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Detecting Behavioral Engagement of Students in the Wild Based on Contextual and Visual Data
[article]
2019
arXiv
pre-print
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To investigate the detection of students' behavioral engagement (On-Task vs. Off-Task), we propose a two-phase approach in this study. ...
Our cross-classroom and cross-platform experiments showed the proposed generic and multi-modal behavioral engagement models' applicability to a different set of students or different subject areas. ...
In this study, our goal is to detect students' behavioral engagement [5] (i.e., On-Task vs. Off-Task states) [7, 8, 4] in 1:1 digital learning scenarios. ...
arXiv:1901.06291v1
fatcat:ka5s2ufxt5ak3jfd7gurk52jai
Automatic Detection of Learning-Centered Affective States in the Wild
2015
Proceedings of the 20th International Conference on Intelligent User Interfaces - IUI '15
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Affect detection is a key component in developing intelligent educational interfaces that are capable of responding to the affective needs of students. ...
(.649), delight (.867), engagement (.679), and frustration (.631) as well as a fiveway overall classification of affect (.655), despite the noisy nature of the data. ...
Any opinions, findings and conclusions, or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the NSF or the Bill & Melinda Gates Foundation. ...
doi:10.1145/2678025.2701397
dblp:conf/iui/BoschDBOSVWZ15
fatcat:3m2yfz25a5enjpjhaufzoo4eau
Automatic Recognition of Student Engagement using Deep Learning and Facial Expression
[article]
2019
arXiv
pre-print
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2018 pre-print arXiv:1808.02324v3 fatcat:s6jh4rmjpjhjtoeojkzua4j2yaOther Versions
Engagement is a key indicator of the quality of learning experience, and one that plays a major role in developing intelligent educational interfaces. ...
Any such interface requires the ability to recognise the level of engagement in order to respond appropriately; however, there is very little existing data to learn from, and new data is expensive and ...
To handle the complexity and ambiguity of engagement concept, our data is annotated in two steps, separating the behavioral and emotional dimensions of engagement. ...
arXiv:1808.02324v5
fatcat:tphgzg6torblrbdqbrrpvbeari
EmotiW 2018: Audio-Video, Student Engagement and Group-Level Affect Prediction
[article]
2018
arXiv
pre-print
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The challenge aims at providing a common platform to researchers working in the affective computing community to benchmark their algorithms on 'in the wild' data. ...
This paper details the sixth Emotion Recognition in the Wild (EmotiW) challenge. EmotiW 2018 is a grand challenge in the ACM International Conference on Multimodal Interaction 2018, Colorado, USA. ...
Due to unavailability of datasets for student engagement detection in the wild new dataset for student engagement detection is created in this work. ...
arXiv:1808.07773v1
fatcat:rykklyagvbdudbxh3nnqtoorqu
Prediction and Localization of Student Engagement in the Wild
[article]
2018
arXiv
pre-print
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In this paper, we introduce a new dataset for student engagement detection and localization. ...
Recognizing the lack of any publicly available dataset in the domain of user engagement, a new 'in the wild' dataset is created to study the subject engagement problem. ...
Prediction and Localization of Student Engagement in the Wild WOODSTOCK'97, July 1997, El Paso, Texas USA ...
arXiv:1804.00858v4
fatcat:2y3leaq5rbckppv5cqh3vmunbu
Plenary Talk II Measuring Student Engagement in Early Engineering Coursework
2020
2020 15th International Conference on Computer Engineering and Systems (ICCES)
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Engineering programs suffer from a high rate of attrition in the freshman year, primarily due to poor engagement of students with their classes. ...
This talk describes recent efforts for quantifying students' engagement in early engineering coursework, through designing, implementing, and testing a system to measure the students' emotional, behavioral ...
) pilot testing of the system's effectiveness in gathering meaningful data for subsequent work on emotional, behavioral, and cognitive metrics of engagement. ...
doi:10.1109/icces51560.2020.9334628
fatcat:sykgrhjcszdcfcym6liac4x3ve
Multimodal Affect Detection in the Wild
2015
Proceedings of the 2015 ACM on International Conference on Multimodal Interaction - ICMI '15
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Affect detection is an important component of computerized learning environments that adapt the interface and materials to students' affect. ...
Facial features and interaction log features are considered as modalities for affect detection in this scenario, each with their own advantages. ...
