Mastery Learning Improves Performance on Complex Tasks on PCP Literacy Test

TL;DR

This study demonstrates that applying Mastery Learning to teaching Parallel Coordinate Plots enhances students' understanding of complex visualization tasks, especially in higher-order thinking modules, compared to traditional methods.

Contribution

It introduces a Mastery Learning approach combined with Bloom's taxonomy for teaching PCPs and provides a reproducible test suite for assessing literacy in data visualization.

Findings

Mastery Learning improves performance on advanced modules

Students in the Mastery group show better comprehension of PCPs

Both groups perform similarly on basic modules

Abstract

Developing literacy with unfamiliar data visualization techniques such as Parallel Coordinate Plots (PCPs) can be a significant challenge for students. We adopted the Revised Bloom's taxonomy to instruct students on Parallel Coordinate Plots (PCPs) using Mastery Learning in the classroom. To evaluate Mastery Learning's impact, we conducted an intervention in a Data Visualization course to teach students about PCPs using the Revised Bloom's taxonomy with and without Mastery Learning. Based on our intervention, we found that while students in both groups performed similarly on the first two (Remember, Understand) modules, the students in the Mastery Learning group performed better on modules that required more advanced thinking (Analyze, Evaluate) and demonstrated a better comprehension of PCPs. We provide all the materials developed including the six-module Bloom's Taxonomy PCP literacy (BTPL) test for full reproducibility on our website at https://vis-graphics.github.io/PCP-Literacy-Test/.