Schemas in Problem Solving

Schemas in Problem Solving

by Sandra P. Marshall
     
 

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ISBN-10: 0521043697

ISBN-13: 9780521043694

Pub. Date: 11/22/2007

Publisher: Cambridge University Press

Schemas in Problem Solving introduces a new approach to the study of learning, instruction, and assessment. Focusing on the area of arithmetic story problems, Marshall shows how instruction can lead to more meaningful learning by emphasizing the ways students acquire and store knowledge in memory. She identifies major knowledge structures called schemas, describes

Overview

Schemas in Problem Solving introduces a new approach to the study of learning, instruction, and assessment. Focusing on the area of arithmetic story problems, Marshall shows how instruction can lead to more meaningful learning by emphasizing the ways students acquire and store knowledge in memory. She identifies major knowledge structures called schemas, describes instruction designed around theses structures, and assesses the strengths and weaknesses in the knowledge that the students demonstrate following instruction. To evaluate the success of her approach, Marshall describes traditional experiments and computer simulations of student performance.

Product Details

ISBN-13:
9780521043694
Publisher:
Cambridge University Press
Publication date:
11/22/2007
Pages:
440
Product dimensions:
5.98(w) x 8.98(h) x 0.91(d)

Table of Contents

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.

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