Empowering instructors through customizable collection and analyses of actionable information

Danny Y.T. Liu, Charlotte E. Taylor, Adam J. Bridgeman, Kathryn Bartimote-Aufflick, Abelardo Pardo

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

The use of analytics to support learning has been increasing over the last few years. However, there is still a significant disconnect between what algorithms and technology offer and what everyday instructors need to integrate actionable items from these tools into their learning environments. In this paper we present the evolution of the Student Relationship Engagement System, a platform to support instructors to select, collect, and analyze student data. The approach provides instructors the ultimate control over the decision process to deploy various actions. The approach has two objectives: To increase instructor data literacies and competencies, and to provide a low adoption barrier to promote a data-driven pedagogical improvement culture in educational institutions. The system is currently being used in 58 courses and 14 disciplines, and reaches over 20,000 students.

Original languageEnglish
Pages (from-to)3-9
Number of pages7
JournalCEUR Workshop Proceedings
Volume1590
Publication statusPublished - 2016
Externally publishedYes

Keywords

  • Curriculum design and delivery
  • Instructors
  • Learning analytics adoption
  • Machine learning
  • Scaling up
  • Teaching approaches

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