Analyzing frequent sequential patterns of learning behaviors in concept mapping

Shang Wang, Erin Walker, Ruth Wylie

Research output: Contribution to journalConference articlepeer-review


Computer-based concept mapping learning environments can produce large amounts of data on student interactions. The ability to automatically extract common interaction patterns and distinguish between effective and ineffective interactions creates opportunities for researchers to calibrate feedback and assistance to better support student learning. In this paper, we present an exploratory workflow that assesses and compares student learning behaviors with concept maps. This workflow employs a sequential pattern mining technique to classify interaction patterns among students and determine specific behavior patterns that lead to better learning outcomes.

Original languageEnglish (US)
JournalCEUR Workshop Proceedings
StatePublished - 2016
Event2016 EDM Workshops and Tutorials, WT-EDM 2016 - Raleigh, United States
Duration: Jun 29 2016 → …


  • Concept mapping
  • Data mining
  • Sequential pattern mining
  • Student behavior

ASJC Scopus subject areas

  • Computer Science(all)


Dive into the research topics of 'Analyzing frequent sequential patterns of learning behaviors in concept mapping'. Together they form a unique fingerprint.

Cite this