Massive Open Online Courses (MOOCs) have become an attractive opportunity for people around the world to gain knowledge and skills. Despite the initial enthusiasm of the first wave of MOOCs and the subsequent research efforts, MOOCs today suffer from retention issues: many MOOC learners start but do not finish. A main culprit is the lack of oversight and directions: learners need to be skilled in self-regulated learning to monitor themselves and their progress, keep their focus and plan their learning. Many learners lack such skills and as a consequence do not succeed in their chosen MOOC. Many of today's MOOCs are centered around video lectures, which provide ample opportunities for learners to become distracted and lose their attention without realizing it. If we were able to detect learners' loss of attention in real-time, we would be able to intervene and ideally return learners' attention to the video. This is the scenario we investigate: we designed a privacy-aware system (IntelliEye) that makes use of learners' Webcam feeds to determine---in real-time---when they no longer pay attention to the lecture videos. IntelliEye makes learners aware of their attention loss via visual and auditory cues. We deployed IntelliEye in a MOOC across a period of 74 days and explore to what extent MOOC learners accept it as part of their learning and to what extent it influences learners' behaviour. IntelliEye is open-sourced at https://github.com/Yue-ZHAO/IntelliEye.
%0 Conference Paper
%1 Robal:2018:IEM:3209542.3209547
%A Robal, Tarmo
%A Zhao, Yue
%A Lofi, Christoph
%A Hauff, Claudia
%B Proceedings of the 29th on Hypertext and Social Media
%C New York, NY, USA
%D 2018
%I ACM
%K attention eye-tracking hypertext2018 mooc
%P 106--114
%R 10.1145/3209542.3209547
%T IntelliEye: Enhancing MOOC Learners' Video Watching Experience Through Real-Time Attention Tracking
%U http://doi.acm.org/10.1145/3209542.3209547
%X Massive Open Online Courses (MOOCs) have become an attractive opportunity for people around the world to gain knowledge and skills. Despite the initial enthusiasm of the first wave of MOOCs and the subsequent research efforts, MOOCs today suffer from retention issues: many MOOC learners start but do not finish. A main culprit is the lack of oversight and directions: learners need to be skilled in self-regulated learning to monitor themselves and their progress, keep their focus and plan their learning. Many learners lack such skills and as a consequence do not succeed in their chosen MOOC. Many of today's MOOCs are centered around video lectures, which provide ample opportunities for learners to become distracted and lose their attention without realizing it. If we were able to detect learners' loss of attention in real-time, we would be able to intervene and ideally return learners' attention to the video. This is the scenario we investigate: we designed a privacy-aware system (IntelliEye) that makes use of learners' Webcam feeds to determine---in real-time---when they no longer pay attention to the lecture videos. IntelliEye makes learners aware of their attention loss via visual and auditory cues. We deployed IntelliEye in a MOOC across a period of 74 days and explore to what extent MOOC learners accept it as part of their learning and to what extent it influences learners' behaviour. IntelliEye is open-sourced at https://github.com/Yue-ZHAO/IntelliEye.
%@ 978-1-4503-5427-1
@inproceedings{Robal:2018:IEM:3209542.3209547,
abstract = {Massive Open Online Courses (MOOCs) have become an attractive opportunity for people around the world to gain knowledge and skills. Despite the initial enthusiasm of the first wave of MOOCs and the subsequent research efforts, MOOCs today suffer from retention issues: many MOOC learners start but do not finish. A main culprit is the lack of oversight and directions: learners need to be skilled in self-regulated learning to monitor themselves and their progress, keep their focus and plan their learning. Many learners lack such skills and as a consequence do not succeed in their chosen MOOC. Many of today's MOOCs are centered around video lectures, which provide ample opportunities for learners to become distracted and lose their attention without realizing it. If we were able to detect learners' loss of attention in real-time, we would be able to intervene and ideally return learners' attention to the video. This is the scenario we investigate: we designed a privacy-aware system (IntelliEye) that makes use of learners' Webcam feeds to determine---in real-time---when they no longer pay attention to the lecture videos. IntelliEye makes learners aware of their attention loss via visual and auditory cues. We deployed IntelliEye in a MOOC across a period of 74 days and explore to what extent MOOC learners accept it as part of their learning and to what extent it influences learners' behaviour. IntelliEye is open-sourced at https://github.com/Yue-ZHAO/IntelliEye.},
acmid = {3209547},
added-at = {2018-07-11T20:13:09.000+0200},
address = {New York, NY, USA},
author = {Robal, Tarmo and Zhao, Yue and Lofi, Christoph and Hauff, Claudia},
biburl = {https://www.bibsonomy.org/bibtex/24d2bd7637a5b04573b1d7bb6e58f8136/brusilovsky},
booktitle = {Proceedings of the 29th on Hypertext and Social Media},
description = {IntelliEye},
doi = {10.1145/3209542.3209547},
interhash = {10f56f7681e096f9de9ba02fabe985a0},
intrahash = {4d2bd7637a5b04573b1d7bb6e58f8136},
isbn = {978-1-4503-5427-1},
keywords = {attention eye-tracking hypertext2018 mooc},
location = {Baltimore, MD, USA},
numpages = {9},
pages = {106--114},
publisher = {ACM},
series = {HT '18},
timestamp = {2018-07-11T20:13:09.000+0200},
title = {IntelliEye: Enhancing MOOC Learners' Video Watching Experience Through Real-Time Attention Tracking},
url = {http://doi.acm.org/10.1145/3209542.3209547},
year = 2018
}