Mastery Learning Improves Performance on Complex Tasks on PCP Literacy Test

2025-06-11

AI Summary

Students exhibit weak higher-order literacy skills—specifically analysis and evaluation—in interpreting complex visualizations such as Parallel Coordinate Plots (PCPs). Method: Grounded in the Revised Bloom’s Taxonomy, this study designs a six-module instructional framework and pioneers its integration with Mastery Learning for classroom intervention. It further introduces the Bloom’s-Taxonomy–guided PCP Literacy Assessment (BTPL), a standardized, multi-level cognitive assessment tool targeting analytical and evaluative competencies. Results: A controlled educational experiment demonstrates that the Mastery Learning group significantly outperforms the control group on Analyze and Evaluate tasks (p < 0.01), with substantial gains in deep PCP comprehension. All instructional materials and the BTPL assessment toolkit are openly released, offering a reproducible, scalable theoretical framework and pedagogical paradigm for cultivating advanced data visualization literacy.

Technology Category

• Data Mining & Knowledge Management: Data Visualization & Summarization
• Machine Learning: Evaluation and Analysis
• Cognitive Modeling & Cognitive Systems: Analogy

Application Category

• Web Mining and Content Analysis: Web data visualization
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets
• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success

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/.

Problem

• Enhancing literacy in Parallel Coordinate Plots (PCPs) for students
• Evaluating Mastery Learning's impact on advanced data visualization skills
• Comparing Revised Bloom's taxonomy with and without Mastery Learning

Innovation

• Used Mastery Learning for PCP literacy
• Applied Revised Bloom's taxonomy framework
• Developed six-module BTPL test