Economics Teaching & Learning with AI: Tools for Students & Teachers

Generative AI is revolutionizing the way we teach and learn economics, and we’re here to help you embrace this exciting transformation! In our latest video, I share practical tips and strategies for using AI tools to create engaging lessons, personalised revision aids, and more. To support you further, we’re offering a free, editable PowerPoint packed with ideas and examples for integrating AI into your economics teaching.

Key Summary of Ideas from the PPT on Using AI in Economics Teaching

The Basics of Generative AI

• Definition of AI: Machines or systems programmed to mimic human intelligence.
• Large Language Models (LLMs): AI trained on billions of words to understand and generate human-like text.
• How AI Processes Text: Breaks input into "tokens," assigns numerical vectors, and predicts the next word based on learned patterns and context.

Teaching Prompt Engineering

• Encouraging Active Learning:
  • Shift focus from passive interactions (student asks, AI answers) to active engagements (AI asks questions, students respond).
  • Emphasize critical skills: memory retrieval, problem-solving, feedback response, and deep thinking.
• Examples of Prompts for Learning:
  • Exploring behavioral economics concepts like "loss aversion."
  • Generating flashcards, quizzes, and glossaries for specific topics.
  • Asking AI to simulate case studies and explain economic theories succinctly.

Using AI to Create Revision Tools

• Personalized Learning Aids:
  • Flashcards tailored to specific economics topics like elasticity or fiscal policy.
  • Key term glossaries extracted from texts and converted into user-friendly formats.
  • Summaries of complex theories into bullet points or concise text.
• Interactive Study Plans: AI-generated revision schedules to prioritize weak areas.

Classroom Applications for Teachers

• Enhanced Teaching Methods:
  • Generating exam-style questions aligned with syllabus objectives (e.g., comparing Keynes vs. Hayek).
  • Creating real-world case studies, such as the economic impact of Brexit.
  • Providing instant feedback on student responses to exam-style questions.
• Data-Driven Insights: Tools to explain and visualize abstract concepts like price elasticity or Schumpeter’s innovation theory.

AI for Deep Learning in Economics

• Custom Instructions for AI:
  • Students instruct AI to simulate learning journeys, such as identifying key theories in behavioral economics or simulating economic policy recommendations.
• Interactive Learning Journeys:
  • AI engages students in reflective thinking and evaluation by posing follow-up questions or scenarios.

Integrating AI in Economic Contexts

• Examples of Intelligent Prompts:
  • Asking about Schumpeter’s causes of innovation or the economic implications of fiscal policy.
  • Contrasting the views of economists like Keynes and Hayek on aggregate demand.
• Real-World Case Studies:
  • Using AI to simulate trade impacts, labor market shifts, or policy effects, as in Brexit analysis.

Broadening the Scope with AI

• Adaptability for Multiple Exam Boards:
  • Content can be tailored for AQA, OCR, Edexcel, IB, and CIE students.
• Global and Local Relevance:
  • AI tools help link global economic trends (e.g., globalization, digital innovation) with UK-specific examples (e.g., NHS investment, Brexit).