Use digital tools to summarize data and create visualizations. Apply these tools to identify patterns, clean and prepare data, perform analysis, and build models for simulations to explore relationships and trends.

Examine how digital tools influence access, privacy, and bias, shaping opportunities and challenges in technology use. Consider the broader ethical and societal impacts of AI, including its role in decision-making, accountability, and policy.

Assess the technical limitations of digital tools and compare no-code, low-code, and high-code solutions based on their capabilities and use cases.

Choose the appropriate no-code, low-code, or high-code digital tool based on the task. Use multiple tools throughout the data investigation process and explore how digital tools are applied in the workforce.

Explore how block coding and computer code automate and enhance data analysis. Understand how coding enables reproducible processes and compare its advantages and limitations to no-code and low-code tools.

Understand how digital tools can support a broad range of diverse learners. Evaluate their effectiveness and impact, and explore inclusive data representations.