Structural Knowledge

Techniques for Representing, Conveying, and Acquiring Structural Knowledge

David H. Jonassen, Michael Yacci, Katherine Beissner, Michael Yacci

• Publisher: Routledge
• Year: 2013
• ISBN:
  9781136474415
• Edition: 1
• Topic: Education
• Subtopic: Education General

This book introduces the concept of a hypothetical type of knowledge construction -- referred to as structural knowledge -- that goes beyond traditional forms of information recall to provide the bases for knowledge application. Assuming that the validity of the concept is accepted, the volume functions as a handbook for supporting the assessment and use of structural knowledge in learning and instructional settings. It's descriptions are direct and short, and its structure is consistent. Almost all of the chapters describe a technique for representing and assessing structural knowledge acquisition, conveying knowledge structures through direct instruction, or providing learners with strategies that they may use to acquire structural knowledge. These chapters include the following sections in the same sequence: * description of the technique and its theoretical or conceptual rationale * examples and applications * procedures for development and use * effectiveness -- learner interactions and differences, and advantages and disadvantages * references to the literature. The chapters are structured to facilitate access to information as well as to illuminate comparisons and contrasts among the techniques.

Part I

Introduction to Structural Knowledge

Chapter 1 Structural Knowledge: Description, Rationale, and Assumptions

1

Structural Knowledge: Description, Rationale, and Assumptions

DEFINITIONS OF STRUCTURAL KNOWLEDGE

Structural knowledge has several convergent definitions, all of which describe a form a knowledge representation.

Declarative, Structural, and Procedural Knowledge

Discussions of the psychology of knowing have often distinguished between declarative or procedural forms of knowledge. Declarative knowledge represents cognizance or awareness of some object, event, or idea. Ryle (1949) describes this type of knowledge as knowing that. When a person knows that, she or he is able to define or describe the objects of that knowing but are not necessarily able to use that knowledge, as declarative knowledge does not imply understanding. Declarative knowledge of ideas is often characterized as schemas (Rumelhart & Ortony, 1977). Schemas are ideational constructs that are defined by attributes that they inherit from other schemas. Declarative knowledge enables learners to come to know, or define, which forms the basis for thinking about and using those schemas.

Procedural knowledge, on the other hand, describes how learners use or apply their declarative knowledge. Ryle describes this type of knowledge as knowing how. Procedural knowledge entails the interrelating of schemas into patterns that represent mental performance which are in turn represented mentally as performance schemata. Solving problems, forming plans, and making arguments are examples of activities that entail procedural knowledge. In performing these activities, learners must access and interrelate relevant schemata and extract the relevant attributes to apply to the situation. Through practice, procedural knowledge schemata evolve where the mental activities are represented in more complex, performance-oriented schemata, otherwise known as scripts (Schank & Abelson, 1977). Declarative knowledge provides the conceptual basis for procedural knowledge. Most psychologists believe that without awareness of the objects of performance, performance would be impossible. Yet, certain performances or skills may be based on tacit knowledge (Polanyi, 1966), especially by experts, so articulating the declarative knowledge base would be difficult for the performer. Other performances may become so automatized that the performer is not declaratively aware of the skill.

In this volume, we propose an intermediate type of knowledge, structural knowledge, that mediates the translation of declarative into procedural knowledge and facilitates the application of procedural knowledge. Structural knowledge is the knowledge of how concepts within a domain are interrelated (Diekhoff, 1983). If schemas are defined by their interrelationships to other schemas, then explicit awareness of those interrelationships and the ability to explicate those relationships is essential for higher order, procedural knowledge. It is not enough to know that. In order to know how, you must know why. Structural knowledge provides the conceptual bases for why; it describes how the declarative knowledge is interconnected. Procedural knowledge is dependent on complex interconnections between ideas. For example, the dictum “warm air rises” entails connections between air and its modifier, warm as opposed to cold. That warm air rises is predicated on a causal relationship between warm and rising, the basis of the principle of convection. Structural knowledge, the understanding of these relationships, enables learners to form the connections that they need to use scripts or complex schemas.

Some researchers conceive of structural knowledge as a part of declarative knowledge, which has two dimensions — content and structure (Mitchell & Chi, 1984). Structure refers to how information within a knowledge domain is organized, which we have defined as structural knowledge. Whether structural knowledge exists as a separate type of knowledge or it is a part of declarative knowledge is a semantic distinction that does not affect it recognition as an entity or as a distinct type of knowledge.

Structural Knowledge as Cognitive Structure

Structural knowledge is also known as cognitive structure, the pattern of relationships among concepts in memory (Preece, 1976) or more specifically, “…a hypothetical construct referring to the organization of the relationships of concepts in long-term memory” (Shavelson, 1972, pp. 226-227). Structural knowledge is the awareness and understanding of one’s cognitive structure.

Cognitive structure, like most psychological constructs, has numerous interpretations (Nagy, 1984). As described shortly, cognitive structure evolves from memory theory, particularly semantic memory.

Some researchers conceive of cognitive structure as an integral component of an individual’s personality (Scott, Osgood, & Peterson, 1979). Individual differences in behavior are attributable in part to differences in an individual’s cognitive contents. Cognitive structure evolves individually from the ascription of attributes (any objective or subjective feature) to objects in the world, which enables the definition of structural relations among concepts. Attributes may be related to one another in at least two ways — relations of association (e.g., friendliness) or relations of implication in which information is used in forming judgments in different circumstances. This object-attribute model of cognitive structure is based on Kelly’s (1955) personal construct theory which focuses on the development of attribute-based personal constructs, which are used to interpret reality. Rather than being a reactive organism, Kelly believed that individuals take an active role in representing and organizing their environment, which drives their behavior rather than merely responding to environmental stimuli. Individuals revise or replace their constructs as is necessary in order to interpret their environment. The way that individuals organize and represent constructs, that is, their cognitive structure, determines how they interact with the environment.

