Getting Things in Order: Collecting and Analyzing Data on Learning

Frank E. Ritter, Josef Nerb and Erno Lehtinen

in In Order to Learn

Published in print August 2007 | ISBN: 9780195178845
Published online April 2010 | e-ISBN: 9780199893751 | DOI:

Series: Advances in Cognitive Models and Architecture

Getting Things in Order: Collecting and Analyzing Data on Learning

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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

Chapter.  8124 words.  Illustrated.

Subjects: Cognitive Psychology

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