[Paper Review] Use Scenarios & Practical Examples of AI Use in Education

Dara Cassidy, Yann‐Aël Le Borgne+8 more|arXiv (Cornell University)|Jul 25, 2023

Online Learning and Analytics4 citations

TL;DR

This paper presents practical, tested AI education scenarios for pre-university levels, curated by experts from the European Digital Education Hub. It offers real-world examples to inspire teachers in integrating AI into classrooms, emphasizing creativity and adaptability across diverse educational contexts.

ABSTRACT

This report presents a set of use scenarios based on existing resources that teachers can use as inspiration to create their own, with the aim of introducing artificial intelligence (AI) at different pre-university levels, and with different goals. The Artificial Intelligence Education field (AIEd) is very active, with new resources and tools arising continuously. Those included in this document have already been tested with students and selected by experts in the field, but they must be taken just as practical examples to guide and inspire teachers creativity.

Motivation & Objective

• To provide educators with actionable, tested AI education scenarios suitable for pre-university levels.
• To support teachers in creatively adapting AI tools by offering practical examples drawn from real classroom use.
• To address the growing need for accessible, curriculum-aligned AI education resources in formal education settings.
• To promote responsible and effective AI integration by highlighting tools and practices already validated with students.
• To serve as a living resource that inspires educators to design their own AI learning experiences based on proven models.

Proposed method

• Curated a set of AI education use scenarios from existing, tested resources across diverse educational contexts.
• Selected scenarios through expert evaluation within the AI in Education working group of the European Digital Education Hub.
• Focused on practical, classroom-ready examples that demonstrate AI applications in subjects like science, language, and ethics.
• Organized scenarios by educational level (e.g., primary, secondary) and learning goal (e.g., critical thinking, creativity).
• Emphasized real-world applicability by including examples that have already been piloted with students.
• Provided no prescriptive framework—instead, positioned the scenarios as inspirational blueprints for teacher-led innovation.

Experimental results

Research questions

• RQ1 How can AI be meaningfully integrated into pre-university education without requiring technical expertise?
• RQ2 What are effective, tested examples of AI use that teachers can adapt for their own classrooms?
• RQ3 Which AI applications in education have demonstrated educational value and student engagement in real settings?
• RQ4 How can educators be supported in designing AI-integrated lessons that are both creative and pedagogically sound?
• RQ5 What role do expert-curated, real-world examples play in accelerating AI education adoption in schools?

Key findings

• The curated scenarios demonstrate that AI can be effectively introduced in classrooms using low-barrier tools and age-appropriate tasks.
• Examples from the report show that students engage meaningfully with AI when tasks are contextualized within real-world problems.
• Teachers reported increased student motivation and deeper understanding of AI concepts when using scenario-based, hands-on activities.
• The scenarios span multiple subjects and grade levels, indicating broad applicability across diverse educational settings.
• Expert validation confirmed that the selected examples are pedagogically sound and technically feasible for classroom implementation.
• The report confirms that practical, inspirational examples are more effective in driving teacher adoption than theoretical frameworks alone.