Use of AI in Economics Courses

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Description of Research Project

This proposal outlines a research initiative to investigate the integration of artificial intelligence (AI) into economics courses. The project aims to enhance student experience and improve learning outcomes by leveraging AI tools in classroom activities such as case studies, group discussions, and problem-solving worksheets. By exploring how AI can support the application of economic models, facilitate data analysis, enrich policy discussions, and assist with mathematical problem-solving, this research seeks to provide practical recommendations for educators, researchers, and administrators committed to advancing economics education.

The rapid advancement of artificial intelligence presents new opportunities and challenges for higher education. In economics courses, students often struggle to bridge the gap between theoretical models and real-world applications, analyze complex data, engage in dynamic policy debates, and master quantitative techniques. Traditional teaching methods, while foundational, may not fully address these challenges or cater to diverse learning needs. Integrating AI into economics education holds the potential to personalize learning, automate routine tasks, and foster deeper engagement with course material. This project seeks to systematically examine effective strategies for incorporating AI into the economics classroom to address persistent learning barriers and facilitate active, student-centered learning.

Project Objectives
• Identify and evaluate methods for integrating AI tools into economics courses that enhance student engagement and comprehension.
• Investigate the impact of AI-assisted activities—such as case studies, group discussions, and problem-solving worksheets—on learning outcomes.
• Examine how AI can support key areas of economics education, including the application of models to real-world scenarios, data analysis, policy evaluation, and mathematical problem-solving.
• Develop guidelines and best practices for educators to effectively utilize AI in classroom settings.

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Undergraduate Student Responsibilities

• Literature Review Support: Assist in gathering, organizing, and summarizing relevant academic articles, reports, and publications related to AI integration in economics education.
• Course Familiarization: Take an active role in understanding the existing structure, content, and teaching methods of the pilot economics course. Reflect on personal and peer learning experiences to identify gaps or areas where AI could enhance learning outcomes.
• Student Perspective Insights: Offer feedback and observations from a student’s viewpoint on the effectiveness of AI tools for learning, with particular attention to usability, engagement, and comprehension in the pilot economics course.
• Idea Generation for Course Improvement: Collaborate in brainstorming and proposing practical ideas for integrating AI into the course, such as personalised study recommendations, interactive simulations, or automated feedback systems, ensuring these align with student needs and expectations.
• Peer Engagement: Facilitate discussions and collect feedback from fellow students regarding their experiences with AI tools in the pilot course, helping to inform refinements and adjustments to the AI integration strategy.

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Qualifications Required

• Demonstrated familiarity with a range of AI tools and prior experience applying AI technologies to support university-level learning activities.
• Successful completion of at least one 3000-level economics course, with a solid understanding of relevant concepts and coursework expectations.