Scaling and Adopting a Multimodal Learning Analytics Application in an Institution-Wide Setting

Federico Domínguez, Xavier Ochoa, Dick Zambrano, Katherine Camacho, Jaime Castells

Research output: Contribution to journalArticlepeer-review


Multimodal learning analytics, which is collection, analysis, and report of diverse learning traces to better understand and improve the learning process, has been producing a series of interesting prototypes to analyze learning activities that were previously hard to objectively evaluate. However, none of these prototypes have been taken out of the laboratory and integrated into real learning settings. This article is the first to propose, execute, and evaluate a process to scale and deploy one of these applications, an automated oral presentation feedback system, into an institution-wide setting. Technological, logistical, and pedagogical challenges and adaptations are discussed. An evaluation of the use and effectiveness of the deployment shows both successful adoption and moderate learning gains, especially for low-performing students. In addition, the recording and summarizing of the perception of both instructors and students point to a generally positive experience in spite of the common problems of a first-generation deployment of a complex learning technology.

Original languageEnglish (US)
Article number9502002
Pages (from-to)400-414
Number of pages15
JournalIEEE Transactions on Learning Technologies
Issue number3
StatePublished - Jun 1 2021


  • Automated feedback
  • multimodal
  • oral presentation skills

ASJC Scopus subject areas

  • Education
  • General Engineering
  • Computer Science Applications


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