KnE Social Sciences

ISSN: 2518-668X

The latest conference proceedings on humanities, arts and social sciences.

Using Education Data Mining (EDM) and Tracer Study (TS) Data as Materials for Evaluating Higher Education Curriculum and Policies

Published date: Sep 28 2022

Journal Title: KnE Social Sciences

Issue title: 4th International Conference on Education and Social Science Research (ICESRE)

Pages: 26–35

DOI: 10.18502/kss.v7i14.11948

Authors:

Muhammad Arifin - arifin.m@umk.ac.id

Widowati .

Farikhin .

Abstract:

The policy-making process is influenced by the results of a good evaluation process. However, to get valid results, the evaluation process requires supporting data and technology. Higher education produces huge amounts of data but is still lacking in turning it into useful information. With the rapid development of information technology, higher education data must be processed into information that can be used as an evaluation and basis for making quick and accurate policies. Educational Data Mining (EDM) is a technique used to measure students’ academic achievement to improve their results, assess the learning process, evaluate the overall quality of education, etc. Besides, the relevance of the curriculum followed by a university and the competencies possessed can be analyzed using a tracer study (TS). The current study uses EDM to extract information from higher education data and tracer study results. The relationship between higher education data and TS data was analyzed. The results indicated that not all students with higher GPA scores get jobs per the competencies they had in college, however, those with higher GPAs and who were actively organized during college are easier to find work. The study results must be considered as material for curriculum evaluation and for making higher education policies.

Keywords: higher education, Educational Data mining development, Tracer Study, curriculum evaluation, policy making

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