Studying Conceptual Change in Classrooms Using Association Rule Mining to Detect Changes in Students' Explanations of the Effects of Urban Planning and Social Policy

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

  • Arthur Hjorth
  • Uri Wilensky, Northwestern Univ, Northwestern University, Learning Sci & Comp Sci

Context . Conceptual developments in our understanding of knowledge are merging with machine-learning methods for making sense of data. This creates new, and interesting ways in which we can document and analyse knowledge, and conceptual change. Problem . Currently, the study of conceptual change is often limited to small sample sizes because of the laborious nature of existing, purely qualitative approaches. Method . We present Association Rule Mining to better measure and understand changes in students' thinking at the classroom level, based on data collected while implementing a constructionist learning activity in a US college classroom. Association Rule Mining is used on a set of qualitatively coded student responses. We then look at changes in the association rules between students' responses before and after a learning activity to better understand students'conceptual change at the classroom level. Results . We find that students converge on a more complete and accurate set of causal claims in their post-responses. Finding these changes would have been difficult or impossible without Association Rule Mining, or a similar approach. This suggests that Association Rule Mining is a potentially fruitful approach to analysing conceptual change at the classroom level. Constructivist content . Association Rule Mining is agnostic with regard to the ontology of its data. This makes Association Rule Mining a particularly suitable analysis method when taking a constructivist view of learning

Original languageEnglish
JournalConstructivist Foundations
Pages (from-to)272-283
Number of pages12
Publication statusPublished - Jul 2019

    Research areas

  • Qualitative research, computational methods, knowledge analysis, education, conceptual change, complex systems thinking, learning sciences, constructionism, LEARNING ANALYTICS, SIMCITY, GAMES

See relations at Aarhus University Citationformats

ID: 162454512