Modelling the way: Using action sequence archetypes to differentiate learning pathways from learning outcomes

Kelvin H.R. Ng, Kevin Hartman, Kai Liu, Andy W.H. Khong

Research output: Contribution to conferencePaperpeer-review

5 Citations (Scopus)

Abstract

During the semester break, 36 second-grade students accessed a set of resources and completed a series of online math activities focused on the application of the model method for arithmetic in two contexts 1) addition/subtraction and 2) multiplication/ division. The learning environment first modeled and then supported the use of a scripted series of steps for solving mathematical word problems. As students completed the activities, the learning environment captured their event-related data. We then used a combination of Affinity Propagation, an automated form of clustering, and sequential pattern mining to convert the activity logs into interpretable activity sequences. Analysis of the activity sequences identified distinct patterns of behavior that strongly predicted which students would transit from the familiar addition/subtraction word problem activity to the unfamiliar multiplication/division word problem activity. Students who showed the greatest and least compliance with the script were the least likely to attempt the multiplication/division activity. Students who showed more of a schematic problem solving process were more likely to continue to the multiplication/division activity.

Original languageEnglish
Pages167-174
Number of pages8
Publication statusPublished - 2016
Externally publishedYes
Event9th International Conference on Educational Data Mining, EDM 2016 - Raleigh, United States
Duration: Jun 29 2016Jul 2 2016

Conference

Conference9th International Conference on Educational Data Mining, EDM 2016
Country/TerritoryUnited States
CityRaleigh
Period6/29/167/2/16

Bibliographical note

Publisher Copyright:
© 2016 International Educational Data Mining Society. All rights reserved.

ASJC Scopus Subject Areas

  • Computer Science Applications
  • Information Systems

Keywords

  • Affinity propagation
  • Cognitive models
  • Sequential pattern mining

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