Storytelling with learner data: guiding student reflection on multimodal team data

Gloria Milena Fernandez-Nieto, Vanessa Echeverria, Simon Buckingham Shum, Katerina Mangaroska, Kirsty Kitto, Evelyn Palominos, Carmen Axisa, Roberto Martinez-Maldonado

Research output: Contribution to journalArticleResearchpeer-review

15 Citations (Scopus)

Abstract

There is growing interest in creating learning analytics feedback interfaces that support students directly. While dashboards and other visualizations are proliferating, the evidence is that many fail to provide meaningful insights that help students reflect productively. The contribution of this article is qualitative and quantitative evidence from two studies evaluating a multimodal teamwork analytics tool in authentic clinical teamwork simulations. Collocated activity data are rendered to help nursing students reflect on errors and stress-related incidents during simulations. The user interface explicitly guides student reflection using data storytelling principles, tuned to the intended learning outcomes. The results demonstrate the potential of interfaces that 'tell one data story at a time,' by helping students to identify misconceptions and errors; think about strategies they might use to address errors, and reflect on their arousal levels. The results also illuminate broader issues around automated formative assessment, and the intelligibility and accountability of learning analytics.

Original languageEnglish
Pages (from-to)695-708
Number of pages14
JournalIEEE Transactions on Learning Technologies
Volume14
Issue number5
DOIs
Publication statusPublished - 1 Oct 2021

Keywords

  • Collocated spaces
  • Feedback
  • Guidance
  • Multimodal learning analytics (MMLA)
  • Reflection
  • Visualization

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