How to Open Science: Promoting Principles and Reproducibility Practices Within the Artificial Intelligence in Education Community

Abstract

Across the past decade, open science has increased in momentum, making research more openly available and reproducible. 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. While completed, generalized AI models take advantage of available open science practices, models used during the actual research process are not made available. In this tutorial, we will provide an overview of open science practices and their benefits and mitigation within AI education research. In the second part of this tutorial, we will use the Open Science Framework to make, collaborate, and share projects - demonstrating how to make materials, code, and data open. The final part of this tutorial will go over some mitigation strategies when releasing datasets and materials so other researchers may easily reproduce them. Participants in this tutorial will learn what the practices of open science are, how to use them in their own research, and how to use the Open Science Framework. The website (https://aied2023-tutorial.howtoopenscience.com/ ) and associated resources can be found on an Open Science Framework project (https://doi.org/10.17605/osf.io/yd9kr ).