Mining the National Career Assessment Examination Result Using Clustering Algorithm

International Conference on Information Technology and Digital Applications 2017

计算机科学

Pagudpud, M.V.^1 ; Palaoag, T.T.^2 ; Padirayon, L.M.^3

Quirino State University, Quirino, Philippines^1

University of the Cordilleras, Baguio City, Philippines^2

Cagayan State University, Cagayan, Philippines^3

关键词: Clustering techniques;    Density-based spatial clustering of applications with noise;    Educational improvement;    Expectation;    maximizations;    Innovative strategies;    Knowledge extraction;    Silhouette indices;    Support vector clustering algorithm;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/325/1/012001/pdf
DOI  :  10.1088/1757-899X/325/1/012001

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

Education is an essential process today which elicits authorities to discover and establish innovative strategies for educational improvement. This study applied data mining using clustering technique for knowledge extraction from the National Career Assessment Examination (NCAE) result in the Division of Quirino. The NCAE is an examination given to all grade 9 students in the Philippines to assess their aptitudes in the different domains. Clustering the students is helpful in identifying students' learning considerations. With the use of the RapidMiner tool, clustering algorithms such as Density-Based Spatial Clustering of Applications with Noise (DBSCAN), k-means, k-medoid, expectation maximization clustering, and support vector clustering algorithms were analyzed. The silhouette indexes of the said clustering algorithms were compared, and the result showed that the k-means algorithm with k = 3 and silhouette index equal to 0.196 is the most appropriate clustering algorithm to group the students. Three groups were formed having 477 students in the determined group (cluster 0), 310 proficient students (cluster 1) and 396 developing students (cluster 2). The data mining technique used in this study is essential in extracting useful information from the NCAE result to better understand the abilities of students which in turn is a good basis for adopting teaching strategies.