Dharmapatni, Pande Ni Putu Vania
Unknown Affiliation

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

Imbalance in Teacher Readiness Between Technological Self-Efficacy and Ethical Awareness in the Era of AI Humanification Dharmapatni, Pande Ni Putu Vania; Santosa, Made Hery; Paramartha, Anak Agung Gede Yudha
Jurnal Studi Guru dan Pembelajaran Vol. 9 No. 1 (2026): Januari - April 2026
Publisher : Universitas Cokroaminoto Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30605/jsgp.9.1.2026.8337

Abstract

The development of Generative Artificial Intelligence (GenAI) has transformed assessment practices in English as a Foreign Language (EFL) learning, particularly through the emergence of AI humanification, where the boundaries between authentic student writing and AI-generated text become increasingly blurred. This study aims to analyze secondary school English teachers’ readiness in addressing these challenges. This research employed a sequential explanatory mixed-method design involving 23 EFL teachers from nine senior high schools in Buleleng Regency, selected through purposive sampling. Data were collected using a modified Readiness Artificial Intelligence Scale (RAIS) questionnaire and semi-structured interviews. Quantitative data were analyzed using descriptive statistics, while qualitative data were analyzed using thematic analysis. The findings reveal a structural imbalance in teacher readiness. While teachers demonstrate high levels of technological self-efficacy in using AI, their ability to detect AI misuse and verify student authenticity remains limited. Teachers adopt adaptive strategies such as restricting device use, implementing oral verification, and repositioning AI as a supportive tool rather than a substitute. These findings imply that teacher readiness is multidimensional and develops unevenly, highlighting the need for assessment redesign, ethical governance, and institutional support to maintain academic integrity in AI-mediated learning environments.