Maestro: A Gamified Platform for Teaching AI Robustness
Project Overview
The document presents an overview of Maestro, a gamified educational platform aimed at teaching undergraduate students fundamental AI concepts through interactive and goal-oriented experiences. It highlights the significance of incorporating competitive learning environments to boost student engagement and motivation. Key applications of Maestro include its use of gamification elements, such as leaderboards, which not only enhance learning outcomes but also encourage collaboration among students. Findings from surveys indicate that students perceive Maestro as an effective tool for learning AI, citing the gamified aspects as particularly beneficial in fostering a competitive spirit and enhancing the overall educational experience. This suggests that integrating generative AI in educational frameworks can lead to improved student motivation and engagement, ultimately contributing to a deeper understanding of AI concepts.
Key Applications
Maestro, a gamified platform for teaching robust AI
Context: Undergraduate courses focusing on robust AI at the University of California, Irvine
Implementation: Students engage in competitive programming assignments using goal-based scenarios within the Maestro platform, integrated with Gradescope for submissions.
Outcomes: Increased student engagement, motivation, and skill acquisition in robust AI; positive feedback on the gamification features, particularly the leaderboard.
Challenges: Limited existing educational tools specifically targeting robust AI; ensuring effective adaptation of the platform to various course structures without loss of educational quality.
Implementation Barriers
Technical
Lack of existing educational tools specifically for robust AI education.
Proposed Solutions: Develop new platforms like Maestro that are publicly available and can be adapted for various educational contexts.
Project Team
Margarita Geleta
Researcher
Jiacen Xu
Researcher
Manikanta Loya
Researcher
Junlin Wang
Researcher
Sameer Singh
Researcher
Zhou Li
Researcher
Sergio Gago-Masague
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Margarita Geleta, Jiacen Xu, Manikanta Loya, Junlin Wang, Sameer Singh, Zhou Li, Sergio Gago-Masague
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18
Analysis Provider: Openai