The Big Five

Addressing Recurrent Multimodal Learning Data Challenges

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

1 Downloads (Pure)

Abstract

The analysis of multimodal data in learning is a growing field of research, which has led to the development of different analytics solutions. However, there is no standardised approach to handle multimodal data. In this paper, we describe and outline a solution for five recurrent challenges in the analysis of multimodal data: the data collection, storing, annotation, processing and exploitation. For each of these challenges, we envision possible solutions. The prototypes for some of the proposed solutions will be discussed during the Multimodal Challenge of the fourth Learning Analytics & Knowledge Hackathon, a two-day hands-on workshop in which the authors will open up the prototypes for trials, validation and feedback.
Original languageEnglish
Title of host publicationCompanion Proceedings of the 8th International Conference on Learning Analytics and Knowledge
Subtitle of host publicationTowards User-Centred Learning Analytics
Place of PublicationSyndey, Australia
PublisherSoLAR
Pages420-424
Number of pages5
Publication statusPublished - Mar 2018
EventThe 8th International Learning Analytics & Knowledge Conference - SMC Conference & Function Centre, Sydney, Australia
Duration: 5 Mar 20189 Mar 2018
https://latte-analytics.sydney.edu.au/

Conference

ConferenceThe 8th International Learning Analytics & Knowledge Conference
Abbreviated titleLAK18
CountryAustralia
CitySydney
Period5/03/189/03/18
Internet address

Fingerprint

Feedback
Processing

Keywords

  • multimodal learning analytics
  • wearables
  • CrossMMLA
  • sensor-based learning

Cite this

Di Mitri, D., Schneider, J., Specht, M., & Drachsler, H. (2018). The Big Five: Addressing Recurrent Multimodal Learning Data Challenges. In Companion Proceedings of the 8th International Conference on Learning Analytics and Knowledge: Towards User-Centred Learning Analytics (pp. 420-424). Syndey, Australia: SoLAR.
Di Mitri, Daniele ; Schneider, Jan ; Specht, Marcus ; Drachsler, Hendrik. / The Big Five : Addressing Recurrent Multimodal Learning Data Challenges. Companion Proceedings of the 8th International Conference on Learning Analytics and Knowledge: Towards User-Centred Learning Analytics. Syndey, Australia : SoLAR, 2018. pp. 420-424
@inproceedings{5e08caa2242a41dcb648d7e3cb9a2d56,
title = "The Big Five: Addressing Recurrent Multimodal Learning Data Challenges",
abstract = "The analysis of multimodal data in learning is a growing field of research, which has led to the development of different analytics solutions. However, there is no standardised approach to handle multimodal data. In this paper, we describe and outline a solution for five recurrent challenges in the analysis of multimodal data: the data collection, storing, annotation, processing and exploitation. For each of these challenges, we envision possible solutions. The prototypes for some of the proposed solutions will be discussed during the Multimodal Challenge of the fourth Learning Analytics & Knowledge Hackathon, a two-day hands-on workshop in which the authors will open up the prototypes for trials, validation and feedback.",
keywords = "multimodal learning analytics, wearables, CrossMMLA, sensor-based learning",
author = "{Di Mitri}, Daniele and Jan Schneider and Marcus Specht and Hendrik Drachsler",
year = "2018",
month = "3",
language = "English",
pages = "420--424",
booktitle = "Companion Proceedings of the 8th International Conference on Learning Analytics and Knowledge",
publisher = "SoLAR",

}

Di Mitri, D, Schneider, J, Specht, M & Drachsler, H 2018, The Big Five: Addressing Recurrent Multimodal Learning Data Challenges. in Companion Proceedings of the 8th International Conference on Learning Analytics and Knowledge: Towards User-Centred Learning Analytics. SoLAR, Syndey, Australia, pp. 420-424, The 8th International Learning Analytics & Knowledge Conference, Sydney, Australia, 5/03/18.

The Big Five : Addressing Recurrent Multimodal Learning Data Challenges. / Di Mitri, Daniele; Schneider, Jan; Specht, Marcus; Drachsler, Hendrik.

Companion Proceedings of the 8th International Conference on Learning Analytics and Knowledge: Towards User-Centred Learning Analytics. Syndey, Australia : SoLAR, 2018. p. 420-424.

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

TY - GEN

T1 - The Big Five

T2 - Addressing Recurrent Multimodal Learning Data Challenges

AU - Di Mitri, Daniele

AU - Schneider, Jan

AU - Specht, Marcus

AU - Drachsler, Hendrik

PY - 2018/3

Y1 - 2018/3

N2 - The analysis of multimodal data in learning is a growing field of research, which has led to the development of different analytics solutions. However, there is no standardised approach to handle multimodal data. In this paper, we describe and outline a solution for five recurrent challenges in the analysis of multimodal data: the data collection, storing, annotation, processing and exploitation. For each of these challenges, we envision possible solutions. The prototypes for some of the proposed solutions will be discussed during the Multimodal Challenge of the fourth Learning Analytics & Knowledge Hackathon, a two-day hands-on workshop in which the authors will open up the prototypes for trials, validation and feedback.

AB - The analysis of multimodal data in learning is a growing field of research, which has led to the development of different analytics solutions. However, there is no standardised approach to handle multimodal data. In this paper, we describe and outline a solution for five recurrent challenges in the analysis of multimodal data: the data collection, storing, annotation, processing and exploitation. For each of these challenges, we envision possible solutions. The prototypes for some of the proposed solutions will be discussed during the Multimodal Challenge of the fourth Learning Analytics & Knowledge Hackathon, a two-day hands-on workshop in which the authors will open up the prototypes for trials, validation and feedback.

KW - multimodal learning analytics

KW - wearables

KW - CrossMMLA

KW - sensor-based learning

M3 - Conference article in proceeding

SP - 420

EP - 424

BT - Companion Proceedings of the 8th International Conference on Learning Analytics and Knowledge

PB - SoLAR

CY - Syndey, Australia

ER -

Di Mitri D, Schneider J, Specht M, Drachsler H. The Big Five: Addressing Recurrent Multimodal Learning Data Challenges. In Companion Proceedings of the 8th International Conference on Learning Analytics and Knowledge: Towards User-Centred Learning Analytics. Syndey, Australia: SoLAR. 2018. p. 420-424