Fostering digital competence in pre-service mathematics teachers through learning analytics and mobile app use

Aizhan Almat, Serik Daiyrbekov, Indira Omarova, Raushan Sherimova

2026

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DOI 10.18488/61.v14i2.4851
Data confidence 70 medium
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Abstract

The rapid integration of digital technologies into higher education highlights the need to understand how mobile applications contribute to the development of digital competence in teacher education. This study investigates the relationship between mobile app usage behaviors and competence growth among pre-service mathematics teachers, combining the DigCompEdu framework with behavioral learning analytics. By addressing an underexplored higher education context characterized by high mobile connectivity but limited formal EdTech integration, the research offers insights rarely captured in studies conducted in digitally mature systems. A quasi-experimental quantitative design was implemented with 98 undergraduate pre-service mathematics teachers at O. Zhanibekov South Kazakhstan Pedagogical University. Digital competence was measured at two points (pre-test and post-test) using a validated survey instrument (Cronbach’s α = 0.685). Learning analytics indicators session frequency, app diversity, and self-rated productivity were analyzed through linear regression, Pearson correlation, and non-parametric tests. Results indicate that depth of engagement, reflected in session frequency, is a stronger predictor of competence growth than tool diversity alone, while self-rated productivity shows a positive, though non-significant, trend. These findings extend the DigCompEdu framework by linking its competence domains to objective behavioral indicators and metacognitive self-assessment measures. The study offers transferable methodological and practical insights for curriculum designers, teacher educators, and policymakers aiming to integrate digital tools into teacher preparation programs in diverse higher education contexts.