Multimodal learning analytics data challenges

Xavier Ochoa; Nadir Weibel; Marcelo Worsley; Sharon Oviatt

doi:10.1145/2883851.2883913

Multimodal learning analytics data challenges

Xavier Ochoa, Nadir Weibel, Marcelo Worsley, Sharon Oviatt

Administration, Leadership & Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This is a proposal for organizing a Multimodal Learning An- Alytics (MLA) data challenge as part of the workshop offering of the Learning Analytics and Knowledge (LAK) conference. It explains the motivation of the event, its objectives, target groups, expected format, organization, dissemination strategy and schedule.

Original language	English (US)
Title of host publication	LAK 2016 Conference Proceedings, 6th International Learning Analytics and Knowledge Conference - Enhancing Impact
Subtitle of host publication	Convergence of Communities for Grounding, Implementation, and Validation
Publisher	Association for Computing Machinery
Pages	498-499
Number of pages	2
ISBN (Electronic)	9781450341905
DOIs	https://doi.org/10.1145/2883851.2883913
State	Published - Apr 25 2016
Event	6th International Conference on Learning Analytics and Knowledge, LAK 2016 - Edinburgh, United Kingdom Duration: Apr 25 2016 → Apr 29 2016

Publication series

Name	ACM International Conference Proceeding Series
Volume	25-29-April-2016

Other

Other	6th International Conference on Learning Analytics and Knowledge, LAK 2016
Country	United Kingdom
City	Edinburgh
Period	4/25/16 → 4/29/16

Keywords

Data challenge
Multimodal
Multimodal datasets

ASJC Scopus subject areas

Software
Human-Computer Interaction
Computer Vision and Pattern Recognition
Computer Networks and Communications

Access to Document

10.1145/2883851.2883913

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Cite this

Ochoa, X., Weibel, N., Worsley, M., & Oviatt, S. (2016). Multimodal learning analytics data challenges. In LAK 2016 Conference Proceedings, 6th International Learning Analytics and Knowledge Conference - Enhancing Impact: Convergence of Communities for Grounding, Implementation, and Validation (pp. 498-499). (ACM International Conference Proceeding Series; Vol. 25-29-April-2016). Association for Computing Machinery. https://doi.org/10.1145/2883851.2883913

Multimodal learning analytics data challenges. / Ochoa, Xavier; Weibel, Nadir; Worsley, Marcelo; Oviatt, Sharon.

LAK 2016 Conference Proceedings, 6th International Learning Analytics and Knowledge Conference - Enhancing Impact: Convergence of Communities for Grounding, Implementation, and Validation. Association for Computing Machinery, 2016. p. 498-499 (ACM International Conference Proceeding Series; Vol. 25-29-April-2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ochoa, X, Weibel, N, Worsley, M & Oviatt, S 2016, Multimodal learning analytics data challenges. in LAK 2016 Conference Proceedings, 6th International Learning Analytics and Knowledge Conference - Enhancing Impact: Convergence of Communities for Grounding, Implementation, and Validation. ACM International Conference Proceeding Series, vol. 25-29-April-2016, Association for Computing Machinery, pp. 498-499, 6th International Conference on Learning Analytics and Knowledge, LAK 2016, Edinburgh, United Kingdom, 4/25/16. https://doi.org/10.1145/2883851.2883913

Ochoa X, Weibel N, Worsley M, Oviatt S. Multimodal learning analytics data challenges. In LAK 2016 Conference Proceedings, 6th International Learning Analytics and Knowledge Conference - Enhancing Impact: Convergence of Communities for Grounding, Implementation, and Validation. Association for Computing Machinery. 2016. p. 498-499. (ACM International Conference Proceeding Series). https://doi.org/10.1145/2883851.2883913

Ochoa, Xavier ; Weibel, Nadir ; Worsley, Marcelo ; Oviatt, Sharon. / Multimodal learning analytics data challenges. LAK 2016 Conference Proceedings, 6th International Learning Analytics and Knowledge Conference - Enhancing Impact: Convergence of Communities for Grounding, Implementation, and Validation. Association for Computing Machinery, 2016. pp. 498-499 (ACM International Conference Proceeding Series).

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