Explaining Student Behavior at Scale. Van der Sluis, F., Ginn, J., & Van der Zee, T. In Proceedings of the Third (2016) ACM Conference on Learning @ Scale - L@S '16, pages 51-60, 2016. ACM Press. ![Explaining Student Behavior at Scale [link]](https://bibbase.org/img/filetypes/link.svg "link")
Website abstract bibtex Understanding why and how students interact with educational videos is essential to further improve the quality of MOOCs. In this paper, we look at the complexity of videos to explain two related aspects of student behavior: the dwelling time (how much time students spend watching a video) and the dwelling rate (how much of the video they actually see). Building on a strong tradition of psycholinguistics, we formalize a definition for information complexity in videos. Furthermore, building on recent advancements in time-on-task measures we formalize dwelling time and dwelling rate based on click-stream trace data. The resulting computational model of video complexity explains 22.44% of the variance in the dwelling rate for students that finish watching a paragraph of a video. Video complexity and student dwelling show a polynomial relationship, where both low and high complexity increases dwelling. These results indicate why students spend more time watching (and possibly contemplating about) a video. Furthermore, they show that even fairly straightforward proxies of student behavior such as dwelling can already have multiple interpretations; illustrating the challenge of sense-making from learning analytics.
@inProceedings{
title = {Explaining Student Behavior at Scale},
type = {inProceedings},
year = {2016},
identifiers = {[object Object]},
pages = {51-60},
websites = {http://dl.acm.org/citation.cfm?doid=2876034.2876051},
publisher = {ACM Press},
city = {New York, New York, USA},
id = {2d0b82a5-30d3-34ff-bfb6-086739bf14f9},
created = {2016-09-01T15:46:29.000Z},
accessed = {2016-09-01},
file_attached = {false},
profile_id = {15d5ede6-80ea-3b4c-a7e1-5b79ba86707d},
group_id = {a7fbd406-18f3-3b0b-bf98-38c617d1e04e},
last_modified = {2017-03-14T17:40:34.521Z},
tags = {ayse,behaviour,engagement,video watching},
read = {false},
starred = {false},
authored = {false},
confirmed = {false},
hidden = {false},
private_publication = {false},
abstract = {Understanding why and how students interact with educational videos is essential to further improve the quality of MOOCs. In this paper, we look at the complexity of videos to explain two related aspects of student behavior: the dwelling time (how much time students spend watching a video) and the dwelling rate (how much of the video they actually see). Building on a strong tradition of psycholinguistics, we formalize a definition for information complexity in videos. Furthermore, building on recent advancements in time-on-task measures we formalize dwelling time and dwelling rate based on click-stream trace data. The resulting computational model of video complexity explains 22.44% of the variance in the dwelling rate for students that finish watching a paragraph of a video. Video complexity and student dwelling show a polynomial relationship, where both low and high complexity increases dwelling. These results indicate why students spend more time watching (and possibly contemplating about) a video. Furthermore, they show that even fairly straightforward proxies of student behavior such as dwelling can already have multiple interpretations; illustrating the challenge of sense-making from learning analytics.},
bibtype = {inProceedings},
author = {Van der Sluis, Frans and Ginn, Jasper and Van der Zee, Tim},
booktitle = {Proceedings of the Third (2016) ACM Conference on Learning @ Scale - L@S '16}
}
Downloads: 0
