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Learning with Artifacts; Declarative Knowledge Cheat Sheet by

learning     knowledge     artifacts     creation     declarative

Introd­uction

Knowledge often comes to us via transc­ribed content or artifacts, which is derived from other's knowledge. These are facts, concepts, processes, proced­ures, and princi­ples (Clark & Chopeta, 2004). Thus, artifacts are used in the learning process for creating knowledge, while in turn, knowledge creates new artifacts.

Theses artifacts (content) are in turn, used in the knowledge creation process to create two types of knowledge: declar­ative and proced­ural.

Declar­ative models refers to repres­ent­ations of objects and events and how these knowledge and events are related to other objects and events. They focus on the why rather than the how. It allows us to think and talk about the world. Declar­ative models include propos­itions and schemata.

Cognitive Schemata

Schemata are higher­-level cognitive units that use propos­itional networks as their building blocks. These are often abstract or general nature that allow us to classify objects or events as belonging to a particular class and to reason about them.

Schemata are composed of conc­ept­ional knowledge, plan-like knowledge, and causal knowle­dge.

Concep­tional Knowledge

Concepts are simple schemata that represent a class of objects, events, or other entities by their charac­ter­istic features. Concepts enable a person to identify or classify particular instances (concrete object or event) as belonging to a particular class. In a language, most words identify concepts and at least to a certain degree, they are arbitrary in that they can be catego­rized in many altern­ative ways.

For example, the concept "­car­" can be linked to "­tir­es" and "­eng­ine­s." Thus, a instance can be classified as a car or not a car.

Experts possess more powerful concepts in their domain than novices that help them to solve problems. These concepts give them patterns for labeling various memory states, which allow them to classify problems according to their solution mode or deep structure. Where as novices typically classify problems according to their surface structure or superf­icial feature
 

Propos­itions and Propos­itional networks

Plan-Like Knowledge (Scripts)

These are simple schemata that describe how goals are related in time or space. They allow us to understand events and organize functions and actions. Plans are often referred to as scripts (or simple proced­ures) because they represent routine sequences of events.

Causal Knowledge

Causal knowledge are complex schemata that link principles and concepts with each other to form cause-­effect relati­ons­hips. They allow us to interpret events, give explan­ations, and make predic­tions.

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