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

Lommatsch, Christina W.; Tucker, Stephen I.; Moyer‐Packenham, Patricia S.; Symanzik, Jürgen

doi:10.1007/978-3-319-90179-4_10

Cited by 3 publications

(1 citation statement)

References 20 publications

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“…Additionally, a heatmap was built. This is another way to visualize hierarchical clustering and consist in a graphical representation of data that uses a system of color-coding to represent different values (Lommatsch, Tucker, Moyer-Packenham, & Symanzik, 2018). The columns/rows of the data matrix are re-ordered according to the hierarchical clustering result, putting similar observations close to each other (DataNovia, 2018).…”

Section: Application Of Hierarchical Clusteringmentioning

confidence: 99%

Clustering Applied to the Education: A K-means and Hierarchical Application

Gil-Vera¹,

Lópera²,

Quintero-López³

2020

RES

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Currently, most schools in the world use ICT, which is why students must make use of computers and mobile devices in and out of schools. Thanks to the use of technology, students are more interested and motivated to learn, considering that motivation is one of the main engines of learning, since it encourages activity and thought. On the other hand, motivation makes students spend more time working and therefore they are more likely to learn more. The aim of this paper was to present a clustering of European countries according to the number of desktop computers available to students in primary schools (ISCED 1), lower secondary schools (ISCED 2) and upper secondary schools (ISCED 3). Was used the database developed by the ES Open Data Portal for the year 2019 on "ICT in Education". For the classification were used the hierarchical clustering and K-means techniques and the statistical software Rcran 3.6.3. These techniques were used as they have the ability to group a large number of elements into clusters, based on the similarity learned. This paper concludes that the countries with the highest GDP are not the ones that have the most desktop computers in their schools. Bulgaria is the country with the major number of desktop computers in their schools.

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Section: Application Of Hierarchical Clusteringmentioning

confidence: 99%

Clustering Applied to the Education: A K-means and Hierarchical Application

Gil-Vera¹,

Lópera²,

Quintero-López³

2020

RES

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Mathematics Apps—Stormy with the Weather Clearing: Using Cluster Analysis to Enhance App Use in Mathematics Classrooms

Larkin

Milford

2018

Mathematics Education in the Digital Era

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Using the ACAT Framework to Evaluate the Design of Two Geometry Apps: an Exploratory Study

Larkin

Kortenkamp

Ladel

et al. 2018

Digit Exp Math Educ

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It is an increasingly common phenomenon that elementary school students are using mobile applications (apps) in their mathematics classrooms. Classroom teachers using apps might benefit from a tool, or a set of tools, to help them determine whether or not a given app is appropriate and how enhanced educational outcomes can be achieved via its use. In this article we investigate whether Artifact Centric Activity Theory (ACAT) can be used to create a useful tool for evaluating apps, present a review guide based on the theory and test it using a randomly selected geometry app [Pattern Shapes] based on unknown design principles that may or may not conform to design principles suggested in the research as best practice. In doing so we broaden the scope of ACAT by investigating [Pattern Shapes], an app that has additional requirements in terms of accuracy of external representations, and depictions of mathematical properties (e.g. rotations, symmetry), than is the case for place value concepts in [Place Value Chart] which was created using ACAT principles and has been the primary app evaluated using ACAT. We further expand the use of ACAT via an independent assessment of a second app [Click the Cube] by a novice, using the ACAT review guide. Based on our latest research, we argue that ACAT is highly useful for evaluating any mathematics learning app and this is a critical contribution if the evaluation of apps is to move beyond academic circles and start to impact student learning and teacher choice in mathematics classrooms.

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

Cited by 3 publications

References 20 publications

Clustering Applied to the Education: A K-means and Hierarchical Application

Clustering Applied to the Education: A K-means and Hierarchical Application

Mathematics Apps—Stormy with the Weather Clearing: Using Cluster Analysis to Enhance App Use in Mathematics Classrooms

Using the ACAT Framework to Evaluate the Design of Two Geometry Apps: an Exploratory Study

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