Visualising alignment to support students’ judgment of confidence in open learner models

Lamiya Al-shanfari, Carrie Demmans Epp, Chris Baber, Mahvish Nazir

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
199 Downloads (Pure)


Knowledge monitoring is a component of metacognition which can help students regulate their own learning. In adaptive learning software, the system’s model of the student can be presented as an open learner model (OLM) which is intended to enable monitoring processes. We explore how presenting alignment, between students’ self-assessed confidence and the system’s model of the student, supports knowledge monitoring. When students can see their confidence and their performance (either combined within one skill meter or expanded as two separate skill meters), their knowledge monitoring and performance improves, particularly for low-achieving students. These results indicate the importance of communicating the alignment between the system’s evaluation of student performance and student confidence in the correctness of their answers as a means to support metacognitive skills.
Original languageEnglish
Pages (from-to)159-194
Number of pages36
JournalUser Modelling and User Adapted Interaction
Issue number1
Early online date22 Jan 2020
Publication statusPublished - 1 Mar 2020


  • Confidence judgment
  • Intelligent tutoring systems
  • Knowledge monitoring
  • Learning dashboards
  • Open learner model
  • Self-regulated learning

ASJC Scopus subject areas

  • Education
  • Human-Computer Interaction
  • Computer Science Applications


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