100 + Examples for Technology-Rich Teaching

Remember, obtain, or acknowledge facts and interpretations.

• Recall: List crucial terms for an unit glossary.
• Find: Locate a primary-source quote supporting an insurance claim.
• Book mark: Conserve reliable resources to a common collection.
• Tag: Apply exact keywords to arrange resources.
• Get: Use spaced-repetition/flashcards to review formulas.
• Trigger (recall): Ask an AI to restate meanings from class notes, after that confirm with sources.

Explain, sum up, analyze, and contrast concepts.

• Sum up: Write a succinct abstract of a podcast episode.
• Paraphrase: Rephrase a dense paragraph to make clear definition.
• Annotate: Add notes that clarify motif and proof in a shared doc.
• Contrast: Build a side-by-side chart of two plans.
• Explain: Record a short screencast clarifying a procedure.
• Prompt (explain): Ask an AI to discuss a concept at two quality degrees; cite-check claims.

Usage expertise to carry out tasks, fix issues, or generate artefacts.

• Demonstrate: Tape a functioned instance addressing a square.
• Carry out: Run a simulation and record end results.
• Model: Develop a low-fidelity version in Slides or Canva.
• Code: Compose a short script to transform or verify data.
• Apply rubric: Score a sample item using standards.
• Improve timely: Iteratively change an AI prompt to meet restraints (audience, size, citations).

Damage principles apart, determine patterns and connections, take a look at structure.

• Assess: Compare 2 editorials for predisposition using an evidence checklist.
• Organize: Produce a timeline that separates causes and effects.
• Categorize: Kind claims, evidence, and thinking right into groups.
• Visualize: Construct graphes that expose trends in a dataset.
• Trace sources: Verify quotes and acknowledgments back to originals.
• Compare models: Assess 2 AI results on precision and transparency.

Court high quality, justify choices, and defend positions making use of requirements.

• Review: Give evidence-based feedback on a peer draft.
• Validate: Fact-check data and mention authoritative sources.
• Moderate: Assist in a class discussion for relevance and respect.
• A/B assess: Test two options and warrant the more powerful selection.
• Red-team: Stress-test an AI-generated plan for risks and mistakes.
• Reflect: Compose a procedure note justifying critical choices with criteria.

Manufacture concepts to generate initial, deliberate work.

• Design: Strategy a product with audience, objective, and restrictions.
• Make up: Generate a podcast/video describing a real-world issue.
• Remix morally: Change public-domain/CC media with acknowledgment.
• Prototype (hi-fi): Construct a refined artefact and user-test it.
• Chain (AI): Orchestrate multi-step AI jobs (rundown → draft → cite-check → modification) with human oversight.
• Automate: Use simple scripts/AI agents to simplify an operations; record restrictions.