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People often rank and order data items as a vital part of making decisions. Multi-attribute ranking systems are a common tool used to make such data-driven decisions. These systems are often table-based tools that can produce rankings based on numerical weights that a user assigns to each attribute, where the weight represents how important the user believes an attribute is to their decision. These systems assume that users are able to quantify their conceptual understanding of how important particular attributes are; however, this is not always the case.
Data analysis novices often encounter barriers in executing low-level operations for pairwise comparisons. They may also run into barriers in interpreting the artefacts (e.g., visualizations) created as a result of the operations. We developed Duet, a visual analysis system designed to help data analysis novices conduct pairwise comparisons by addressing execution and interpretation barriers. To reduce the barriers in executing low-level operations during pairwise comparison, Duet employs minimal specification: when one object group (i.e.
This research explored the effect of intuitive versus rational thinking on creativity. Our objective was to investigate this relationship through design tasks with undergraduate industrial design students. Students performed nine separate design tasks across three conditions. Their work was scored for novelty and feasibility, and we analyzed this performance data in conjunction with self-reported mood and information processing assessments. Our results show numerous statistically significant differences.

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