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System design for using multimodal trace data in modeling self-regulated learning

Elizabeth Brooke Cloude, Roger Azevedo, Philip H. Winne, Gautam Biswas, Eunice E. Jang
2022 Frontiers in Education  
In this paper, we discuss recommendations for building a multimodal learning analytics architecture for advancing research on how researchers or instructors can standardize, process, analyze, recognize  ...  Our overall goals are to (a) advance the science of learning by creating links between multimodal trace data and theoretical models of SRL, and (b) aid researchers or instructors in developing effective  ...  Acknowledgments The authors would like to thank team members of the SMART Lab at the University  ... 
doi:10.3389/feduc.2022.928632 fatcat:rpgfc4zpxzdtdfbdvephijbp3q

MULTIFOCUS: MULTImodal Learning Analytics FOr Co-located Collaboration Understanding and Support

Sambit Praharaj, Maren Scheffel, Hendrik Drachsler, Marcus Specht
2018 European Conference on Technology Enhanced Learning  
Using the help of Multimodal Learning Analytics with the help of sensors to understand how co-located collaboration takes place, identifying the indicators of collaboration (such as pointing at peer, looking  ...  at peer, making constructive interruptions, etc.) and designing a collaboration framework model which defines the aspects of successful collaboration.  ...  .: Leveraging multimodal learning analytics to differentiate student learning strategies. In: Proceedings of the Fifth International Conference on Learning Analytics And Knowledge. pp. .  ... 
dblp:conf/ectel/PraharajSDS18a fatcat:ppt3cszz2vgwhj4cr4rtofzgn4

Scalable Higher Education Learning Analytics Architecture through Data Integration

Jeanette Samuelsen
2018 European Conference on Technology Enhanced Learning  
As part of this project we have conducted a systematic review, to understand state-of-the art research and practice regarding multiple data source usage and combination in learning analytics.  ...  Effectively implementing LA at an institutional level is far from trivial, as such a solution needs to be scalable. In this project I aim to build a scalable learning analytics architecture.  ...   What types of data are being used for learning analytics in higher education? System Architecture Informed by the results of the systematic literature review, we are developing a LA architecture.  ... 
dblp:conf/ectel/Samuelsen18 fatcat:6nq66oauivguhah6y7xsqu6sqm

Deep Auto-Encoders with Sequential Learning for Multimodal Dimensional Emotion Recognition [article]

Dung Nguyen, Duc Thanh Nguyen, Rui Zeng, Thanh Thi Nguyen, Son N. Tran, Thin Nguyen, Sridha Sridharan, Clinton Fookes
2020 arXiv   pre-print
To validate the robustness of our proposed architecture, we carry out extensive experiments on the multimodal emotion in the wild dataset: RECOLA.  ...  To address these challenges, in this paper, we propose a novel deep neural network architecture consisting of a two-stream auto-encoder and a long short term memory for effectively integrating visual and  ...  He graduated with a PhD in Computer Science from Curtin University, Australia in 2012 in the area of machine learning and social media analytics.  ... 
arXiv:2004.13236v1 fatcat:qgoybjaf3jgphcoed7qablxqlm

Read Between the Lines

Daniele Di Mitri, Jan Schneider, Roland Klemke, Marcus Specht, Hendrik Drachsler
2019 Proceedings of the 9th International Conference on Learning Analytics & Knowledge - LAK19  
We call this workflow the Multimodal Learning Analytics Pipeline, a toolkit for orchestration, the use and application of various MMLA tools.  ...  While most of the existing Multimodal Learning Analytics (MMLA) solutions are tailor-made for specific learning tasks and sensors, the VIT addresses the data annotation for different types of learning  ...  In support of these new forms of interaction, within the Learning Analytics community, a new research focus has emerged, coined as multimodal learning analytics (MMLA) [6] .  ... 
doi:10.1145/3303772.3303776 dblp:conf/lak/Mitri0KSD19 fatcat:b635gpbmejfslnfzj2oovmbory

