Heatmap and Hierarchical Clustering Analysis to Highlight Changes in Young Children’s Developmental Progressions Using Virtual Manipulative Mathematics Apps

Christina Lommatsch, Stephen Tucker, Patricia S. Moyer-Packenham, Juergen Symanzik

Research output: A Conference proceeding or a Chapter in BookChapterpeer-review

Abstract

The purpose of this study was to examine what patterns were revealed using heatmaps with hierarchical clustering to examine preschooler’s performance, speed, and developmental progressions in counting and seriation. The chapter describes a study conducted with 35 preschoolers who used six touchscreen virtual manipulative mathematics apps in two different learning sequences: counting and seriation. The analysis employed heatmaps coupled with hierarchical clustering to highlight changes in children’s performance, speed, and developmental progressions, between a pre- and post- assessment app after using two learning apps. This method allowed for analysis of individual and whole group data examining several tasks within each app and also several apps within each learning sequence. The analysis revealed different clusters of children grouped according to their developmental progressions which were related to incremental changes in performance and speed from the Pre to Post App use.

Original languageEnglish
Title of host publicationUsing Mobile Technologies in the Teaching and Learning of Mathematics
EditorsNigel Calder, Kevin Larkin, Nathalie Sinclair
Place of PublicationSwitzerland
PublisherSpringer
Chapter10
Pages167-187
Number of pages11
Volume12
Edition1
ISBN (Electronic)9783319901794
ISBN (Print)9783319901787
DOIs
Publication statusPublished - 2018
Externally publishedYes

Publication series

Name Mathematics Education in the Digital Era

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