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Learning analytics for collaborative writing: A prototype and case study

  • Brian J. McNely
  • , Paul Gestwicki
  • , J. Holden Hill
  • , Philip Parli-Horne
  • , Erika Johnson

Producción científica: Conference contributionrevisión exhaustiva

23 Citas (Scopus)

Resumen

This paper explores the ways in which participants in writing intensive environments might use learning analytics to make productive interventions during, rather than after, the collaborative construction of written artifacts. Specifically, our work considered how university students learning in a knowledge work model - one that is collaborative, project-based, and that relies on consistent peer-to-peer interaction and feedback - might leverage learning analytics as formative assessment to foster metacognition and improve final deliverables. We describe Uatu, a system designed to visualize the real time contribution and edit history of collaboratively written documents. After briefly describing the technical details of this system, we offer initial findings from a fifteen week qualitative case study of 8 computer science students who used Uatu in conjunction with Google Docs while collaborating on a variety of writing and programming tasks. These findings indicate both the challenges and promise of delivering useful metrics for collaborative writing scenarios in academe and industry.

Idioma originalEnglish
Título de la publicación alojadaLAK 2012 - Proceedings of the 2nd International Conference on Learning Analytics and Knowledge
Páginas222-225
Número de páginas4
DOI
EstadoPublished - 2012
Evento2nd International Conference on Learning Analytics and Knowledge, LAK 2012 - Vancouver, BC, Canada
Duración: abr 29 2012may 2 2012

Serie de la publicación

NombreACM International Conference Proceeding Series

Conference

Conference2nd International Conference on Learning Analytics and Knowledge, LAK 2012
País/TerritorioCanada
CiudadVancouver, BC
Período4/29/125/2/12

ASJC Scopus subject areas

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

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