Multimodal Data Fusion in Learning Analytics: A Systematic Review

Su Mu, Meng Cui, Xiaodi Huang
2020 Sensors  
Multimodal learning analytics (MMLA), which has become increasingly popular, can help provide an accurate understanding of learning processes.  ...  For this purpose, we first present a conceptual model for reviewing these articles from three dimensions: data types, learning indicators, and data fusion.  ...  As a new area of learning analytics [7] , multimodal learning analytics (MMLA) [9] captures, integrates, and analyzes learning traces from different sources in a way that enables a holistic understanding  ... 
doi:10.3390/s20236856 pmid:33266131 pmcid:PMC7729570 fatcat:lcnlxpiw5zcwjhrzc26c2zq6b4

Multimodal Mastery Learning

Matthew Montebello, Department of Artificial Intelligence, University of Malta, Malta, Bill Cope, Mary Kalantzis, Samaa Haniya, Tabassum Amina, Anastasia Olga Tzirides, Duane Searsmith, Naichen Zhao, Min Chen
2019 International Journal of Learning and Teaching  
Educators frequently encourage and value the use of a variety of media in student work, as learners design their knowledge representations using rich, multimodal sources and embedding multiple types of  ...  Finally, we present results from qualitative data collected and analysed regarding the use of rich, multimodal sources, as we come to a close with a number of conclusions and recommendations.  Index Terms-multimedia  ...  The analytics tool itself represents a number of significant developments in the field of assessment and learning analytics, as it captures individual and whole cohort progress in learning with a level  ... 
doi:10.18178/ijlt.5.1.19-23 fatcat:tbadg24rqzajplipk26zdi45ke

A data value chain to support the processing of multimodal evidence in authentic learning scenarios

Shashi Kant Shankar, Adolfo Ruiz-Calleja, Sergio Serrano-Iglesias, Alejandro Ortega-Arranz, Paraskevi Topali, Alejandra Martínez-Monés
2019 Learning Analytics Summer Institute Spain  
Multimodal Learning Analytics (MMLA) uncovers the possibility to get a more holistic picture of a learning situation than traditional Learning Analytics, by triangulating learning evidence collected from  ...  As a first step in this direction, this paper analyzes four MMLA scenarios, abstracts their data processing activities and extracts a Data Value Chain to model the processing of multimodal evidence of  ...  Moreover, this research is partially funded by the European Regional Development Fund and the National Research Agency of the Spanish Ministry of Science, Innovations and Universities under project grants  ... 
dblp:conf/lasi-spain/ShankarRSOTM19 fatcat:iyj2llucjfd3jog2nplmrel56e

A Scalable Architecture for the Dynamic Deployment of Multimodal Learning Analytics Applications in Smart Classrooms

Alberto Huertas Celdrán, José A. Ruipérez-Valiente, Félix J. García Clemente, María Jesús Rodríguez-Triana, Shashi Kant Shankar, Gregorio Martínez Pérez
2020 Sensors  
The area of Multimodal Learning Analytics (MMLA) explores the affordances of processing these heterogeneous data to understand and improve both learning and the context where it occurs.  ...  However, a review of different MMLA studies highlighted that ad-hoc and rigid architectures cannot be scaled up to real contexts.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s20102923 pmid:32455699 pmcid:PMC7285125 fatcat:ablwghgvmvfrpd5ml54zapeybi

IEEE Access Special Section Editorial: Intelligent Biometric Systems for Secure Societies

Marina L. Gavrilova, Gee-Sern Hsu, Khalid Saeed, Svetlana Yanushkevich
2021 IEEE Access  
Her list of publications includes three coauthored books, over 30 books of conference proceedings, and more than 200 peer-reviewed articles on machine learning, biometric security, and multimodal cognitive  ...  GAVRILOVA (Senior Member, IEEE) is currently a Full Professor with the CSPS Department and an international expert in the area of biometric security, machine learning, pattern recognition, data analytics  ...  It also explores emerging deep learning architectures for various types of unimodal and multimodal biometric systems as one of most interesting approaches to human authentication.  ... 
doi:10.1109/access.2021.3078343 fatcat:uoxaq7ldnnfdddk5c32ujjoccu

