Evaluating Differences in Insights from Interactive Dimensionality Reduction Visualizations Through Complexity and Vocabulary

Chris North, Leanna L. House

Abstract

The software, Andromeda, enables users to explore high-dimensional data using the dimensionality reduction algorithm Weighted Multidimensional Scaling (WMDS). How data are projected in WMDS is determined by weights assigned to variables, and with Andromeda, the weights are set in response to user interactions. This work evaluates the impact of such interactions on student insight generation via a large-scale study implemented in a university introductory statistics course. Insights are analyzed using complexity metrics. This analysis is extended to compare insight vocabulary to gain an understanding of differences in terminology. Both analyses are conducted using the same semi-automated method that applies basic natural language processing techniques and logistic regression modeling. Results show that specific user interactions correlate to differences in the dimensionality and cardinality of insights. Overall, these results suggest that the interactions available to users impact the ir insight generation and therefore impact their learning and analysis process.

Mia Taylor, Lata Kodali, Leanna House, Chris North: Evaluating Differences in Insights from Interactive Dimensionality Reduction Visualizations Through Complexity and Vocabulary. VISIGRAPP (3: IVAPP) 2023: 158-165