Context-Aware Systems and Applications, and Nature of Computation and Communication. 8th EAI International Conference, ICCASA 2019, and 5th EAI International Conference, ICTCC 2019, My Tho City, Vietnam, November 28-29, 2019, Proceedings

Research Article

A System and Model of Visual Data Analytics Related to Junior High School Students

Download
75 downloads
  • @INPROCEEDINGS{10.1007/978-3-030-34365-1_9,
        author={Dang Pham and Phuoc Tran},
        title={A System and Model of Visual Data Analytics Related to Junior High School Students},
        proceedings={Context-Aware Systems and Applications, and Nature of Computation and Communication. 8th EAI International Conference, ICCASA 2019, and 5th EAI International Conference, ICTCC 2019, My Tho City, Vietnam, November 28-29, 2019, Proceedings},
        proceedings_a={ICCASA \& ICTCC},
        year={2019},
        month={12},
        keywords={Visual graphs Students’ learning ability Visual analysis system (VAS) Visual data analysis model Visual data analysis criteria Visual data analysis questions},
        doi={10.1007/978-3-030-34365-1_9}
    }
    
  • Dang Pham
    Phuoc Tran
    Year: 2019
    A System and Model of Visual Data Analytics Related to Junior High School Students
    ICCASA & ICTCC
    Springer
    DOI: 10.1007/978-3-030-34365-1_9
Dang Pham,*, Phuoc Tran1,*
  • 1: Ho Chi Minh City Open University
*Contact email: pvdang@ntt.edu.vn, phuoc.tvinh@ou.edu.vn

Abstract

The assessment of students’ learning ability for career guidance in the future is a huge challenge. The development stage of students’ learning ability is considered from the sixth grade to the ninth grade. Student’s transcripts from grade 6 to grade 9 are used to assess students’ learning abilities. A transcript comparison of grades 6 through 9 is essential for each parent and analyst from there they can guide their children to comprehensive development of knowledge. The objective of this paper is to visually analyze student data using visual analysis approach, proposes a visual analysis system for data discovery with many variables (VAS), a visual data analysis model, visual data analysis criteria, visual data variables, multidimensional cube representing student data, and some visual data analysis questions based on visual graphs related to Junior High School students (JHSSs). Visual analysis of student data helps parents or analysts observe and extract useful information that they interact visual on visual graphs by asking themselves or answering the visual data analysis questions themselves when observing visual graphs by the retina to guide their children to choose the right knowledge chain and future jobs. Visual graphs represent the correlation between subjects and especially the comparison of a subject in the academic years together to help parents and analysts see clearly the trend of the development of students’ learning abilities by visual data analysis model.