Cambridge Catalogue  
  • Help
Home > Catalogue > Schemas in Problem Solving
Schemas in Problem Solving


  • 43 b/w illus.
  • Page extent: 440 pages
  • Size: 228 x 152 mm
  • Weight: 0.61 kg


 (ISBN-13: 9780521043694)

Schemas in Problem Solving explores a theory of schema development and studies the applicability of the theory as a unified basis for understanding learning, instruction and assessment. The theory's prescriptions for teaching are direct, and its application to assessment suggests new directions for tests. After examining the roots of the theory in earlier work by philosophers and psychologists, Marshall illustrates the main features of her theory with experimental evidence from students who are learning to recognize and solve arithmetic story problems. She describes individual performance with traditional empirical studies as well as computer simulation. The computer simulation reflects an approach in modelling cognition. Marshall's model links neural networks with symbolic systems to form a hybrid model that uses pattern matching of sets of features as well as logical step-by-step rules.

• Introduces an alternative theory of memory structures, what they are, how they are acquired and how they may be evaluated • Takes the innovative approach of using a unified basis for understanding learning, instruction and assessment • Introduces a form of computer modelling which joins neural networks with production systems to form a hybrid model of cognition


Preface; Acknowledgements; Part I. Fundamentals: 1. Schema roots; 2. The nature of a schema; 3. The schemas of arithmetic story problems; Part II. Schemas and Instruction: 4. Theoretical issues for instruction; 5. The story problem solver and the problem solving environment: two examples of schema-based instruction; Part III. Learning from Instruction: 6. Learning and schema theory; 7. Learning from schema-based instruction; 8. The acquisition of planning knowledge; 9. The diagram: marker and template; Part IV. Schemas and Assessment: 10. Schema-based assessment; 11. Assessment in SPS and PSE; Part V. Schema Models: 12. Production systems, neural networks and hybrid models; 13. The performance model; 14. The learning model; 15. The full schema model; 16. Some concluding remarks on schema theory; Notes; References; Name index; Subject index.

printer iconPrinter friendly version AddThis