Increasingly, AI literacy is being recognized as a set of critical competences that can – and should – be embedded across a broad range of subject areas and educational contexts. Students and educators alike will require skills to recognize, understand, and respond to AI’s potential impacts within their learning environments, as well as in the world outside the classroom.
The AI Literacy (AILit) Framework aims to not only equip young people and teachers with an understanding of how these technologies work, but to ensure they consider and critically evaluate the social and ethical implications when choosing whether or not to employ AI systems. Alongside the final version of the framework, to be published in the coming weeks, teachers will have access to two ready-to-use, multilingual exemplar activities. The goal of the AILit Framework and these exemplars is to illustrate for educators how and where AI literacy can fit into their teaching through approachable scenarios and guidance.
AILit in the Classroom
The AILit exemplars are learning activities designed for practical classroom use and mapped to the framework’s competences. With the exemplars as a teaching resource, the foundational competences are made tangible, putting the framework into practice and serving as a roadmap that demonstrates how AI literacy can be meaningfully integrated across learning contexts and subject areas. At its core, the AILit Framework is a way to help teachers identify and prioritize AI literacy outcomes, with these two exemplars guiding initial implementation.
The first exemplar is geared towards primary school teachers. In this activity, students help a bot differentiate between and categorize a variety of images. Teachers use the activity to demonstrate how AI systems are trained, reinforcing the importance of understanding that AI does not “know” everything but instead follows logical, technical processes based on probabilities and data. Teachers could integrate this first exemplar within an existing lesson or use it to expand upon the learning scenarios shared throughout the framework.
The second exemplar, aimed at secondary school teachers, focuses on verifying information. Students discuss and check the outputs coming from large language models (LLMs) and are then asked to corroborate certain information. This exemplar is grounded in the framework’s emphasis on the human skills that are essential when interacting with AI, such as critical thinking. As with the first, teachers could use this exemplar as a starting point to adapt and plan more detailed lessons connecting AI literacy to their academic curriculum.
Each competence in the current draft of the AILit Framework also presents sample AI literacy learning scenarios, highlighting further opportunities for classroom implementation. Teachers could envision integrating these scenarios as mini-lessons before or after a more detailed exemplar activity. Alternatively, they could use the structured guidance of an exemplar to further develop a scenario under a particular competence. For example, the current draft of the AILit Framework describes a primary education scenario in which students label and sort blocks by their features before creating a decision tree to categorize new blocks. Paired with the primary school exemplar, which also centers on categorization, teachers could introduce an offline labeling exercise inspired by the learning scenario to emphasize what students worked through in the online exemplar activity.
Opportunities for Meaningful Interdisciplinary Learning
In addition to teaching their standard curriculum, educators have a unique and critical role in shaping how students come to grasp AI literacy. As students experiment and explore with AI – both inside and outside the classroom – teachers can design meaningful learning experiences for students to understand the principles underlying these technologies they have already begun to use. The AILit Framework’s exemplars will offer guidance for crafting such opportunities. Equipped with the right resources, teachers can find synergies for aligning AI literacy competences with their academic curriculum, preparing future generations to understand our rapidly transforming world.
