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An approach for enhancing and measuring information comprehensibility for engineering designers: applied to patent documents

Published online by Cambridge University Press:  20 September 2024

Chris McTeague*
Affiliation:
The University of the West of England, Bristol, United Kingdom
Anna Chatzimichali
Affiliation:
The University of the West of England, Bristol, United Kingdom University of Bath, Bath, United Kingdom
*
Corresponding author: Chris McTeague; Email: chris.mcteague@googlemail.com
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Abstract

Computational simplification tools can make complex information sources easier to read for engineering designers. To guide and evaluate such approaches, it is necessary to understand how designers process information and how that information can be enhanced and measured. Here, we establish an approach for enhancing and measuring the comprehensibility of technical information for engineering designers. It is grounded in theories of document search and comprehension and provides theoretically supported principles for enhancing information and methods for measuring comprehension experimentally. It is tailored for engineering design in that it (i) does not summarize or remove potentially important information, (ii) is suitable for long, complex sources of information, (iii) can be applied in experiments that simulate real-life information sharing scenarios, and (iv) enables the measurement of domain-specific comprehension. The feasibility of the approach was tested by using patent documents as a test case since they represent a valuable but underutilized source of technical information. A 2 (patent documents) × 2 (conditions: control vs. modified) experiment was conducted with 28 professional engineering designers. Two patent documents were modified with six information design principles. Comprehension scores were higher for the modified patent than for the control, but the change was not statistically significant (p = 0.073). We attribute this either to redundancy effects causing a smaller than expected overall improvement in performance, or differences in prior knowledge for each patent. Overall, this approach offers a novel method for investigating and measuring information comprehensibility in engineering design; however, its effectiveness in enhancing information comprehensibility remains unvalidated.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2024. Published by Cambridge University Press
Figure 0

Figure 1. The cognitive approach used to remodel patent documents.

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Table 1. Three demands on cognitive capacity during multimedia comprehension – adapted from Mayer (2014b), table 3.6

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Table 2. Information design principles for improving comprehension

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Table 3. A classification of question types for eliciting search and comprehension processing

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Figure 2. The key conceptual elements of the experiment.

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Table 4. Experiment factors

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Figure 3. Images from the patent documents.

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Table 5. Summary of the four stimuli and how they were created

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Table 6. The information design principles applied to create the modified patent documents

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Figure 4. An example of a page of the preferred embodiment in the modified version of patent GB24.

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Table 7. A list of the questions that were given to the participants

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Table 8. Code definitions

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Table 9. Scoring examples for the failure modes transfer questions

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Table 10. Scoring examples for the redesign transfer questions

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Figure 5. The study procedure as it was shown to the participants.

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Figure 6. Data from the patent experiment, showing the data grouped by patent and condition (A), summary data and 95% CIs highlighting the participant groups (B) and the two patent documents (C), and truncated violin plots for the main effects of condition (D), groups (E), and patent (F). Mean values are shown by a cross (+) on the boxplots.

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Table 11. Summary data showing mean comprehension scores

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Table 12. Results from the two-way mixed ANOVA

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Figure A1. Patent GB24 in its original form.

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Figure A2. Patent GB24 after modifications.

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Table A1. Scoring criteria for patent GB24

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Table A2. Scoring criteria for patent GB25

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Figure A3. Differences between the stimuli configuration groups for frequency of patent use (A), familiarity of patent use (B) and years of industry experience (C).

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Table A3. Demographic analyses

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Figure A4. Demographic data and comprehension scores.

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Table A4. Results from Shapiro–Wilk’s test of normality