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Learning to spell: variability, choice, and change in children's strategy use
B Rittle-Johnson1, R S Siegler
1Department of Psychology, Carnegie Mellon University, Pittsburgh, PA 15213, USA. br2e@andrew.cmu.edu
Child Development
|April 28, 1999
Summary
The overlapping waves model effectively explains strategy development in spelling, even though backup strategies had little impact on accuracy. This research extends the model
Area of Science:
- Cognitive Psychology
- Educational Psychology
- Developmental Psychology
Background:
- The overlapping waves model, initially developed for arithmetic strategy choices, offers a framework for understanding cognitive development.
- Arithmetic is an algorithmic domain, while spelling is non-algorithmic, presenting a unique contrast for model application.
- Understanding strategy development is crucial for educational interventions.
Purpose of the Study:
- To investigate the applicability of the overlapping waves model to spelling strategy development.
- To compare strategy choices and effectiveness in algorithmic (arithmetic) versus non-algorithmic (spelling) domains.
- To analyze developmental changes in spelling strategy use from first to second grade.
Main Methods:
- A longitudinal study involving 30 first-grade students, with 23 retested in second grade.
- Trial-by-trial analysis of spelling strategy use across different conditions.
- Assessment of strategy adaptiveness, effectiveness, and developmental changes.
Main Results:
- The overlapping waves model successfully accounted for strategy choices in spelling.
- While students used various strategies, explicit use of backup strategies minimally impacted spelling accuracy.
- Developmental shifts in strategy selection and adaptiveness were observed between first and second grade.
Conclusions:
- The overlapping waves model is a valuable tool for understanding the development of strategy use in non-algorithmic domains like spelling.
- Adaptive strategy choice in spelling develops over time, irrespective of the direct impact on accuracy.
- Findings have implications for differentiating strategy development in algorithmic and non-algorithmic learning contexts.
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