What are the most common challenges in using data visualization for technical training?

1 Choosing the right type

One of the first challenges in using data visualization for technical training is choosing the right type of chart, graph, or diagram for your data and your learning objectives. Different types of data visualizations have different strengths and weaknesses, and can convey different messages and emotions. For example, a pie chart can show proportions, but it can also create visual clutter and confusion if there are too many slices or categories. A line chart can show trends, but it can also imply continuity and causality where there is none. A map can show spatial relationships, but it can also introduce distortions and biases depending on the projection and scale. Therefore, you need to consider what type of data you have, what you want to highlight or compare, and what you want your learners to take away from your visualization.

2 Designing for clarity

Another challenge in using data visualization for technical training is designing your visualization for clarity and simplicity. You want your visualization to be attractive and engaging, but not at the expense of accuracy and readability. You need to avoid common design mistakes, such as using too many colors, fonts, or effects, using inappropriate scales or axes, or adding unnecessary elements or decorations. You also need to follow the principles of visual hierarchy, contrast, and alignment, to make your visualization easy to scan and understand. Moreover, you need to provide clear labels, titles, legends, and annotations, to explain what your visualization shows and why it matters.

3 Adapting to the audience

A third challenge in using data visualization for technical training is adapting your visualization to the needs and preferences of your audience. You need to consider who your learners are, what they already know, what they want to learn, and how they prefer to learn. You need to tailor your visualization to their level of expertise, interest, and motivation, as well as their cultural and linguistic background. You need to use appropriate terminology, symbols, and formats, to avoid confusion and misunderstanding. You also need to provide options for interactivity, feedback, and customization, to allow your learners to explore your data and discover their own insights.

4 Evaluating the impact

A final challenge in using data visualization for technical training is evaluating the impact of your visualization on your learners' learning outcomes and satisfaction. You need to measure how well your visualization helps your learners achieve your learning objectives, such as acquiring new knowledge, skills, or attitudes, or applying them to real-world scenarios. You need to use valid and reliable assessment methods, such as quizzes, tests, surveys, or observations, to collect and analyze data on your learners' performance and perception. You also need to use the results of your evaluation to improve your visualization and your training program, by identifying strengths and weaknesses, and making adjustments accordingly.

5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?