Complex datasets must be communicated clearly, and data visualization helps achieve this. Bar charts and line graphs are effective but often fail to illustrate deeper relationships, such as the “why” and “how.” This paper explores the use of LEGO bricks to enhance students data visualization skills. By constructing three-dimensional models, students develop a deeper understanding of complex structures and relationships in data while applying creativity. LEGO’s modularity enables students to build, modify, and explore patterns dynamically, fostering a hands-on learning experience.

Each LEGO brick can represent different data points, categories, or variables, with colors, sizes, and arrangements conveying specific metrics. This approach helps students grasp how data interrelates and how visualizations represent complex patterns. Traditional visualizations often oversimplify relationships, whereas LEGO-based models allow for interactive exploration.

For example, consider a dataset displaying monthly sales performance across regions. Typically, students would create bar charts or line graphs, which condense data effectively but fail to reveal underlying connections. Instead, using LEGO bricks, students assign colors to regions and stack bricks to indicate sales volume per month. Tall red bricks could signify high sales, while shorter green bricks represent lower sales. As they adjust the model, students observe how sales evolve over time and across regions, making the data more tangible and engaging than static charts.

LEGO-based visualizations provide a dynamic method for modeling data. Students can add or remove bricks to reflect changes in sales, testing different scenarios. This interactivity helps learners explore how datasets shift and how different factors influence outcomes. Unlike static charts, which can be abstract, LEGO models enable students to physically manipulate data, reinforcing comprehension.

Additionally, LEGO's three-dimensional nature enhances students’ understanding of relationships within datasets. By arranging bricks spatially, they can highlight trends, value comparisons, and anomalies that might be harder to identify in two-dimensional graphs. Stacking bricks over time reveals trends, while spatial positioning shows regional correlations. This encourages deeper analytical thinking and effective communication of complex ideas.

Indeed, because LEGOs are accessible, students from different contexts are able to collaborate and participate in discussions. Collaboration among students assists them in improving their visualizations and analyzing the data from different angles.

Furthermore, LEGO-based exercises allow students to simulate different scenarios. For instance, to analyze the impact of a marketing campaign, students can modify the LEGO model to reflect sales growth, visually testing hypotheses in real-time. This hands-on experimentation reinforces understanding of data dynamics and relationships.

Thus, with the use of LEGO bricks in teaching data visualization, learners participate in the improvement of the interpretation of data sets. Building and changing LEGO models strengthens the learners’ visualization skills and fosters creativity, collaboration, and critical thinking. Students are prepared to deal with real-life data analysis challenges. It makes the learning process in the classroom more engaging and purposeful in terms of students learning about data visualization.

Keywords: LEGO, data, data storytelling, data visualisation.