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Teaching variability engineering to cognitive psychologists

Published: 15 September 2014 Publication History

Abstract

In research of cognitive psychology, experiments to measure cognitive processes may be run in many similar yet slightly different configurations. Variability engineering offers techniques to handle variable configurations both conceptually and technically. However, these techniques are largely unknown to cognitive psychologists so that experiment configurations are specified informally or too coarse grain. This is problematic, because it becomes difficult to get an overview of paradigm configurations used in the so far conducted experiments. Variability engineering techniques provide, i.a., concise notations for capturing variability in software and can also be used to express the configurable nature of a wide range of experiments in cognitive psychology. Furthermore, it enables cognitive psychologists to structure configuration knowledge, to identify suitably similar experiment setups and to more efficiently identify individual configuration options as relevant reasons for a particular effect in the outcome of an experiment. In this paper, we present experiences with teaching variability engineering to cognitive psychologists along with a suitable curriculum.

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cover image ACM Other conferences
SPLC '14: Proceedings of the 18th International Software Product Line Conference: Companion Volume for Workshops, Demonstrations and Tools - Volume 2
September 2014
151 pages
ISBN:9781450327398
DOI:10.1145/2647908
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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  • University of Florence: University of Florence
  • CNR: Istituto di Scienza e Tecnologie dell Informazione

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 September 2014

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Author Tags

  1. cognitive psychology
  2. feature model
  3. teaching
  4. variability engineering

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SPLC '14
Sponsor:
  • University of Florence
  • CNR

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Overall Acceptance Rate 167 of 463 submissions, 36%

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  • (2016)Colocation as a Hybrid ICT Sourcing Strategy to Improve Operational AgilityACM SIGMIS Database: the DATABASE for Advances in Information Systems10.1145/2963175.296317747:2(9-35)Online publication date: 24-Jun-2016
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