A quantitative analysis of Educational Data through the Comparison between Hierarchical and Not-Hierarchical Clustering

Di Paola B; Fazio C.

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7 Citazioni (Scopus)

Abstract

Many research papers have studied the problem of taking a set of data and separating it into subgroups through the methods of Cluster Analysis. However, the variables and parameters involved in Cluster Analysis have not always been outlined and criticized, especially in the field of Science Education. Moreover, in the field of Science Education, a comparison between two different Clustering methods is not discussed in the literature. In this paper two different Cluster Analysis methods are described and the variables and parameters involved are discussed in order to clarify the information that they can supply. The clustering results obtained by using the two methods are compared and showed a good coherence between them. The results are interpreted and compared with the literature. More detail about the relationship between different student conceptions of modeling in physics was obtained.
Lingua originaleEnglish
pagine (da-a)4491-4512
Numero di pagine22
RivistaEurasia Journal of Mathematics, Science and Technology Education
Volume13
Stato di pubblicazionePublished - 2017

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Hierarchical Clustering
Cluster analysis
Cluster Analysis
Quantitative Analysis
Science Education
cluster analysis
Education
Chemical analysis
Clustering Methods
Physics
science
Clustering
Subgroup
Students
physics
education
Modeling
student
literature

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abstract = "Many research papers have studied the problem of taking a set of data and separating it into subgroups through the methods of Cluster Analysis. However, the variables and parameters involved in Cluster Analysis have not always been outlined and criticized, especially in the field of Science Education. Moreover, in the field of Science Education, a comparison between two different Clustering methods is not discussed in the literature. In this paper two different Cluster Analysis methods are described and the variables and parameters involved are discussed in order to clarify the information that they can supply. The clustering results obtained by using the two methods are compared and showed a good coherence between them. The results are interpreted and compared with the literature. More detail about the relationship between different student conceptions of modeling in physics was obtained.",
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T1 - A quantitative analysis of Educational Data through the Comparison between Hierarchical and Not-Hierarchical Clustering

AU - Di Paola B; Fazio C.

AU - Battaglia, Onofrio Rosario

AU - Fazio, Claudio

AU - Di Paola, Benedetto

PY - 2017

Y1 - 2017

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AB - Many research papers have studied the problem of taking a set of data and separating it into subgroups through the methods of Cluster Analysis. However, the variables and parameters involved in Cluster Analysis have not always been outlined and criticized, especially in the field of Science Education. Moreover, in the field of Science Education, a comparison between two different Clustering methods is not discussed in the literature. In this paper two different Cluster Analysis methods are described and the variables and parameters involved are discussed in order to clarify the information that they can supply. The clustering results obtained by using the two methods are compared and showed a good coherence between them. The results are interpreted and compared with the literature. More detail about the relationship between different student conceptions of modeling in physics was obtained.

UR - http://hdl.handle.net/10447/239875

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JO - Eurasia Journal of Mathematics, Science and Technology Education

JF - Eurasia Journal of Mathematics, Science and Technology Education

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