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A Data-centric Approach to Tracking Student Academic Performance and Progression.

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Title: A Data-centric Approach to Tracking Student Academic Performance and Progression.
Authors: Ibarra-Esquer, Jorge E.1 jorge.ibarra@uabc.edu.mx, Flores-Rios, Brenda L.2 brenda.flores@uabc.edu.mx, Astorga-Vargas, Maria A.3 angelicaastorga@uabc.edu.mx, González-Ramírez, Maria L.1 maria.gonzalez@uabc.edu.mx, Justo-López, Araceli C.3 araceli.justo@uabc.edu.mx, Chávez-Valenzuela, Gloria E.1 chavez@uabc.edu.mx
Source: IAENG International Journal of Computer Science. Dec2024, Vol. 51 Issue 12, p1968-1979. 12p.
Subjects: State universities & colleges, Engineering schools, Graduation rate, Data mining, Academic achievement
Abstract: Tracking student performance individually and as a group is a crucial activity for educational institutions. It serves as an indicator of success and provides valuable data for self-assessment and decision-making. Some important metrics and statistics can be used to understand student performance and progression. Examples include the number of students in a cohort or academic period, dropout and graduation rates, and failure and success rates for specific courses. These indicators can provide a comprehensive overview of how students are doing overall. However, the process of dealing with high volumes of data from different sources that are needed to calculate, present, explain, analyze, and visualize these indicators is not always a streamlined one. As part of a continuous improvement strategy in an engineering college at a public university in Mexico, a new role was defined to manage historical and current student data. Its primary objective was to establish a consistent and flexible system for collecting, organizing, processing, analyzing, and sharing student performance indicators from institutional data. The goal was to create an approach for tracking students’ progression at college, program, and individual levels. This paper describes the data approach that guided this process, highlighting the dynamic reports, visualizations, and tools created to enhance data and improve decision-making. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:Tracking student performance individually and as a group is a crucial activity for educational institutions. It serves as an indicator of success and provides valuable data for self-assessment and decision-making. Some important metrics and statistics can be used to understand student performance and progression. Examples include the number of students in a cohort or academic period, dropout and graduation rates, and failure and success rates for specific courses. These indicators can provide a comprehensive overview of how students are doing overall. However, the process of dealing with high volumes of data from different sources that are needed to calculate, present, explain, analyze, and visualize these indicators is not always a streamlined one. As part of a continuous improvement strategy in an engineering college at a public university in Mexico, a new role was defined to manage historical and current student data. Its primary objective was to establish a consistent and flexible system for collecting, organizing, processing, analyzing, and sharing student performance indicators from institutional data. The goal was to create an approach for tracking students’ progression at college, program, and individual levels. This paper describes the data approach that guided this process, highlighting the dynamic reports, visualizations, and tools created to enhance data and improve decision-making. [ABSTRACT FROM AUTHOR]
ISSN:1819656X