Overview:  Whether you are a researcher or a teacher, it can be helpful to know what knowledge and perspectives the youth have coming in (e.g., to measure learning gains after an activity for research, or so that you can tailor your curriculum to fit the specific learners' needs at hand for teaching). But a lot of these types of 'pre-tests' (to gauge prior knowledge) are intimidating, as youth are asked to answer confusing questions about AI before they have even learned about it. Discouraging learners before they've even started is especially problematic for those from marginalized backgrounds, who may already not be sure that they belong in a computing education environment. Developed with scientifically validated ways of engaging youth, below there three example activities to gauge knowledge in more culturally responsive, asset-based ways (i.e., ways that build on their own life experiences), which do not feel like an intimidating quiz or exam.

Audience: Middle school-aged youth, upper elementary

Notes:

• These are examples of materials, which can be used for inspiration or adapted to fit your curriculum or research context.

• You may want to understand what students learned after your AI literacy activities. A few ideas for how this can be done depending on your context could be (1) having them add their new understandings onto the pre-test activities or (2) going through the same pre-test activity from scratch, so that you can compare the before and after.

• Some crafting activities may require a thematic analysis approach to rigorously interpret content.