How to Open Science: Promoting Principles and Reproducibility Practices within the Learning Analytics Community
Conference: LAK 2023 | March 13th - 17th, 2023 | Arlington, Texas, USA
In Person (SWSH 424): #March 13th 1:30 PM - 3:00 PM, 3:30 PM - 5:00 PM CDT# $2023-03-13 13:30:00-15:00:00,15:30:00-17:00:00 -05:00$
Online (Zoom via Email): #March 14th 4:00 PM - 7:00 PM CDT# $2023-03-14 16:00:00-19:00:00 -05:00$
Across the past decade, open science has increased in momentum, making research more openly available and reproducible. In parallel, learning analytics, as a subfield of education technology, has been increasing as well, providing more accurate statistical models and integrations to improve learning. However, open science and learning analytics rarely tend to intersect, causing a bit of difficulty when trying to reuse methodologies, datasets, analyses for replication, reproduction, or an entirely separate end goal. In this tutorial, we will provide an overview of open science principles and their benefits and mitigation within research. In the second part of this tutorial, we will provide an example on using the Open Science Framework to make, collaborate, and share projects. The final part of this tutorial will go over some mitigation strategies when releasing datasets and materials such that other researchers may easily reproduce them. Participants in this tutorial will gain a better understanding of open science, how it is used, and how to apply it themselves.
This project is available on OSF under the CC-BY-4.0 License.