{"_id":"HJmAYGbyu7cC4TWcy","bibbaseid":"vandersluis-ginn-vanderzee-explainingstudentbehavioratscale-2016","authorIDs":[],"author_short":["Van der Sluis, F.","Ginn, J.","Van der Zee, T."],"bibdata":{"title":"Explaining Student Behavior at Scale","type":"inProceedings","year":"2016","identifiers":"[object Object]","pages":"51-60","websites":"http://dl.acm.org/citation.cfm?doid=2876034.2876051","publisher":"ACM Press","city":"New York, New York, USA","id":"2d0b82a5-30d3-34ff-bfb6-086739bf14f9","created":"2016-09-01T15:46:29.000Z","accessed":"2016-09-01","file_attached":false,"profile_id":"15d5ede6-80ea-3b4c-a7e1-5b79ba86707d","group_id":"a7fbd406-18f3-3b0b-bf98-38c617d1e04e","last_modified":"2017-03-14T17:40:34.521Z","tags":"ayse,behaviour,engagement,video watching","read":false,"starred":false,"authored":false,"confirmed":false,"hidden":false,"private_publication":false,"abstract":"Understanding why and how students interact with educational videos is essential to further improve the quality of MOOCs. In this paper, we look at the complexity of videos to explain two related aspects of student behavior: the dwelling time (how much time students spend watching a video) and the dwelling rate (how much of the video they actually see). Building on a strong tradition of psycholinguistics, we formalize a definition for information complexity in videos. Furthermore, building on recent advancements in time-on-task measures we formalize dwelling time and dwelling rate based on click-stream trace data. The resulting computational model of video complexity explains 22.44% of the variance in the dwelling rate for students that finish watching a paragraph of a video. Video complexity and student dwelling show a polynomial relationship, where both low and high complexity increases dwelling. These results indicate why students spend more time watching (and possibly contemplating about) a video. Furthermore, they show that even fairly straightforward proxies of student behavior such as dwelling can already have multiple interpretations; illustrating the challenge of sense-making from learning analytics.","bibtype":"inProceedings","author":"Van der Sluis, Frans and Ginn, Jasper and Van der Zee, Tim","booktitle":"Proceedings of the Third (2016) ACM Conference on Learning @ Scale - L@S '16","bibtex":"@inProceedings{\n title = {Explaining Student Behavior at Scale},\n type = {inProceedings},\n year = {2016},\n identifiers = {[object Object]},\n pages = {51-60},\n websites = {http://dl.acm.org/citation.cfm?doid=2876034.2876051},\n publisher = {ACM Press},\n city = {New York, New York, USA},\n id = {2d0b82a5-30d3-34ff-bfb6-086739bf14f9},\n created = {2016-09-01T15:46:29.000Z},\n accessed = {2016-09-01},\n file_attached = {false},\n profile_id = {15d5ede6-80ea-3b4c-a7e1-5b79ba86707d},\n group_id = {a7fbd406-18f3-3b0b-bf98-38c617d1e04e},\n last_modified = {2017-03-14T17:40:34.521Z},\n tags = {ayse,behaviour,engagement,video watching},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {Understanding why and how students interact with educational videos is essential to further improve the quality of MOOCs. In this paper, we look at the complexity of videos to explain two related aspects of student behavior: the dwelling time (how much time students spend watching a video) and the dwelling rate (how much of the video they actually see). Building on a strong tradition of psycholinguistics, we formalize a definition for information complexity in videos. Furthermore, building on recent advancements in time-on-task measures we formalize dwelling time and dwelling rate based on click-stream trace data. The resulting computational model of video complexity explains 22.44% of the variance in the dwelling rate for students that finish watching a paragraph of a video. Video complexity and student dwelling show a polynomial relationship, where both low and high complexity increases dwelling. These results indicate why students spend more time watching (and possibly contemplating about) a video. Furthermore, they show that even fairly straightforward proxies of student behavior such as dwelling can already have multiple interpretations; illustrating the challenge of sense-making from learning analytics.},\n bibtype = {inProceedings},\n author = {Van der Sluis, Frans and Ginn, Jasper and Van der Zee, Tim},\n booktitle = {Proceedings of the Third (2016) ACM Conference on Learning @ Scale - L@S '16}\n}","author_short":["Van der Sluis, F.","Ginn, J.","Van der Zee, T."],"urls":{"Website":"http://dl.acm.org/citation.cfm?doid=2876034.2876051"},"bibbaseid":"vandersluis-ginn-vanderzee-explainingstudentbehavioratscale-2016","role":"author","downloads":0},"bibtype":"inProceedings","creationDate":"2020-02-06T23:44:30.830Z","downloads":0,"keywords":[],"search_terms":["explaining","student","behavior","scale","van der sluis","ginn","van der zee"],"title":"Explaining Student Behavior at Scale","year":2016}