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In Order to LearnHow the sequence of topics influences learning$
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Frank E. Ritter, Josef Nerb, Erno Lehtinen, and Timothy O'Shea

Print publication date: 2007

Print ISBN-13: 9780195178845

Published to Oxford Scholarship Online: April 2010

DOI: 10.1093/acprof:oso/9780195178845.001.0001

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Getting Things in Order: Collecting and Analyzing Data on Learning

Getting Things in Order: Collecting and Analyzing Data on Learning

Chapter:
(p.81) Chapter 6 Getting Things in Order: Collecting and Analyzing Data on Learning
Source:
In Order to Learn
Author(s):

Frank E. Ritter

Josef Nerb

Erno Lehtinen

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780195178845.003.0006

This chapter provides a tutorial on the types of data that have been used to study sequence effects, some of the data collection methodologies that have been and will continue to be used because they are necessary to study order effects, and how to use model output as data. It starts by introducing the basic measurements typically used in experimental psychology, such as reaction times and errors. The chapter also examines the feasibility of using protocol data that, although used infrequently, offer a rich record to study order effects. It looks at how these data can be “cooked down” into theories, which can then be broken down into static and dynamic process models. Static descriptions, such as simple grammars and Markov models, depict the shape of the data. Process models perform the task that a person does in a manner that a person does and so provide a more dynamic description. Process models are inherently not only more powerful but also more difficult to use. The chapter concludes with a brief discussion on using model output as data.

Keywords:   sequence effects, data collection, process models

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