Birdwell, A. N., & Cook, J., & Weiss, R. S., & Mache, J. (2024, June), Board 289: From Logs to Learning: Applying Machine Learning to Instructor Intervention in Cybersecurity Exercises  Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. 10.18260/1-2--46864

\bibitem{asee_peer_46864}
  Birdwell, A. N., \& Cook, J., \& Weiss, R. S., \& Mache, J. (2024, June), \emph{Board 289: From Logs to Learning: Applying Machine Learning to Instructor Intervention in Cybersecurity Exercises}
  Paper presented at 2024 ASEE Annual Conference \& Exposition, Portland, Oregon.
  10.18260/1-2--46864

Aubrey Nicholas Birdwell, Jack Cook, Richard S Weiss, and Jens Mache.  "Board 289: From Logs to Learning: Applying Machine Learning to Instructor Intervention in Cybersecurity Exercises".  2024 ASEE Annual Conference & Exposition, Portland, Oregon, 2024, June.  ASEE Conferences, 2024.  https://peer.asee.org/46864 Internet.  21 Dec, 2024

\bibitem{asee_peer_46864}
  Aubrey Nicholas Birdwell, Jack Cook, Richard S Weiss, and Jens Mache.
  "Board 289: From Logs to Learning: Applying Machine Learning to Instructor Intervention in Cybersecurity Exercises".
  \emph{2024 ASEE Annual Conference \& Exposition, Portland, Oregon, 2024, June}.
  ASEE Conferences, 2024.
  https://peer.asee.org/46864 Internet.  21 Dec, 2024

@INPROCEEDINGS{asee_peer_46864
author = "Aubrey Nicholas Birdwell, Jack Cook, Richard S Weiss, and Jens Mache"
title = "Board 289: From Logs to Learning: Applying Machine Learning to Instructor Intervention in Cybersecurity Exercises"
booktitle = "2024 ASEE Annual Conference \& Exposition"
year = "2024"
month = "June"
address = "Portland, Oregon"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/46864}
number = {10.18260/1-2--46864}
}

TY  - CPAPER
AB  - Hands-on exercises provide students with practical skills and abilities. However, for exercises to be effective, students may need timely feedback while they are engaged to prevent them from getting stuck or frustrated. The goal of this project is to use machine learning to help identify such students such that timely and contextually appropriate hints can be given.

We are building a system that identifies students who are potentially in the most need of help, and suggests hints that the instructor could provide. The instructor can reject hints that they do not find appropriate. The hint system will be integrated into the EDURange cybersecurity education platform and will also be compatible with other platforms.

We are collecting data that will be analyzed to determine the efficacy of the tool, and to develop new hints and strategies for helping students. This project plans to use our machine learning system to create, test, and deploy semi-automated hints in a timely manner.
AU  - Aubrey Nicholas Birdwell
AU  - Jack Cook
AU  - Richard S Weiss
AU  - Jens Mache
CY  - Portland, Oregon
DA  - 2024/06/23
PB  - ASEE Conferences
TI  - Board 289: From Logs to Learning: Applying Machine Learning to Instructor Intervention in Cybersecurity Exercises
UR  - https://peer.asee.org/46864
DO  - 10.18260/1-2--46864
ER  -