@inproceedings{b96fd3d453e545c79576a93f7d11c82e,
title = "The RAP system: Automatic feedback of oral presentation skills using multimodal analysis and low-Cost sensors",
abstract = "Developing communication skills in higher education students could be a challenge to professors due to the time needed to provide formative feedback. This work presents RAP, a scalable system to provide automatic feedback to entry-level students to develop basic oral presentation skills. The system improves the state-of-the-art by analyzing posture, gaze, volume, filled pauses and the slides of the presenters through data captured by very low-cost sensors. The system also provides an off-line feedback report with multimodal recordings of their performance. An initial evaluation of the system indicates that the system{\textquoteright}s feedback highly agrees with human feedback and that students considered that feedback useful to develop their oral presentation skills.",
keywords = "Filled-pauses, Gaze, Multimodal learning analytics, Posture",
author = "Xavier Ochoa and Federico Dom{\'i}nguez and Bruno Guam{\'a}n and Ricardo Maya and Gabriel Falcones and Jaime Castells",
year = "2018",
month = mar,
day = "7",
doi = "10.1145/3170358.3170406",
language = "English (US)",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "360--364",
booktitle = "Proceedings of the 8th International Conference on Learning Analytics and Knowledge",
note = "8th International Conference on Learning Analytics and Knowledge, LAK 2018 ; Conference date: 05-03-2018 Through 09-03-2018",
}