Schema Level Research Articles

Schema-based learning

Schema-based learning (SBL) builds on the schema theory of The Metaphorical Brain 2 (TMB2) in a number of ways. In SBL we incorporate not only schemas which provide units of interaction of the organism with its environment, but also predictive schemas reflecting expectations about those interactions. These internal models exist at all levels of granularity forming a hierarchical network of schemas. Schemas as generic specifications go beyond any specific implementation (neural networks in particular). Thus, the definition of schemas must be general enough so that it applies to a whole variety of possible implementations. There have been several attempts at formalizing schemas. Lyons and Arbib [7] formalized schemas as port automata and Corbacho and Arbib [4] extended this formalization by including activity variables for each port automaton along with the corresponding dynamics. Since schemas must be general by definition we claim the “power” comes from the operations at this schema level. For instance. SBL includes schema instantiation, schema assertion by distributed competitive and cooperative dynamics over the schemas activity variables, schema tuning and schema construction (where predictive schemas play a very important role in deciding when to construct a new schema). Arbib asserts that “schema theory attempts to bridge between structure and function at the highest level”. A schema may refer to either a set of regularities in observed behavior or the internal mechanisms which give rise to such regularities. In analyzing a living system we mostly refer to the first. In designing (synthesizing) a system we must provide the second, i.e., provide internal mechanisms. The ultimate challenge is to match both. Hanson argues that “one might posit different types of schemas, ones perhaps that vary in abstractness or perhaps have some domain or topic dependency . ..‘I. and indeed SBL introduces several types of schemas: perceptual, motor, sensorimotor, goal and predictive schemas. Current extensions on progress also include autonomous construction of incrementally abstract schemas grounded on more primitive sensorimotor schemas, much in the way Piaget [9] described the appearance of more abstract schemas along the

Specialization by restriction and schema derivations

Specialization and inheritance are well-known concepts in the area of object-oriented modelling and knowledge representation. However, certain aspects of these concepts lack formal foundations. In particular, when properties of different classes are semantically related, several different semantics are possible for the inherited properties, and a choice is necessary. Conventional systems impose an a priori solution that supports only one of the possible semantics of inheritance. In this paper, we present constructs that allow to differentiate between the possible semantics of inheritance, in a formal and sound way. Our approach is based on a structured view of the real world and a model for its representation. By necessity, the model only partly represents the real world. Thus, reasoning in the model is done with reference to the real world. We introduce restriction isa, a form of specialization that represents property restriction, and demonstrate that it can be a useful conceptual modelling mechanism. We employ restriction isa to formally define property inheritance. Reasoning in our model is done through a number of inference rules that reflect real world constraints. These rules allow for sound derivations both at the instance and schema levels. At the schema level, in particular, these rules allow us to relate inherited properties to other properties through restriction-isa and isa relations. Such relations not only give useful information about the inherited properties but also refine the values of these properties.

On the Semantics of a Semantic Network

We elaborate on the semantics of an enhanced object-oriented semantic network, where multiple instantiation, multiple specialization, and meta-classes are supported for both kinds of objects: entities and properties. By semantics of a semantic network, we mean the information (both explicit and derived) that the semantic network carries. Several data models use semantic networks to organize information. However, many of these models do not have a formalism defining what the semantics of the semantic network is. In our data model, in addition to the Isa relation, we consider a stronger form of specialization for properties, that we call restriction isa, or Risa for short. The Risa relation expresses property value refinement. A distinctive feature of our data model is that it supports the interaction between Isa and Risa relations. The combination of Isa and Risa provides a powerful conceptual modeling mechanism. The user declares objects and relations between objects through a program. Reasoning is done through a number of (built-in) inference rules that allow for derivations both at instance and schema level. Through the inference rules, new objects and new relations between objects are derived. In our data model, inherited properties are considered to be derived objects. In addition to the inference rules, a number of (built-in) system constraints exist for checking the validity of a program.

Refraining the Relationship Between Teacher Thinking and Teacher Behaviour: levels in learning about teaching

Abstract This article presents a new conceptualization of the relationship between teacher thinking and teacher behaviour. First, it is argued that much of a teacher's behaviour is determined by Gestalts within the teacher, i.e. dynamic unities of perception, internal processes and action, triggered by the contact between the teacher and the situation. Second, three levels of teacher knowledge are distinguished: the Gestalt level, the schema level and the theory level. The processes of Gestalt formation, schematization and theory‐building are analysed. The three levels are illustrated by means of excerpts from interviews with teachers and non‐teachers. Following a theoretical reflection on the proposed view of teacher knowledge, its implications for teacher education and research on teaching are discussed.

