IEEE VIS 2024 Content: An Inductive Approach for Identification of Barriers to PCP Literacy

An Inductive Approach for Identification of Barriers to PCP Literacy

Chandana Srinivas - University of San Francisco, San Francisco, United States

Elif E. Firat - Cukurova University, Adana, Turkey

Robert S. Laramee - University of Nottingham, Nottingham, United Kingdom

Alark Joshi - University of San Francisco, San Francisco, United States

Room: Esplanade Suites I + II + III

2024-10-13T16:00:00ZGMT-0600Change your timezone on the schedule page
2024-10-13T16:00:00Z
Exemplar figure, described by caption below
This figure shows the methodology used to inductively identify an enhanced list of PCP literacy barriers.
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Abstract

Parallel coordinate plots (PCPs) are gaining popularity in data exploration, statistical analysis, predictive analysis along with for data-driven storytelling. In this paper, we present the results of a post-hoc analysis of a dataset from a PCP literacy intervention to identify barriers to PCP literacy. We analyzed question responses and inductively identified barriers to PCP literacy. We performed group coding on each individual response and identified new barriers to PCP literacy. Based on our analysis, we present a extended and enhanced list of barriers to PCP literacy. Our findings have implications towards educational interventions targeting PCP literacy and can provide an approach for students to learn about PCPs through active learning.