Embedding parallel computing readiness in database education: quasi-experimental evidence from Kazakhstan
Abstract
Although modern database systems increasingly rely on parallel and distributed execution, parallel computing is often taught separately from database courses. This study addresses this gap by embedding parallel computing readiness directly into database education through a competency-based instructional module. The study designed and evaluated an integrated module that introduced students to parallel execution reasoning through authentic database tasks. A quasi-experimental pre-test/post-test design with an experimental group (EG) (N=81) and a control group (CG) (N=71) was utilized to assess learning outcomes over four competency dimensions: parallel computing readiness, content/theoretical competence, organizational/practical competence, and motivational competence. Clear evidence of a shift from low competency levels to average and high competency levels within the EG was evident across all competency dimensions, with the strongest changes observed in content/theoretical competence, where low-level ratings decreased from 87.7% to 25.9%, and organizational/practical competence, where low-level ratings decreased from 88.9% to 37.0%. In contrast, the CG showed only limited improvement and remained predominantly at the low level across the main competency dimensions. The study provides support for the integration of parallelism with authentic database projects and offers a replicable model for assessing and developing parallel computing readiness in modern database curricula.
Keywords
Cloud databases; Competency-based learning; Database systems education; Parallel computing education; Performance-aware structured query language; Quasi-experimental design
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PDFDOI: https://doi.org/10.11591/eei.v15i5.12343
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Bulletin of Electrical Engineering and Informatics (BEEI)
ISSN: 2089-3191
,
e-ISSN: 2302-9285
This journal is published by the
Institute of Advanced Engineering and Science (IAES)
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