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All Journal Afeksi: Jurnal Penelitian dan Evaluasi Pendidikan Jurnal Inovasi dan Teknologi Pendidikan Saqbe : Jurnal Sains dan Pembelajarannya
Tari, Suci Rizkina
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Decision Sciences, Operations Research & Management Education Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Unfolding Generation Z Pre-Service Elementary Teachers Positive Attitude Toward Artificial Intelligence: Rasch Model Analysis Meivawati, Eli; Ningthias, Dyah Puspitasari; Pravitasari Putri, Eka; Tari, Suci Rizkina; Qudratudarsi, Hilman; Yanti, Meili
Afeksi: Jurnal Penelitian dan Evaluasi Pendidikan Vol 6, No 4 (2025)
Publisher : Pusat Studi Penelitian dan Evaluasi Pembelajaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59698/afeksi.v6i4.487

Abstract

This study investigates the attitudes of pre-service elementary teachers in Indonesia toward artificial intelligence (AI) using Rasch model analysis. As future educators, their perceptions of AI are crucial for the successful integration of technology in educational practices. The research involved 244 participants from the Elementary Teacher Education program in West Sulawesi, Indonesia, selected based on inclusion criteria such as year of study and experience with AI applications in learning. The instrument, adapted with 12 items measuring positive attitudes toward AI, was validated through checks for reliability, item separation, fit statistics, and unidimensionality. Data were analyzed using WINSTEPS software to generate Wright maps and conduct Differential Item Functioning (DIF) analysis. Findings reveal that pre-service teachers generally demonstrate a moderate to high positive attitude toward AI, with higher-year students and those with more frequent AI usage exhibiting stronger positive attitudes. DIF analysis shows significant differences in item endorsement based on year of study and supported by one-way ANOVA results. These results suggest that greater exposure to AI correlates with more favorable attitudes. The study implies the need for structured AI integration in teacher education curricula to foster readiness and acceptance of AI in future teaching practices.
Generation Z Pre-service Science Teacher Artificial Intelligence Competence Self-Efficacy (AICS): A Survey Study Adam, Wahyuni; Qudratuddarsi, Hilman; Tari, Suci Rizkina; Putri, Eka Pravitasari
Saqbe: Jurnal Sains dan Pembelajarannya Vol 1 No 2 (2024): Saqbe : Sains dan Pembelalajarannya (Oktober 2024)
Publisher : Universitas Sulawesi Barat

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Abstract

Abstrak Penelitian ini mengkaji hubungan antar enam sub-konstruk (AI Knowledge (AIK), AI Pedagogy (AIP), AI Assessment (AIA), AI Ethics (AIE), Human-Centred Education (HCE), and Professional Engagement (PEN)? dari Artificial Intelligence Competence Self-Efficacy (AICS). Selain itu, penelitian ini juga mengeksplorasi pengaruh gender dan spesialisasi (kimia, fisika, biologi, dan sains) terhadap AICS. Penelitian ini menggunakan metode survei kuantitatif untuk menilai AICS pada 318 mahasiswa calon guru sains. Data dikumpulkan menggunakan instrumen yang telah divalidasi dan disesuaikan, mencakup enam sub-konstruk terkait AI. Analisis data dilakukan menggunakan SPSS versi 25, meliputi analisis korelasi, perbandingan gender dengan uji t independen, dan perbedaan spesialisasi menggunakan uji ANOVA satu arah dengan uji lanjutan LSD. Hasil deskriptif dan korelasi menunjukkan bahwa AI Knowledge dan AI Assessment adalah area yang paling dikuasai oleh peserta, dengan hubungan positif yang kuat di seluruh sub-konstruk. Perbandingan berdasarkan gender menunjukkan tidak ada perbedaan signifikan, yang mengindikasikan tingkat self-efficacy AI yang seimbang antara peserta laki-laki dan perempuan. Namun, analisis berdasarkan spesialisasi menunjukkan perbedaan signifikan pada AI Pedagogy dan AI Assessment, di mana mahasiswa jurusan Pendidikan Kimia dan Pendidikan Fisika menunjukkan kepercayaan diri yang lebih tinggi dibandingkan dengan jurusan pendidikan sains. Temuan ini menegaskan pentingnya pengembangan program pelatihan AI yang disesuaikan, spesifik sesuai disiplin ilmu, dan inklusif dalam pendidikan calon guru.
ChatGPT Acceptance and Use by Generation Z Pre-service Mathematics Teachers Lestari, Yusfa; Tari, Suci Rizkina; Ramadhani, Widya Putri; Qudratuddarsi, Hilman
Jurnal Inovasi dan Teknologi Pendidikan Vol. 3 No. 3 (2025): Jurnal Inovasi dan Teknologi Pendidikan
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/jurinotep.v3i3.141

Abstract

In today’s digital era, educational technology—particularly AI tools like ChatGPT—offers innovative solutions to enhance mathematics education. This study explores how Gen-Z pre-service mathematics teachers accept and use ChatGPT, guided by TPB and UTAUT2 frameworks, while also examining the roles of gender and year of study in shaping their behavior. This quantitative study used a cross-sectional survey with 157 Gen-Z pre-service mathematics teachers, selected via convenience sampling. Data were gathered using a validated questionnaire based on UTAUT, showing high reliability (α = 0.97). Analysis involved descriptive statistics, Pearson correlation, t-tests, and ANOVA to examine ChatGPT acceptance and use by gender and year of study. Descriptive statistics confirmed normal distribution, supporting parametric tests. Pearson coefficients revealed strong, significant correlations between behavioral intention and variables like social influence (r = 0.785) and perceived behavioral control (r = 0.777). Actual ChatGPT use was most correlated with perceived behavioral control (r = 0.784) and attitude (r = 0.738). All predictors, including performance expectancy, effort expectancy, and hedonic motivation, showed positive, significant relationships, supporting the relevance of UTAUT 2 and TPB frameworks in explaining ChatGPT adoption in educational contexts.
Co-Authors Adam, Wahyuni Meivawati, Eli Ningthias, Dyah Puspitasari Pravitasari Putri, Eka Putri, Eka Pravitasari Qudratudarsi, Hilman QUDRATUDDARSI, HILMAN Widya Putri Ramadhani Yusfa Lestari