Work

Integration of SAMR, TPACK, and Artificial Intelligence in Computer Science Teacher Education: Impact on Academic Achievement and Digital Competencies

Year: 2026

Type: article

Abstract: The rapid digital transformation of teacher education requires instructional models that integrate established pedagogical frameworks with emerging Artificial Intelligence (AI) tools. This study investigates the effectiveness of a unified Substitution, Augmentation, Modification, Redefinition-Technological Pedagogical Content Knowledge-Artificial Intelligence (SAMR–TPACK–AI) framework for enhancing learning outcomes among pre-service computer science teachers. A quasi-experimental design was implemented with over 150 participants across control and experimental groups, using validated instruments and mixed-methods analysis (Analysis of Covariance (ANCOVA), Linear Mixed Model (LMM)). Findings demonstrate significant gains in the experimental group: academic performance increased by 12.2 percentage points, motivation by 0.52 points, and digital competencies by 14.9 points. Cross-disciplinary outcomes also improved, including critical thinking and teamwork skills. The results provide empirical validation of the integrated SAMR–TPACK–AI framework as an effective digital learning design. The study offers a novel conceptual contribution to AI-enhanced digital pedagogy and provides practical implications for developing sustainable, future-oriented teacher education programs.

Source: International Journal of Information and Education Technology

DOI: 10.18178/ijiet.2026.16.5.2607

Authors: Elmira Abdrashova, Zhanar Kemelbekova, Gulbakhram Beissenova, Aliya Utеbayeva, Zhanat Umarova

Institution: M.Auezov South Kazakhstan State University

Language: English

Topic: Artificial Intelligence in Education

Subfield: Education

Field: Social Sciences

Domain: Social Sciences

SDG: Quality education

Open Access status: diamond

OpenAlex ID: W7161961003