Entity identification in database integration

The objective of entity identification is to determine the correspondence between objective instances from more than one database. This paper examines the problem at the instance level assuming that schema level heterogeneity has been resolved a priori. Soundness and completeness are defined as the desired properties of any entity-identification technique. To achieve soundness, a set of identity and distinctness rules have to be established for the entities in the integrated world. We then propose the use of extended key, which is the union of keys (and possibly other attributes) from the relations to be matched, and its corresponding identity rule to determine the equivalence between tuples from relations that may not share any common key. Instance level functional dependencies (ILFD), a form of semantic constraint information about the real-world entities, are used to derive the missing extended key attribute values of a tuple. Formal properties of ILFDs are derived. Results from a Prolog-based prototype entity-identification system are presented.

Some Effects of Schematic Processing on Consumer Expectations and Disconfirmation Judgments

Recent research has shown that processing based on the product-category schemas of consumers can influence the manner in which consumers evaluate products. This article presents a series of studies that explore how processing based on such schemas interacts with consumer expectations prior to the trial of a new product and influences disconfirmation judgments and product evaluations following the trial. An initial study finds that, when attributes included in the description of a new product are very discrepant from a prior category schema, consumers may switch schemas in forming pretrial expectations. A second study finds that more negative product evaluations following the trial may result when consumers' experience with a product during the trial is very different from schema expectations, compared with the situation in which the product matches schema expectations. A third study demonstrates that disconfirmation judgments and posttrial evaluations may occur through processing at the product-category schema level, rather than through processing at the product attribute level.

The effects of relational and entity-relationship data models on query performance of end users

In database systems the end user interacts with the database at the external schema level. At this level the user sees only the logical structure of the database that is relevant to his/her work. Both the relational and the entity-relationship model have proponents arguing that one data model is superior to the other when used in the end user environment. However, a literature review indicated that these arguments have not been based on empirical results from a systematic inquiry. The study reported here examined this issue through a controlled experiment using query writing as the task. Our basic assumption was that if one data model was superior to the other, then the superiority of the model would be reflected in the user's query writing performance. In addition, this superiority would be demonstrated on both simple and complex tasks. Query writing performance was measured by three variables: number of syntax errors, number of semantic errors, and amount of time to complete queries. The results indicated that subjects using the relational model made fewer syntax errors, but required more time to complete a query. No significant differences in the number of semantic errors were found between the two data models. Based on these results, neither the relational nor the entity-relational data model was clearly superior when used as the interface between a database system and the end user. As expected, the more complex tasks caused more syntax and semantic errors, and required more time to complete.

Facilitating connectivity in composite information systems

Timely access to multiple disparate databases which were independently developed and administered to produce composite information has become increasingly critical for organizations to gain competitive advantage. However, many inter-database problems such as inconsistency, ambiguity, and contradiction remain unresolved. This paper presents an approach for resolving these problems. The techniques employed in this approach include schema integration, inter-database tables, attribute subsetting, object hierarchies, and heuristic rules. Schema integration techniques resolve the incompatibilities among the databases at the schema level. Inter-database tables resolve the semantic inconsistency and concept granularity at the instance value level. The inter-database instance identification table identifies an instance across databases. Object hierarchies represent schemata as well as instances. Finally, heuristic rules are used to facilitate the construction of the inter-database instance identification table and the production of composite information.

THE ROLE, STRUCTURE AND DESIGN OF A DATABASE FOR DISSEMINATION OF PROCESS DATA DURING PLANT DESIGN

Abstract The role of databases in process plant design is reviewed. Data usage and the prevention of concurrency conflicts justify a layering of the databases into a project-wide database for information dissemination and smaller work-spaces for storage of preliminary data. The dissemination of process data is selected as a representative problem space and the information carried in a database containing a process release is characterized. The logical database design is then described, a model for representation of information at the conceptual schema level is selected and a suggested formalism for description of evolutionary graphical documents is discussed. The compatibility between binary associations (the model for schema representation) and normalized R-graphs (the formalism for evolutionary drawings) is demonstrated, and it is shown how such a formalism can be incorporated into a methodology for engineering database design. The methodology proposed is described and illustrated with some data handled...

Computer aided design of database internal schema

A large number of complexly interrelated parameters are involved at the internal schema level design of database systems. Consequently, a single design model is seen to be infeasible. A package of three aids is proposed to assist a designer in step by step design of internal schema. The three aids pertain to splitting of a relation, merging of relations, and access strategy selection for a relation.

Mapping external views to a common data model

In the context of a multilevel database management system architecture, the problem arises of translating, or mapping, operations at the user's representation level (the External Schema) into operations at the system's common logical level (the Conceptual Schema). In order to support different structured user's data models, the need for an unstructured, view-independent and yet carefully defined data model at the Conceptual Schema level is recognized. In this paper a binary model for the Conceptual Schema is illustrated through the specification of a set of primitives, and the elements of a language for the definition of a binary Schema and of the corresponding operations are given. Procedures are then illustrated for translating external into conceptual operations through exploitation of the primitives of the binary model. Two types of mapping specifications are illustrated: the operational mapping, in which the translation is explicitly defined, and the structural mapping, in which only the structural correspondences between elements of the External and the Conceptual Schema are defined. The automatic mapping between n-ary relational views and the binary Conceptual Schema is finally discussed.