Example Data and Narrative
Last updated on 2025-10-14 | Edit this page
Estimated time: 35 minutes
Overview
Questions
- Why should a lesson tell a story?
- What considerations are there when choosing an example dataset for a lesson?
- Where can I find openly-licensed, published data to use in a lesson?
Objectives
After completing this episode, participants should be able to…
- Find candidate datasets to use in a lesson.
- Evaluate the suitability of a dataset to be used in a lesson.
- Choose examples that will prepare learners for formative assessments in the lesson.
- Develop a story for their lesson
With your high-level lesson objectives set, now is a good time to consider any additional resources you may need to effectively communicate your message to learners before you dive deeper into writing the lesson content.
Writing your lesson as a story helps learners stay motivated and engaged, which means they will learn faster1. The story you create can also help learners more easily connect how the skills they are learning now could be useful after the workshop. You can enable learners to make connections between what they learn in your lesson and their own work, by creating a narrative that resembles a situation the learners might encounter there.
For a lot of lessons developed in The Carpentries community, the narrative is closely tied to the example data used in the lesson. A good example dataset makes it easier to teach the relevant skills, helps learners manage their cognitive load by focusing on what is most important. Just like the narrative, finding the right dataset involves striking a balance between authenticity and clarity.
Exercise: Choosing a Dataset or Narrative (30 minutes)
Referring to [the advice you reviewed before this training][handbook-narrative-example-data], find an appropriate dataset or a narrative for your lesson. Identify one or more potential candidates and note down the advantages and disadvantages of each one.
As a summary, here are some aspects we suggest that you consider:
- For datasets:
- size
- complexity
- “messiness”/noise
- relevance to target audience
- availability
- license
- ethics
- For narratives:
- authenticity
- relevance to target audience
- complexity
- possibility to teach useful things first/early
Takes notes in your Lesson Design Notes document about your discussion and the decisions made. It may be particularly helpful to record:
- Which datasets and narratives did you consider?
- How and why did you choose between them?
- What implications do you think your choice of dataset and/or narrative will have for the design and further implementation of your lesson?
Summary
Remember, even if you do not need a dataset for your lesson, you should decide on a narrative. Building your lesson around a central example reduces the cognitive load of context switching throughout the lesson. Using an authentic, yet simple, dataset will also help reduce cognitive load and help learners to see how they might apply what they learned to their own projects. It is also important to consider licensing and ethical considerations when looking for a lesson dataset.
- Using a narrative throughout a lesson helps reduce learner cognitive load.
- Choosing a dataset includes considering data license and ethical considerations.
- Openly-licensed datasets can be found in subject area repositories or general data repositories.
The evidence for this is summarised well in chapter 3, What Factors Motivate Students to Learn?, of Ambrose et al. 2010. The Carpentries Instructor Training curriculum also includes a helpful summary of how lesson content can influence Learner motivation.↩︎