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Making Design of Experiments (DOE) accessible for everyone: Prototype design and evaluation

Published:18 October 2021Publication History

ABSTRACT

The increasing use of artificial intelligence technologies in several areas of knowledge highlights the need to design solutions for people with different backgrounds and skills. Since data collection to use such technologies and obtain reliable results is still a challenge, the statistical technique of Design of Experiments (DOE) can be applied to address this issue gathering less biased and more balanced data. However, to apply DOE effectively is required a high level of specific statistical knowledge, making difficult for most people to use the technique. In this paper we discuss the design and evaluation of a software prototype for people to apply DOE without statistical knowledge. The results of prototype tests reveal that some technical terms are difficult to understand, even when explained. Despite this, results also show that real-life examples were helpful for participants understand concepts related to DOE. We hope our results can inspire Human-Computer Interaction community to design solutions for artificial intelligence technologies, making it more accessible for people from different fields. We believe this multidisciplinary approach contributes to solve real people's needs.

References

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    • Published in

      cover image ACM Other conferences
      IHC '21: Proceedings of the XX Brazilian Symposium on Human Factors in Computing Systems
      October 2021
      523 pages
      ISBN:9781450386173
      DOI:10.1145/3472301

      Copyright © 2021 ACM

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      Publication History

      • Published: 18 October 2021

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      IHC '21 Paper Acceptance Rate29of77submissions,38%Overall Acceptance Rate331of973submissions,34%

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