This study employed multimodal learning analytics (MMLA) to analyze behavioral dynamics during the ABCDE procedure in nursing education, focusing on gaze entropy, hand movement velocities, and proximity measures. Utilizing accelerometers and eye-tracking techniques, behaviorgrams were generated to depict various procedural phases. Results identified four primary phases characterized by distinct patterns of visual attention, hand movements, and proximity to the patient or instruments. The findings suggest that MMLA can offer valuable insights into procedural competence in medical education. This research underscores the potential of MMLA to provide detailed, objective evaluations of clinical procedures and their inherent complexities.
@article{arxiv.2312.05368,
title = {Toward Scalable and Transparent Multimodal Analytics to Study Standard Medical Procedures: Linking Hand Movement, Proximity, and Gaze Data},
author = {Ville Heilala and Sami Lehesvuori and Raija Hämäläinen and Tommi Kärkkäinen},
journal= {arXiv preprint arXiv:2312.05368},
year = {2023}
}
Comments
To be published in the Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing (SAC'24), April 8--12, 2024, Avila, Spain