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Data on multi-actor parameter design tasks by engineering students with variable problem size, coupling, and team size.

ABSTRACT: The experiment studies the effect of technical and social sources of complexity on effort required to complete abstracted design tasks. Parameter design tasks define a set of input design parameters and functional requirements modeled with a linear coupling matrix. Selecting design variables to meet all functional requirements within error limits completes a task. Technical complexity arises from the number and degree of coupling between design parameters. Social complexity arises from the number of designers involved in a task. The experiment includes 10 sessions with between 19 and 24 rounds of randomly generated parameter design tasks each having between two and six design variables and one, two, or three designers. Designers completed individual tasks in parallel during rounds. This article contains raw and post-processed data from 374 completed tasks ranging in effort from a few seconds for simple tasks to more than 15?min for complex ones.

SUBMITTER: Grogan PT

PROVIDER: S-EPMC6140357 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Data on multi-actor parameter design tasks by engineering students with variable problem size, coupling, and team size.

Grogan Paul T PT

Data in brief 20180831

The experiment studies the effect of technical and social sources of complexity on effort required to complete abstracted design tasks. Parameter design tasks define a set of input design parameters and functional requirements modeled with a linear coupling matrix. Selecting design variables to meet all functional requirements within error limits completes a task. Technical complexity arises from the number and degree of coupling between design parameters. Social complexity arises from the numbe ...[more]

PMID: 30229123

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Dataset Information

Data on multi-actor parameter design tasks by engineering students with variable problem size, coupling, and team size.

Publications

Data on multi-actor parameter design tasks by engineering students with variable problem size, coupling, and team size.

Similar Datasets

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