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Dataset to Support the Adoption of Social Media and Emerging Technologies for Students' Continuous Engagement

Oluwatobi Noah Akande, Taofeeq Alabi Badmus, Akinyinka Tosin Akindele, Oladiran Tayo Arulogun
2020 Data in Brief  
The dataset will enhance understanding of how face to face students use social media platforms and how these platforms could be used to engage the students outside their classroom activities.  ...  Also, the dataset exposes how familiar face to face University students are to these emerging teaching and learning technologies.  ...  The dataset will enhance understanding of how face to face students use social me-dia platforms and how these platforms could be used to engage the students outside their classroom activities.  ... 
doi:10.1016/j.dib.2020.105926 pmid:32665968 pmcid:PMC7316039 fatcat:3oripnegsbe3dhbfutttxubxha

Improving state-of-the-art in Detecting Student Engagement with Resnet and TCN Hybrid Network [article]

Ali Abedi, Shehroz S. Khan
2021 arXiv   pre-print
We compared our method with several competing students' engagement detection methods on this dataset.  ...  The spatial and temporal arms of the hybrid network are jointly trained on raw video frames of a large publicly available students' engagement detection dataset, DAiSEE.  ...  The DAiSEE dataset contains 9,068 10-second videos captured from 112 students in online classroom setting, and annotated by the engagement level of students.  ... 
arXiv:2104.10122v2 fatcat:g2sqeicqkbhwjii42vdgaii7xe

Relationship between students' math engagement and math teachers' motivational support

Neşe Özkal
2018 Turkish Journal of Education  
The relationship between the datasets of middle school students' engagement in mathematics classes and their perceptions regarding mathematics teachers' motivational support was investigated via canonical  ...  Findings obtained showed that mathematics teachers' autonomy support provided to middle school 6th,7th, 8th grade students positively affected their behavioral engagement and emotional engagement.  ...  included in engagement dataset.  ... 
doi:10.19128/turje.339944 fatcat:5lxeb644czferoxx7du6gazo5i

Student behavior analysis to measure engagement levels in online learning environments

Khawlah Altuwairqi, Salma Kammoun Jarraya, Arwa Allinjawi, Mohamed Hammami
2021 Signal, Image and Video Processing  
In fact, we build new and realistic student engagement datasets to validate our contributions.  ...  Measuring student engagement is a crucial step towards smart online learning systems.  ...  Conclusion In this paper, we proposed an automatic multimodal approach to measure student engagement.  ... 
doi:10.1007/s11760-021-01869-7 pmid:34007342 pmcid:PMC8119613 fatcat:3mwqszh3tjdfhp2aycdgiymfby

Student rules: Exploring patterns of students' computer-efficacy and engagement with digital technologies in learning

Sarah K. Howard, Jun Ma, Jie Yang
2016 Computers & Education  
To do this, association rules mining and fuzzy representations are used to analyze a large student questionnaire dataset (N = 8817).  ...  Results reveal substantially different patterns among school engagement and computer-efficacy factors between students with positive and negative engagement with digital technologies.  ...  Dataset 1 included only students reporting positive ICT Engagement. Dataset 2 included students reporting negative ICT Engagement.  ... 
doi:10.1016/j.compedu.2016.05.008 fatcat:q424252k3jg5hfcbsabn4qcliq

Relationship between Student Engagement and Performance in e-Learning Environment Using Association Rules [article]

Abdallah Moubayed, MohammadNoor Injadat, Abdallah Shami, Hanan Lutfiyya
2020 arXiv   pre-print
One of the challenges facing e-learning platforms is how to keep students motivated and engaged.  ...  To that end, this paper tries to investigate the relationship between student engagement and their academic performance.  ...  The calculated engagement metrics dataset and the grades dataset were combined to form a new dataset consisting of eighteen features, namely the Student ID, nine engagement metrics, engagement level, and  ... 
arXiv:2101.02006v1 fatcat:zujujcbax5cgzcw324mjgprnai

Online module login data as a proxy measure of student engagement: the case of myUnisa, MoyaMA, Flipgrid, and Gephi at an ODeL institution in South Africa

Chaka Chaka, Tlatso Nkhobo
2019 International Journal of Educational Technology in Higher Education  
module, ENG2601, as extracted from myUnisa, Moya MA , and Flipgrid served as a proxy measure of student engagement.  ...  The current study employed online module login data harvested from three tools, myUnisa, Moya MA and Flipgrid to determine how such data served as a proxy measure of student engagement.  ...  Acknowledgements The authors would like to thank a graduate student who worked with one of the authors to compute and visualise datasets on Gephi.  ... 
doi:10.1186/s41239-019-0167-9 fatcat:ndsfalmsznhipjo3ylgtenfvii

