Saraswathy A/p Ramasundrum
Universiti Malaya

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Validation of Pre-Service STEM Teachers’ Acceptance and Use of Generative Artificial Intelligence Scale: Rasch Model Elsima Nainggolan; Saraswathy A/p Ramasundrum; Indra Maulana
Saqbe: Jurnal Sains dan Pembelajarannya Vol. 2 No. 1 (2025): Saqbe : Sains dan Pembelajarannya (Maret 2025)
Publisher : Universitas Sulawesi Barat

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Abstract

Generation Z pre-service STEM teachers, recognized as digital natives, possess strong potential to adopt Generative Artificial Intelligence (GAI) in educational contexts and advance its meaningful integration. Accordingly, this study aims to validate an instrument designed to measure their acceptance of and use of GAI. A quantitative cross-sectional survey was administered to 401 pre-service STEM teachers using a UTAUT2–TPB–based instrument. Data were collected via Google Forms and analyzed using Rasch modeling (Winsteps 3.7.3). The results confirm that the instrument possesses strong psychometric properties under the Rasch model. Analysis demonstrated high person (0.94) and item (0.97) reliabilities, well-defined separation indices, and acceptable item fit values, indicating that the scale effectively differentiates respondents and maintains stability across items. The unidimensionality test further supported that the instrument measures a single, coherent construct, reinforcing its internal structural integrity. Overall, these findings verify that the instrument is valid and reliable for assessing GAI acceptance and use among pre-service STEM teachers. The study offers both theoretical and practical contributions by providing a rigorously tested measurement tool to evaluate readiness for GAI adoption and integration in teacher education.
AI ACCEPTANCE AND USE IN MATHEMATICS PRE-SERVICE TEACHERS: A THEORY OF PLANNED BEHAVIOUR APPROACH Hilman Qudratuddarsi; Jumriani; Eli Meivawati; Saraswathy a/p Ramasundrum
Mathematics Education and Application Journal (META) Vol. 7 No. 2 (2025): December 2025
Publisher : Department of Mathematics Education Universitas Borneo Tarakan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35334/yn58ya38

Abstract

Artificial Intelligence (AI) is increasingly integrated into education, including mathematics learning, yet its successful implementation largely depends on teachers’ acceptance and readiness. This study aims to examine the determinants of AI acceptance and use among pre-service mathematics teachers by employing the Theory of Planned Behaviour (TPB), which comprises Attitude (AT), Social Norms (SN), Perceived Behavioral Control (PBC), Behavioral Intention (BI), and AI Use (AIU). A quantitative, cross-sectional survey design was used. Data were collected from 427 Generation Z pre-service mathematics teachers enrolled in three Indonesian universities using an online questionnaire. The instrument was adapted from a previously validated TPB-based scale, and data were analyzed using PLS-SEM with SmartPLS. The measurement model demonstrated excellent reliability and validity, and the structural model indicated very good fit (SRMR = 0.044). All hypothesized relationships were supported (p < 0.001). SN emerged as the strongest predictor of BI, followed by AT and PBC, while BI was the most powerful determinant of AIU (β = 0.849). These findings highlight the central role of social influence, positive attitudes, and technological efficacy in shaping pre-service teachers’ intentions and actual use of AI. The study implies that teacher education programs should design courses and practicum experiences that foster positive beliefs about AI, enhance digital competence, and leverage supportive social environments to promote meaningful AI integration in mathematics classrooms.   Keywords: Artificial Intelligence Acceptance, Artificial Intelligence Use, Educational technology, Mathematics Pre-service Teacher, Theory of Planned Behaviour,   Artificial Intelligence (AI) semakin banyak dimanfaatkan dalam pendidikan, termasuk pada pembelajaran matematika, namun keberhasilan integrasinya sangat bergantung pada penerimaan dan kesiapan calon guru. Penelitian ini bertujuan menganalisis faktor-faktor yang memengaruhi penerimaan dan penggunaan AI pada calon guru matematika menggunakan kerangka Theory of Planned Behaviour (TPB), yang mencakup Attitude (AT), Social Norms (SN), Perceived Behavioral Control (PBC), Behavioral Intention (BI) dan AI Use (AIU). Penelitian ini menggunakan pendekatan kuantitatif dengan desain cross-sectional. Sebanyak 427 calon guru matematika generasi Z dari tiga universitas di Indonesia berpartisipasi melalui pengisian kuesioner daring. Instrumen diadaptasi dari penelitian terdahulu berbasis TPB dan dianalisis menggunakan PLS-SEM melalui SmartPLS. Hasil menunjukkan bahwa model pengukuran memiliki reliabilitas dan validitas yang sangat baik, serta model struktural menunjukkan kelayakan yang tinggi (SRMR = 0,044). Semua hipotesis didukung secara signifikan (p < 0,001). SN muncul sebagai prediktor terkuat BI, diikuti AT dan PBC, sedangkan BI menjadi penentu utama AIU (β = 0,849). Temuan ini menegaskan pentingnya dukungan sosial, sikap positif, dan efikasi teknologi dalam mendorong niat dan perilaku penggunaan AI. Implikasinya, program pendidikan guru perlu merancang pelatihan dan pengalaman praktik yang menumbuhkan sikap positif, meningkatkan kompetensi digital, dan memanfaatkan pengaruh sosial yang konstruktif terhadap penggunaan AI dalam pembelajaran matematika.   Kata Kunci: Artificial Intelligence Acceptance, Artificial Intelligence Use, Educational technology, Mathematics Pre-service Teacher, Theory of Planned Behaviour.