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Promoting Open Science in Artificial Intelligence: An Interactive Tutorial on Licensing, Data, and Containers

  • Aaron Haim,
  • Stephen Hutt,
  • Stacy T. Shaw,
  • Neil T. Heffernan

摘要

Across the past decade, the open science movement has increased its momentum, making research more openly available and reproducible across different environments. In parallel, artificial intelligence (AI), especially within education, has produced effective models to better predict student outcomes, generate content, and provide a greater number of observable features for teachers. However, there is a discernible gap between the understanding and application of open science practices in artificial intelligence. In this tutorial, we will expand the knowledge base towards open data and open analysis. First, we will introduce the complexities of intellectual property and licensing within open science. Next, we will provide insights into data sharing methods that preserve the privacy of participants. Finally, we will conclude with an interactive demonstration on sharing research materials reproducibly. We will tailor the content towards the needs and goals of the participants, enabling researchers with the necessary resources and knowledge to implement these concepts effectively and responsibly.