Real-Time Multimodal Feedback with the CPR Tutor [chapter]

Daniele Di Mitri, Jan Schneider, Kevin Trebing, Sasa Sopka, Marcus Specht, Hendrik Drachsler
2020 Lecture Notes in Computer Science  
The CPR Tutor pushes forward the current state of the art of real-time multimodal tutors by providing: 1) an architecture design, 2) a methodological approach to design multimodal feedback and 3) a field  ...  From a multimodal data stream consisting of kinematic and electromyographic data, the CPR Tutor system automatically detects the chest compressions, which are then classified and assessed according to  ...  The exploration of these novel data sources inspired the Multimodal Learning Analytics (MMLA) researc [15] , whose common hypothesis is that combining data from multiple modalities allows obtaining a  ... 
doi:10.1007/978-3-030-52237-7_12 fatcat:bckklimlpzgwbn6hgiqhtytweq

Learning Multimodality through Genre-Based Multimodal Texts Analysis: Listening to Students' Voices

Fuad Abdullah, Soni Tantan Tandiana, Yuyus Saputra
2020 Vision Journal for Language and Foreign Language Learning  
However, only a few studies reported on the way students perceived the use of Genre-Based Multimodal Texts Analysis (GBMTA) for teaching multimodality.  ...  better learning strategies in the future, engagement on multimodal learning issues, and multimodal text analysis practices.  ...  In Modelling of Genre-Based Multimodal Text Analysis, participant #20 was given a model of analysis to familiarise herself with semiotic resources in a multimodal text (posters) and a particular analytical  ... 
doi:10.21580/vjv9i25406 fatcat:nypoyb24mnh3jidpykbcub3wle

Exploring the Affordances of Multimodal Data to Improve Cybersecurity Training with Cyber Range Environments [chapter]

Mariano Albaladejo-González, Sofia Strukova, José A. Ruipérez-Valiente, Félix l Gómez Mármol
2021 Colección Jornadas y Congresos  
by the Govern of Spain and cofunded by European Social Funds.  ...  ACKNOWLEDGMENTS This work has been partially funded by project COBRA (10032/20/0035/00), awarded by the Spanish Ministry of Defense, as well as the fellowships FJCI-2017-34926 and RYC-2015-18210, awarded  ...  Figure 2 presents the overview of the architecture of the cyber range environment with the multimodal learning analytics, and how the following components are connected within the system: B.  ... 
doi:10.18239/jornadas_2021.34.52 fatcat:6aggrhhuz5f5hbt3g4huuvzqcm

Opportunities and challenges in developing deep learning models using electronic health records data: a systematic review

Cao Xiao, Edward Choi, Jimeng Sun
2018 JAMIA Journal of the American Medical Informatics Association  
Objective: To conduct a systematic review of deep learning models for electronic health record (EHR) data, and illustrate various deep learning architectures for analyzing different data sources and their  ...  Discussion: Despite the early success in using deep learning for health analytics applications, there still exist a number of issues to be addressed.  ...  Deep learning architectures for analytics tasks Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction  ... 
doi:10.1093/jamia/ocy068 pmid:29893864 fatcat:ne7weiw7xvc2lp7hfgkzltdnri

Lesson Observation Data in Learning Analytics Datasets: Observata [chapter]

Maka Eradze, Mart Laanpere
2017 Lecture Notes in Computer Science  
The paper identifies the need for theoretical and pedagogical semantics in multimodal learning analytics, and examines the xAPI potential for the multimodal data gathering and aggregation.  ...  The technological environment that supports the learning process tends to be the main data source for Learning Analytics.  ...  Multimodal learning analytics (MMLA) may be a promising approach for this kind of contexts, since researchers in this area are trying to identify and collect also realworld learning data [1] .  ... 
doi:10.1007/978-3-319-66610-5_50 fatcat:kjtjskimevaovdiys7ctg7vdyq
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