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

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.