Situating multimodal learning analytics

Marcelo Worsley, Dor Abrahamson, Paulo Blikstein, Shuchi Grover, Bertrand Schneider, Mike Tissenbaum

Research output: Chapter in Book/Report/Conference proceedingConference contribution

21 Scopus citations

Abstract

The digital age has introduced a host of new challenges and opportunities for the learning sciences community. These challenges and opportunities are particularly abundant in multimodal learning analytics (MMLA), a research methodology that aims to extend work from Educational Data Mining (EDM) and Learning Analytics (LA) to multimodal learning environments by treating multimodal data. Recognizing the short-term opportunities and longterm challenges will help develop proof cases and identify grand challenges that will help propel the field forward. To support the field's growth, we use this paper to describe several ways that MMLA can potentially advance learning sciences research and touch upon key challenges that researchers who utilize MMLA have encountered over the past few years.

Original languageEnglish (US)
Title of host publication12th International Conference of the Learning Sciences, ICLS 2016
Subtitle of host publicationTransforming Learning, Empowering Learners, Proceedings
PublisherInternational Society of the Learning Sciences (ISLS)
Pages1346-1349
Number of pages4
Volume2
ISBN (Electronic)9780990355083
StatePublished - Jan 1 2016
Event12th International Conference of the Learning Sciences: Transforming Learning, Empowering Learners, ICLS 2016 - Singapore, Singapore
Duration: Jun 20 2016Jun 24 2016

Other

Other12th International Conference of the Learning Sciences: Transforming Learning, Empowering Learners, ICLS 2016
CountrySingapore
CitySingapore
Period6/20/166/24/16

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Education

Fingerprint Dive into the research topics of 'Situating multimodal learning analytics'. Together they form a unique fingerprint.

Cite this