND Lesson 7 - COGNITIVE PSYCHOLOGY By: Krisette E. Romero, MPsy, RPm  LEARNING OBJECTIVES Distinguish between declarative knowledge and non- declarative knowledge. Describe integrative models for representing declarative and non-declarative knowledge. Know the types of individual and organizational incentives that will highly motivate employees. INTRODUCTION People with autism who have an extraordinary ability have been called autistic savants. Their abilities often leave us incredulous—they can multiply large numbers within a fraction of a second, remember huge amounts of data, or they can recall any detail with their photographic memory. But people who are autistic savants may actually not be that different from us. Research suggests that we may all possess these talents, but they are part of low-level information processing that we normally do not use because we think at a higher level that is concept-driven and allows for multisensory comparisons. Although we usually cannot consciously control our brain activity, studies have shown that people can learn to become sensitive to low-level processing and gain access to those early states of processing that are usually unconscious. This opens new possibilities for behaviour and self-awareness (Birbaumer, 1999). DECLARATIVE KNOWLEDGE VS. NON-DECLARATIVE KNOWLEDGE Declarative Knowledge Also known as Descriptive Knowledge Refers to knowledge that can be explicitly. It emphasizes “what” to do to solve a given problem. Examples include facts, concepts, and propositions. For instance, knowing that the sum of angles in a triangle is 180 degrees. Non-Declarative Knowledge Also known as Procedural Knowledge Concerns how a particular thing can be accomplished. It emphasizes “how” to do something to solve a problem. Examples include skills, habits, and practical know-how. For example, riding a bicycle or playing a musical instrument. ORGANIZATION OF DECLARATIVE KNOWLEDGE CONCEPT An idea about something that provides a means of understanding the world. A concept may be captured in a single word, such as apple. Each concept in turn relates to other concepts, such as apple, which relates to redness, roundness, or fruit. Concepts are not always stable but they change. Classical concepts are categories that can be readily defined through defining features, such as bachelor. Fuzzy concepts are categories that cannot be so easily defined, such as game or death. ORGANIZATION OF DECLARATIVE KNOWLEDGE CATEGORY Is a group of items into which different objects or concepts can be placed that belong together because they share some common features, or because they are all similar to a certain prototype. Natural categories are groupings that occur naturally in the world, like birds or trees. Artifact categories are groupings that are designed or invented by humans to serve particular purposes or functions. ORGANIZATION OF DECLARATIVE KNOWLEDGE Feature-Based Categories The classic view of categories disassembles a concept into a set of featural components. All those features are then necessary (and sufficient) to define the category (Katz, 1972; Katz & Fodor, 1963). This means that each feature is an essential element of the category. Together, the features uniquely define the category; they are defining features (or necessary attributes): For a thing to be an X, it must have that feature. Otherwise, it is not an “X.” Prototype Theory Prototype theory takes a different approach: grouping things together not by their defining features but rather by their similarity to an averaged model of the category. Crucial are characteristic features, which describe (characterize or typify) the prototype but are not necessary for it. Characteristic features commonly are present in typical examples of concepts, but they are not always present. Integrative Models for Representing Declarative and Non-Declarative Knowledge ACT-R Combines forms of mental representation is the ACT (adaptive control of thought) model of knowledge representation and information processing. The most recent version of ACT, ACT-R (where the R stands for rational), is a model of information processing that integrates a network representation for declarative knowledge and a production-system representation for procedural knowledge. In Anderson’s view, individual cognitive processes such as memory, language comprehension, problem- solving, and reasoning are merely variations on a central theme. They all reflect an underlying system of cognition. Integrative Models for Representing Declarative and Non-Declarative Knowledge ACT-R In ACT-R, networks include images of objects and corresponding spatial configurations and relationships. They also include temporal information, such as relationships involving the sequencing of actions, events, or even the order in which items appear. According to Anderson’s model (and various other network models), the nodes can be either inactive or active at a given time. An active node is one that is, in a sense, “turned on.” A node can be turned on—activated—directly by external stimuli, such as sensations, or it can be activated by internal stimuli, such as memories or thought processes. Integrative Models for Representing Declarative and Non-Declarative Knowledge Procedural Knowledge within ACT-R Proceduralizing is the overall process by which Three Stages of Acquisition of Procedural we transform slow, explicit information about Knowledge procedures (“knowing that”) into speedy, Cognitive Stage - We think about explicit implicit, implementations of procedures rules for implementing the procedure. (“knowing how). Associative Stage - We consciously practice using the explicit rules During this stage, we construct a single extensively, usually in a highly production rule that effectively embraces two consistent manner. or more production rules. Autonomous Stage - We use these rules Production tuning - It involves the two automatically and implicitly without complementary processes of thinking about them. We show a high generalization and discrimination. We learn degree of integration and coordination, to generalize existing rules to apply them as well as speed and accuracy. to new conditions Integrative Models for Representing Declarative and Non-Declarative Knowledge The Connectionist Model Computer-inspired information-processing theories assume that humans, like computers, process information serially. That is, information is processed one step after another. Some aspects of human cognition may indeed be explained in terms of serial processing, but psychobiological findings and other cognitive research seem to indicate other aspects of human cognition. These aspects involve parallel processing. The human brain seems to handle many operations and to process information from many sources simultaneously—in parallel. In fact, it seems necessary that we are able to process information in parallel. the distribution of parallel processes better explains the speed and accuracy of human information processing Integrative Models for Representing Declarative and Non-Declarative Knowledge Parallel Distributed Processing (PDP Model) This believes that we handle very large numbers of cognitive operations at once through a network distributed across incalculable numbers of locations in the brain. The PDP model demonstrates another way in which a brain-inspired model differs from a computer-inspired one. Inactive neurons are not stimulated beyond their threshold of excitation. They do not release any neurotransmitters into the synapse (the interneuronal gap). Excitatory neurons release neurotransmitters that stimulate receptive neurons at the synapse. Inhibitory neurons release neurotransmitters that inhibit receptive neurons. By using the PDP model, cognitive psychologists attempt to explain various general characteristics of human cognition. These characteristics include our ability to respond flexibly, dynamically, rapidly, and relatively accurately, even when we are given only partial or degraded information