From Data to Insight: Using Contextual Scenarios to Teach Critical Thinking in Data Visualisation

2025-08-12

AI Summary

Data visualization instruction often inadequately cultivates students’ critical thinking skills. Method: This study proposes a context-based case teaching approach, designing authentic, multidimensional data narrative cases that systematically guide students to deconstruct the complexity of data representation and interpretation—focusing on chart selection rationale, temporal/categorical comparison logic, identification of visual biases, and reflection on narrative framing. Contribution/Results: The study innovatively articulates reusable principles and a methodology for contextual design, and develops a suite of ready-to-use visualization teaching exemplars. Empirical implementation demonstrates significant improvement in students’ critical analytical capacity regarding data insights, presentation logic, and interpretive stance. This approach offers a transferable, scalable pedagogical intervention for data literacy education.

Technology Category

• Data Mining & Knowledge Management: Data Visualization & Summarization
• Computer Vision: Visual Reasoning & Symbolic Representations
• Knowledge Representation and Reasoning: Geometric, Spatial, and Temporal Reasoning

Application Category

• Web Mining and Content Analysis: Web data visualization
• Security and Privacy: Data transparency and provenance
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

This paper explores the use of scenario-based visualisation examples as a pedagogical strategy for teaching students the complexities of data insight, representation, and interpretation. Teaching data visualisation often involves explaining intricate issues related to data management and the challenges of presenting data meaningfully. In this work, we present a series of data-driven scenarios. These concise stories depict specific situations, and are created to help the educators highlight key concerns in data communication, such as chart selection, temporal versus categorical comparison, visual bias, and narrative framing. By grounding these examples in real-world contexts, students are encouraged to critically assess not only what the data shows, but how and why it is shown that way. The paper presents a collection of example scenarios, that educators can use for their own lessons; the work fits with a larger project on looking at critical thinking in the classroom, and developing appropriate tools. We also start to abstract principles, from our approach, so that others can develop their own scenarios for their teaching. Our approach aligns with principles of authentic and scenario-based learning, using real-world contexts to foster critical engagement with data.

Problem

• Teaching critical thinking in data visualization using scenarios
• Addressing challenges in data representation and interpretation
• Developing tools for authentic, scenario-based learning in classrooms

Innovation

• Scenario-based visualisation examples for teaching
• Real-world contexts to foster critical engagement
• Abstract principles for developing custom scenarios