This is an update from the OpenBCI Discovery Program. Click here for details on how to apply.
What are we making?
Koalacademy is a platform that will utilize brain activity during studying to predict whether learning will be successful or not. We will be developing machine learning models and leveraging established research on the subsequent memory effect (SME) in an attempt to provide the most accurate real-time predictions of information retention.
How are OpenBCI tools being applied?
Live EEG data from the OpenBCI Ultracortex Mark IV will be used to give real-time feedback to users about whether learning is likely to be successful or not. This will be used to adapt the studying session to maximize knowledge acquisition.
Why is this important?
Koalacademy will let the user target weak areas while also avoiding unnecessary review of well-learned topics. In the first iteration of this project, we are focusing on English speakers learning Mandarin, but this has broad applicability for learning other languages, as well as for learning in general. Increasing studying efficiency will enable quicker progression in a new field which is essential in our rapidly progressing society.
Who is involved in this project?
This project is being completed by the NeurAlbertaTech 2021 Software Project Team which is composed of a core group of undergraduate students from the University of Alberta (Edmonton, Alberta, Canada) with skills in neuroscience, web development, machine learning, and with previous experience building custom BCIs. This is a group of talented and passionate students who are looking to push forward neurotechnology as a whole!
You can learn more about the team here on the NeurAlbertaTech website.
Development is already well underway, and we will be posting our about progress and access to our repositories here in the OpenBCI Community, over the coming months. Thank you to everyone at OpenBCI for admitting us into the OpenBCI Sponsorship Program!