Learning analytics dashboards for adaptive support in face-to-face collaborative argumentation

Jeongyun Han, Kwan Hoon Kim, Wonjong Rhee, Young Hoan Cho

Research output: Contribution to journalArticlepeer-review

65 Scopus citations

Abstract

Despite the potential of learning analytics for personalized learning, it is seldom used to support collaborative learning particularly in face-to-face (F2F) learning contexts. This study uses learning analytics to develop a dashboard system that provides adaptive support for F2F collaborative argumentation (FCA). This study developed two dashboards for students and instructors, which enabled students to monitor their FCA process through adaptive feedback and helped the instructor provide adaptive support at the right time. The effectiveness of the dashboards was examined in a university class with 88 students (56 females, 32 males) for 4 weeks. The dashboards significantly improved the FCA process and outcomes, encouraging students to actively participate in FCA and create high-quality arguments. Students had a positive attitude toward the dashboard and perceived it as useful and easy to use. These findings indicate the usefulness of learning analytics dashboards in improving collaborative learning through adaptive feedback and support. Suggestions are provided on how to design dashboards for adaptive support in F2F learning contexts using learning analytics.

Original languageEnglish
Article number104041
JournalComputers and Education
Volume163
DOIs
StatePublished - Apr 2021

Keywords

  • Adaptive instruction
  • Argumentation
  • Collaborative learning
  • Dashboard
  • Learning analytics

Fingerprint

Dive into the research topics of 'Learning analytics dashboards for adaptive support in face-to-face collaborative argumentation'. Together they form a unique fingerprint.

Cite this