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All Journal Afeksi: Jurnal Penelitian dan Evaluasi Pendidikan Saqbe : Jurnal Sains dan Pembelajarannya
Hasanuddin, Nurqadriyanti
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Education Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Do Generation Z Pre-Service ESL Teachers Perceive Artificial Intelligence Negatively? Rasch Analysis Hasanuddin, Nurqadriyanti; Amalia, Dinda Firly; Ramadhan, Teuku Muhammad Hary; Qudratuddarsi, Hilman
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.v6i4.502

Abstract

This study investigates the negative attitudes of pre-service English as a Second Language (ESL) teachers toward the integration of Artificial Intelligence (AI) in education. Using a quantitative cross-sectional survey design, data were collected from 363 undergraduate students enrolled in teacher education programs. The participants completed the Negative Attitudes Toward Artificial Intelligence (NATAI) scale which was validated through expert review. Rasch model analysis was employed to examine item fit, reliability, and unidimensionality. The instrument demonstrated high internal consistency (Cronbach’s Alpha = 0.84), strong person and item reliability (0.80 and 0.98, respectively), and solid construct validity. The Wright Map revealed a moderate to high concern among students, particularly about AI's emotional and ethical implications. Differential Item Functioning (DIF) analysis based on year of study and gender showed minimal variation across groups, with third-year students expressing slightly stronger ethical concerns. A one-way ANOVA and independent t-test confirmed no significant difference in attitudes based on the year of study, suggesting uniform skepticism across cohorts. These findings imply a need for teacher education curricula to address AI literacy and integrate balanced perspectives to prepare future educators for AI-enhanced classrooms.
Application of the Rasch Model for Validating Representational Systems and Chemical Reactions Diagnostic Instrument (RSCRDI) Lestari, Yusfa; Hasanuddin, Nurqadriyanti; Ira Saputri, Sukmawati; Zulfi Maulidita, Salizmi
Saqbe: Jurnal Sains dan Pembelajarannya Vol 1 No 2 (2024): Saqbe : Sains dan Pembelalajarannya (Oktober 2024)
Publisher : Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study seeks to evaluate the validity and reliability of the outcomes derived from the adoption of the Representational Systems and Chemical Reactions Diagnostic Instrument (RSCRDI). This research employs a quantitative, survey-based approach, involving 69 prospective chemistry teachers at a university in Indonesia. Prior to implementation, the instrument was translated from English to Indonesian using the back-translation method. The collected data were subsequently analyzed using Winstep, yielding strong validity and reliability results. The instrument exhibited a Cronbach's alpha of 0.65, a person reliability of 0.60, and an item reliability of 0.76. Furthermore, the construct validation results were favorable, as evidenced by mean score (MNSQ), Z-standard (ZSTD), and point measure correlation (Pt Mea Corr) indices. These findings indicate that the RSCRDI is a valid and reliable instrument for assessing conceptual understanding among prospective chemistry teachers in Indonesia.
Co-Authors Amalia, Dinda Firly Ira Saputri, Sukmawati QUDRATUDDARSI, HILMAN Ramadhan, Teuku Muhammad Hary Yusfa Lestari Zulfi Maulidita, Salizmi