@inproceedings{c1c716deaca14c42bde51c8fdfb6c017,
title = "Out of the Fr-{"}Eye{"}-ing Pan: Towards gaze-based models of attention during learning with technology in the classroom",
abstract = "Attention is critical to learning. Hence, advanced learning technologies should benefit from mechanisms to monitor and respond to learners' attentional states. We study the feasibility of integrating commercial off-The-shelf (COTS) eye trackers to monitor attention during interactions with a learning technology called GuruTutor. We tested our implementation on 135 students in a noisy computer-enabled high school classroom and were able to collect a median 95% valid eye gaze data in 85% of the sessions where gaze data was successfully recorded. Machine learning methods were employed to develop automated detectors of mind wandering (MW) -A phenomenon involving a shift in attention from task-related to task-unrelated thoughts that is negatively correlated with performance. Our student-independent, gaze-based models could detect MW with an accuracy (F1 of MW = 0.59) significantly greater than chance (F1 of MW = 0.24). Predicted rates of mind wandering were negatively related to posttest performance, providing evidence for the predictive validity of the detector. We discuss next steps towards developing gaze-based, attention-Aware, learning technologies that can be deployed in noisy, real-world environments.",
keywords = "Attention-Aware learning, Cyberlearning, Eye-gaze, Intelligent tutoring systems, Mind wandering",
author = "Stephen Hutt and Caitlin Mills and Nigel Bosch and Kristina Krasich and James Brockmole and Sidney D'mello",
note = "Publisher Copyright: {\textcopyright}2017 ACM.; 25th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2017 ; Conference date: 09-07-2017 Through 12-07-2017",
year = "2017",
month = jul,
day = "9",
doi = "10.1145/3079628.3079669",
language = "English (US)",
series = "UMAP 2017 - Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization",
publisher = "Association for Computing Machinery",
pages = "94--103",
booktitle = "UMAP 2017 - Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization",
address = "United States",
}