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All Journal Bulletin of Electrical Engineering and Informatics
Zhana-Gul Yessendauletova
Karaganda National Research University named after E.A. Buketov
Electrical & Electronics Engineering

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Embedding parallel computing readiness in database education: quasi-experimental evidence from Kazakhstan Saule Zhumagulova; Ainur Tokzhigitova; Gulnur Abildaeva; Zhana-Gul Yessendauletova; Leilya Fazylova
Bulletin of Electrical Engineering and Informatics Vol 15, No 5: October 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i5.12343

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.
Co-Authors Ainur Tokzhigitova Gulnur Abildaeva Leilya Fazylova Saule Zhumagulova