Personas Design for Conversational Systems in Education

Fatima Ali Amer Jid Almahri, David Bell, Mahir Arzoky
2019 Informatics  
This research aims to explore how to enhance student engagement in higher education institutions (HEIs) while using a novel conversational system (chatbots).  ...  The principal research methodology for this study is design science research (DSR), which is executed in three iterations: personas elicitation, a survey and development of student engagement factor models  ...  Digital Education Advisor in the Digital Education Team in Brunel Educational Excellence Centre at Brunel University London for providing me with documentation that explains the attributes of the VLEs dataset  ... 
doi:10.3390/informatics6040046 fatcat:75aefrljr5a4xm3i4zopiq5u6e

Predicting the decrease of engagement indicators in a MOOC

Miguel L. Bote-Lorenzo, Eduardo Gómez-Sánchez
2017 Proceedings of the Seventh International Learning Analytics & Knowledge Conference on - LAK '17  
Predicting the decrease of students' engagement in typical MOOC tasks such as watching lecture videos or submitting assignments is key to trigger timely interventions in order to try to avoid the disengagement  ...  The approach was employed in an experimental study to predict the decrease of three different engagement indicators in a MOOC.  ...  Number of datasets in which each feature was selected. Video datasets Exercise datasets Assignment datasets 3 Total Table 4 .  ... 
doi:10.1145/3027385.3027387 fatcat:pcmhgbuzqfet5cksauyuiokn7y

Using social media to enhance student engagement and quality

R.A. Lottering
2020 South African Journal of Higher Education  
social media as a method to engage students on performance outside the normal communication time.  ...  The educational benefits, which accrue from the enhancement in student engagement, are well documented in the literature.  ...  of student engagement.  ... 
doi:10.20853/34-5-4271 fatcat:wezfa6fofzdu3ece2zjcegayfq

Automatic Recognition of Student Engagement using Deep Learning and Facial Expression [article]

Omid Mohamad Nezami, Mark Dras, Len Hamey, Deborah Richards, Stephen Wan, Cecile Paris
2019 arXiv   pre-print
We train the model on our new engagement recognition dataset with 4627 engaged and disengaged samples.  ...  training on specialised engagement data.  ...  To do this, we collected a new dataset annotated by Psychology students, who can potentially better recognize the psychological phenomena of engagement, because of the complexity of analyzing student engagement  ... 
arXiv:1808.02324v5 fatcat:tphgzg6torblrbdqbrrpvbeari

Engagement vs performance

Everaldo Aguiar, Nitesh V. Chawla, Jay Brockman, G. Alex Ambrose, Victoria Goodrich
2014 Proceedins of the Fourth International Conference on Learning Analytics And Knowledge - LAK '14  
To address this issue, we derive measurements of engagement from students' electronic portfolios and show how these features can be effectively used to augment the quality of predictions.  ...  This is specially true when the overall set of students has a relatively similar academic performance.  ...  Acknowledgments We thank Jeffrey Yan and Peter Lefferts at Digication for the help they provided with the collection of the electronic portfolio datasets, and Catherine Pieronek for compiling the academic  ... 
doi:10.1145/2567574.2567583 dblp:conf/lak/AguiarCBAG14 fatcat:2xk7b27nvjhhtndi6uwqetmqa4

Relation between Student Engagement and Demographic Characteristics in Distance Learning Using Association Rules

Moohanad Jawthari, Veronika Stoffa
2022 Electronics  
This type of learning, however, faces a challenge in keeping students engaged and interested.  ...  Apriori algorithm is utilized to obtain a set of rules that connect demographic features to student engagement.  ...  OU dataset structure. Figure 1 . 1 Figure 1. OU dataset structure.  ... 
doi:10.3390/electronics11050724 fatcat:2ot3g5pkbrdthebuf6r7n5vf6m

Student Engagement Predictions in an e-Learning System and Their Impact on Student Course Assessment Scores

Mushtaq Hussain, Wenhao Zhu, Wu Zhang, Syed Muhammad Raza Abidi
2018 Computational Intelligence and Neuroscience  
The output variable was the student level of engagement in the various activities. To predict low-engagement students, we applied several ML algorithms to the dataset.  ...  In this study, we used machine learning (ML) algorithms to identify low-engagement students in a social science course at the Open University (OU) to assess the effect of engagement on student performance  ...  In our model, the recall results reflect how many of the low-engagement students were correctly identified as lowengagement out of the total number of low-engagement students in the dataset.  ... 
doi:10.1155/2018/6347186 fatcat:yu766bcz2bcqjnttv5nszuo4wu

Engagement vs Performance: Using Electronic Portfolios to Predict First Semester Engineering Student Persistence

Everaldo Aguiar, G. Alex Ambrose, Nitesh V. Chawla, Victoria Goodrich, Jay Brockman
2014 Journal of Learning Analytics  
To address this issue, we derive measurements of engagement from students' electronic portfolios and show how these features can be used effectively to augment the quality of predictions.  ...  This is especially true when the overall set of students has a relatively similar academic performance.  ...  ACKNOWLEDGEMENTS We thank Jeffrey Yan and Peter Lefferts at Digication for the help they provided with the collection of the ePortfolio datasets, and Catherine Pieronek for compiling the academic performance  ... 
doi:10.18608/jla.2014.13.3 fatcat:typmvghn3vfjrpkja2m5hrrcgq
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