Any opinions, findings and conclusions, or recommendations expressed in this paper do not necessarily reflect the views of the NSF or the Bill & Melinda Gates Foundation. ...
doi:10.1145/2818346.2823316
dblp:conf/icmi/Bosch15
fatcat:szsiuif5hzc4feoi74jdf6hstq
Engagement in Human-Agent Interaction: An Overview
2020
Frontiers in Robotics and AI
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We also present models for detecting engagement and for generating multimodal behaviors to show engagement. ...
While the notion of engagement is actively being studied in a diverse set of domains, the term has been used to refer to a number of related, but different concepts. ...
"in-the-wild." ...
doi:10.3389/frobt.2020.00092
pmid:33501259
pmcid:PMC7806067
fatcat:zdvt343f55a33l7bo33zwr7ta4
DAiSEE: Towards User Engagement Recognition in the Wild
[article]
2018
arXiv
pre-print
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, and frustration in the wild. ...
We introduce DAiSEE, the first multi-label video classification dataset comprising of 9068 video snippets captured from 112 users for recognizing the user affective states of boredom, confusion, engagement ...
Understanding how engaged a student is, is an important task that can increase the learning intake of a student. ...
arXiv:1609.01885v6
fatcat:dgbz4gsrovcelhabajawysgm4e
Investigating the Reliability of Self-report Data in the Wild: The Quest for Ground Truth
[article]
2021
arXiv
pre-print
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2021 pre-print arXiv:2107.00389v1 fatcat:qnnifleacbdyfayzdouhsuweey
In this research, we investigate the reliability of self-report surveys in the wild by studying the confidence level of responses and survey completion time. ...
., student engagement inference) by recruiting 23 students in a high school setting over a period of 4 weeks. ...
ACKNOWLEDGMENTS This research is supported by the Australian Government through the Australian Research Council's Linkage Projects funding scheme (project LP150100246). ...
arXiv:2107.00389v2
fatcat:yruewvv5xbhdleozzpndh4fici
Improving state-of-the-art in Detecting Student Engagement with Resnet and TCN Hybrid Network
[article]
2021
arXiv
pre-print
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Varying levels of engagement exhibited by students in an online classroom is an affective behavior that takes place over space and time. ...
Automatic detection of students' engagement in online learning settings is a key element to improve the quality of learning and to deliver personalized learning materials to them. ...
The dataset contains 9,068 videos captured from 112 students in online courses for recognizing their affective states of boredom, confusion, engagement, and frustration in the wild. ...
arXiv:2104.10122v2
fatcat:g2sqeicqkbhwjii42vdgaii7xe
Citizen Science in Schools: Students Collect Valuable Mammal Data for Science, Conservation, and Community Engagement
2018
BioScience
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Ninety-four percent of the camera traps were set in accordance with scientific protocols, and the teachers reported the experience as highly engaging for their students. ...
Indian, Kenyan, Mexican, and American students used camera traps near their schools and detected 13-37 species, all of which were verified by professionals. ...
Acknowledgments We thank the 28 teachers and their collective thousands of students from Carroll, East Cary, East Wake, North Garner, ...
doi:10.1093/biosci/biy141
fatcat:2axfudu7p5fzhfcdpoavd4wgae
Teaching Science through Inquiry Based Field Experiences Using Orientation and Mobility
2018
Journal of Science Education for Students with Disabilities
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Instruction in science can be difficult for students with visual impairments due to the use of visual instruction that is often used for conceptual understanding. ...
to explore and make conclusions about their environments through the use of all senses. ...
and to help students fully engage in the numerous fieldbased experiences with their peers. ...
doi:10.14448/jsesd.10.0003
fatcat:5yjsglpm5fd6ph7qfqkd3o4f7a
Does Asking Adolescents About Pornography Make Them Use It? A Test of the Question–Behavior Effect
2018
Journal of Sex Research
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However, repeated measurement may induce the question-behavior effect (QBE)-the phenomenon where asking about a behavior changes the probability of engaging in the behavior in the future. ...
Using an online panel sample of Croatian adolescents (Mage at baseline = 15.8, SD = .50), the present study explored the QBE in the context of adolescent pornography use. ...
Specifically, the QBE involves changes in the probability of engaging in a behavior as a consequence of repeated survey assessments of that behavior (Sprott et al., 2006) . ...
doi:10.1080/00224499.2018.1501549
pmid:30074822
fatcat:pkp7t2pj3vedjf2vwwykaetdcu
Page 3846 of Psychological Abstracts Vol. 93, Issue 11
[page]
2006
Psychological Abstracts
Preserved Fulltext
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J. & de Wilde, Erik Jan. ...
93: 30859-30866
based studies have been reported widely in the literature, little published information exists on the practical aspects of recruiting schools and students into a study. ...
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