Compare levels
How each competence changes as the level rises.
| Competence | basicBasic | intermediateIntermediate | advancedAdvanced |
|---|---|---|---|
| C1Use AI systems to explore new perspectives and approaches that build upon original ideas. | Learners explore how different AI tools can expand their thinking or spark new ideas. | Learners compare AI-generated suggestions to their own ideas during a brainstorming process. | Learners purposefully integrate AI-generated outputs with their own ideas to develop comprehensive solutions and creative approaches. |
| C2Visualise, prototype and combine ideas using different types of AI systems. | Learners use AI to generate an image, story or model to represent an idea. | Learners experiment with AI tools (e.g., text, image or music generators) to develop diverse ideas and produce varied outputs. | Learners select and integrate outputs from multiple AI systems to develop, refine or present a final product. |
| C3Direct generative AI systems to elicit feedback, refine results and support reflection. | Learners know how to prompt AI systems to generate accurate feedback and helpful responses to an idea. | Learners refine their work through iterative exchanges with AI, comparing those outputs to their own ideas to determine what serves their goals. | Learners critically evaluate how AI-generated feedback shapes their own ideas, then reflect on how they would like to use AI in their creative process. |
| C4Analyse how AI can safeguard or violate content authenticity and intellectual property. | Learners know that AI-generated content may reuse or copy work protected by intellectual property or copyright laws and recognise implications for the humans who created the original work. | Learners consider when attribution, permission or avoidance of AI is appropriate for a creative task and apply these choices in their own work. | Learners assess the ethical implications of AI-generated outputs for creative work, distinguish inspiration from replication in their outputs, and justify how their use of AI maintains authenticity and respects other creators. |
| E1Recognise AI’s role and influence in different contexts. | Learners can identify where different types of AI are present in their everyday lives. | Learners share examples of how AI systems have influenced their own choices and experiences at home, in school or online. | Learners can analyse how AI systems may shape individuals’ beliefs and behaviours as consumers, learners, workers and citizens. |
| E2Describe how AI systems perform tasks using language that addresses and clarifies common misconceptions. | Learners know AI is a non-human tool that produces outputs based on patterns of data and lacks authentic context or understanding. | Learners accurately describe how a specific AI tool carries out a task in order to address commonly-held misconceptions about how AI works. | Learners explain how different AI systems work using language that does not attribute human traits or abilities, knowing that their phrasing shapes understanding. |
| E3Evaluate whether AI outputs should be accepted, revised or rejected. | Learners understand why AI-generated outputs should be verified and recognise how they can verify the content themselves. | Learners verify AI-generated outputs for accuracy and relevance by consulting trusted sources and considering task-specific expectations. | Learners assess AI-generated outputs and justify decisions to accept, revise or reject them. |
| E4Examine how predictive AI systems provide recommendations that can inform or limit perspectives. | Learners know that AI can use data about a user to provide recommendations or predictions for them. | Learners consider when AI-generated recommendations might be helpful to them or when they may seem too narrow and too general. | Learners weigh the benefits and drawbacks of AI systems using data to shape access to information and consider how this might influence worldviews, ideas or behaviours. |
| E5Compare how AI systems consume energy and natural resources. | Learners recognise that computers and AI systems require resources to function. | Learners describe different ways that AI impacts the environment (e.g. hardware production, data centre development, water use, energy intensity). | Learners analyse how individual choices along with different design, deployment or business decisions can affect AI’s overall energy and resource use. |
| E6Explain how AI could be used to amplify societal biases. | Learners understand that biases can exist in the data used to train AI and can be perpetuated when humans design, develop and use AI systems. | Learners explain how biased data or design choices (e.g. stereotyped content, misclassification, unequal recommendations) can lead AI systems to generate unfair or skewed outcomes for certain groups. | Learners analyse how individuals, companies or institutions may build and deploy AI systems to serve particular interests and how these systems might shape opportunities, representations or public perceptions. |
| E7Analyse how well the use of an AI system aligns with ethical principles and human values. | Learners recognise that ethical AI use depends on a number of factors that include AI system design, development and a user’s own intentions. | Learners identify when AI use may have unintended impacts or implications that are different from a user’s immediate goals. | Learners evaluate the use of AI according to multiple ethical principles, considering trade-offs and who may benefit or be harmed. |
| M1Decide whether to use AI systems based on the nature of the task. | Learners identify a variety of AI systems and the tasks they are designed to support. | Learners use what they know about AI to determine whether AI is an appropriate digital tool for a specific task. | Learners determine whether AI is the right digital tool for a specific task by comparing the task’s complexity and need for human judgement with the ethical implications of AI use. |
| M2Choose an appropriate AI approach for a task by comparing how different AI systems operate and what they are best suited to do. | Learners recognise that some types of AI systems can be programmed with specific rules to accomplish tasks, while others can learn patterns from data. | Learners identify the benefits and drawbacks of using a rules-based approach and a machine learning approach to solve a problem. | Learners evaluate when AI is an effective approach for a task by considering factors such as context, data availability and quality, efficiency, transparency, desired outcomes and potential impacts. |
| M3Decompose a problem to determine when and how AI systems should be used to automate or augment tasks. | Learners identify the type of problem at hand and consider whether AI might help solve it. | Learners break a problem into component parts and consider ways AI might help with specific steps. | Learners deliberately assign tasks within a multi-step process based on appropriate human strengths and relevant AI capabilities. |
| M4Monitor and evaluate AI use throughout a problem-solving process. | Learners recognise that they should make decisions about AI use that support accountability, learning and fairness. | Learners compare AI outputs to desired results and know when to redirect AI systems or improve outputs themselves. | Learners establish checkpoints based on human and AI roles, monitor progress against success criteria and adjust roles accordingly. |
| S1Investigate how an AI system is intended to work, whom it is designed for and what its limitations are. | Learners identify what different AI systems are designed to do. | Learners describe the purpose, intended users and basic constraints of a specific AI tool. | Learners assess the strengths and limitations of an AI tool by considering its purpose, intended users, constraints and potential impacts. |
| S2Evaluate AI systems using defined criteria, expected outcomes, test cases and user feedback. | Learners define criteria for whether an AI system has accomplished a task. | Learners assess an AI system performance of a task using defined criteria and feedback from human reviews or benchmark tests. | Learners design their own evaluation criteria for an AI system, compare performance across different inputs and users and use it to propose improvements. |
| S3Design AI systems with attention to how data sources, selection and information flow influence behaviour and outputs. | Learners identify examples of data that might be used to train AI systems. | Learners compare the importance of data selection and collection methods in cases when AI is used to make decisions that affect others. | Learners evaluate how specific properties of a dataset (e.g. size, features, biases) affect the performance and impact of an AI model. |
| S4Improve AI systems to address and promote human well-being and societal benefit. | Learners recognise that AI systems can be designed or adjusted to better support individuals, communities and the environment. | Learners propose specific design changes to improve an AI system for themselves and others. | Learners design and justify improvements to an AI system based on technical constraints, ethical considerations and user needs. |