Multimodal teaching analytics: Automated extraction of orchestration graphs from wearable sensor data-Reference-Cited by-同舟云学术

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Multimodal teaching analytics: Automated extraction of orchestration graphs from wearable sensor data

Published:2018-01-24 Issue:2 Volume:34 Page:193-203
ISSN:0266-4909
Container-title:Journal of Computer Assisted Learning
language:en
Short-container-title:J Comput Assist Learn

Author:

Prieto L.P.¹^ORCID,Sharma K.²,Kidzinski Ł.³,Rodríguez-Triana M.J.¹²^ORCID,Dillenbourg P.²

Affiliation:

1. Tallinn University; Estonia

2. École Polytechnique Fédérale de Lausanne; Switzerland

3. Stanford University; CA USA

Funder

Horizon 2020 Framework Programme

European Union's Horizon 2020 research and innovation programme

Marie Curie Fellowship (7th European Community Framework Programme)

US National Institute of Health

Publisher

Wiley

Subject

Computer Science Applications,Education

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/jcal.12232/fullpdf

Reference46 articles.

1. Multimodal learning analytics and education data mining: Using computational technologies to measure complex learning tasks;Blikstein;Journal of Learning Analytics,2016

2. On-line human activity recognition from audio and home automation sensors: Comparison of sequential and non-sequential models in realistic smart Homes;Chahuara;Journal of Ambient Intelligence and Smart Environments,2016

3. Where low and high inference data converge: Validation of CLASS assessment of mathematics instruction using mobile eye tracking with expert and novice teachers;Cortina;International Journal of Mathematical Education in Science and Technology,2015

4. Dhall , A. Ramana Murthy , O. V. Goecke , R. Joshi , J. Gedeon , T. 2015 Video and image based emotion recognition challenges in the wild: EmotiW 2015 Proceedings of the 17th ACM International Conference on Multimodal Interaction 423 426

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