Other Conceptualizations of Structural Knowledge

Structural knowledge has been also referred to as internal connectedness, integrative understanding, or as conceptual knowledge. Conceptual knowledge is the “integrated storage of meaningful dimensions ......... in a given domain of knowledge” (Tennyson & Cocchiarella, 1986). It is more than the storage of declarative knowledge; it is the “understanding of a concept’s operational structure within itself and between associated concepts.” Conceptual knowledge is used to develop procedural knowledge for solving domain problems. Structural (conceptual) knowledge involves the integration of declarative knowledge into useful knowledge structures. The underlying assumption of each of these conceptions is that meaning for any concept or construct is implicit in the pattern of relationships to other concept or constructs.

Structural knowledge may also refer to an individual’s knowledge structure. Knowledge structure is the information-processing term for organized networks of information stored in semantic or long-term memory (Champagne, Klopfer, Desena, & Squires, 1981, p. 97). It is a generic term, like structural knowledge, that refers to the integration and organization of constructs in an individual’s memory.

Structural knowledge, like cognitive structure or knowledge structure, is a hypothetical construct. Such constructs can be reified using techniques described throughout this volume. These techniques, because they represent such important constructs, have utility as instructional and learning tools. To reiterate, a fundamental hypothesis of this volume is that analysis of structural knowledge mediates the acquisition of procedural knowledge. Before considering research support for this hypothesis, we describe some of the theoretical foundations of structural knowledge.

THEORETICAL BASES FOR STRUCTURAL KNOWLEDGE

The following theories provide the conceptual foundation for the construct, structural knowledge.

Schema Theory

Schema theory (Rumelhart, 1980; Rumelhart & Ortony, 1977) contends that knowledge is stored in information packets, or schema, that comprise our mental constructs for ideas. A schema for an object, event, or idea is comprised of a set of attributes or slots that describe and therefore help us to recognize that object or event. These slots contain relationships to other schemas. It is the interrelationships between schemas that give them meaning. For instance, most of us have a well-developed schema for airplane that includes attributes or slots such as wings, fuselage, seats, jet engines, flight attendants, cardboard snacks, and so on. The schema for airplane is a member of larger classes of schemata, such as transportation, business travel, holidays, or recreation. Likewise, our airplane schema has specific slots that are filled with more specific airplanes, such as a Boeing 747 or the plane that I flew to London. Each individual possesses a unique schema for objects or events depending upon their experiences. Each schema that we construct represents a miniframework in which we interrelate elements or attributes of information about that topic or experience into a single conceptual unit (Norman, Gentner, & Stevens, 1976).

Individual schemas vary in complexity. They can resemble concrete or abstract concepts, such as airplane, ice cream cone, anger or trust, or they can be complex combinations of events or objects, such as dining in a restaurant or my trip to London. These more complex, event schemas involve episodic information as well as interrelated conceptual information encoded into the schema’s slots. For instance, a schema for “hitting a homerun” may contain specific home runs that you have hit as well as rules about the application of vector forces, trajectory, and a host of other physical factors or schemas. We must understand the conceptual relationships between placement of the bat on the ball within a limited location in order to hit a homerun (procedural knowledge). We may also encode specific, event-related information, such as the homerun in the Tiger’s game. The interrelationships between schemata and the formation of more complex schemas requires the construction of structural knowledge. We develop schemata for events or stories as well. A story schema is a mental structure that describes the way in which particular stories proceed, which is a reflection of the story grammar, the structures of the stories (Mandler, 1983; Mandler & Goodman, 1982). It is likely that most story schemas for primary children all begin, “Once upon a time....” Schemas are mental abstractions that we use to comprehend discourse, find our way, or solve problems. We must fill the schema’s slots with the correct information through schema selection or inheritance of attributes from other schemas in order to acquire structural and procedural knowledge. Structural knowledge is built with schemas and interrelated schemas (schemata).

How do we acquire or change our schemata, that is, how do we learn? We fill slots by encoding our experiences as attributes of schema (for example, my last trip to London) in a process known as accretion (Rumelhart, 1980). Accretion can also result in the addition of new schemas that use existing schemas as their model. Schemas are tuned or finely adjusted to meet specific task demands or adapted to particular knowledge domains or contexts. Tuning might entail the refining of a procedure, filling-in of inferences, or adapting the schemas to new situations. When new experiences occur that cannot be described by existing schemas, they are restructured. The learner begins to restructure his or her knowledge by adding schemas or developing new conceptualizations for existing ones. While restructuring of knowledge is the least common learning activity, it is the most important one.

Semantic Networks

A basic premise of schema theory is that human memory is organized semantically. Schemas are arranged in networks (schemata) of interrelated concepts. These networks are known as our semantic network. Perhaps the best known conceptualization of a semantic network is active structural networks (Quillian, 1968), structures that are composed of nodes (the equivalent of schemas) and ordered, typed (e.g. subordinate, disjunctive) relationships or links connecting them (Norman et al., 1976). The nodes are token instances of concepts or propositions and the links described the propositional relationship between them.

If memory is organized as a semantic network, then learning can be conceived as a reorganization of the networks in semantic memory. These networks describe what a learner knows, which provides the foundations for learning new ideas, that is, altering and expanding the learner’s semantic network through accretion, tuning and re...

Table of contents

• Cover Page
• Half Title page
• Title Page
• Copyright Page
• Contents
• Dedications
• Preface
• Part I Introduction to Structural Knowledge
• Part II Representing/Assessing Structural Knowledge
• Part III Conveying Structural Knowledge
• Part IV Structural Knowledge Learning Strategies:
• Author Index
• Subject Index